Intent, Named Entity & Chatbots

Notes:

A named entity is a real-world object or concept that can be identified and labeled with a proper name or noun. Named entities can include people, places, organizations, products, and events, among other things. In natural language processing and information extraction, named entities are often tagged or identified in text in order to extract specific information about them or to understand the context in which they are mentioned. For example, a named entity recognition system might be used to extract the names of people and organizations mentioned in a news article, or to identify the location of an event. Named entities can be a useful way to structure and organize information, and they are often used in search engines and other information retrieval systems to help users find specific information more easily.

In the context of chatbots, named entities and intents are often related in that they can both be used to understand and interpret the meaning of a user’s input. Named entities refer to real-world objects or concepts that can be identified and labeled with a proper noun or name, such as people, places, organizations, and products. Intents, on the other hand, refer to the goals or objectives behind a piece of text or speech, or the underlying meaning of a message.

In a chatbot context, named entities and intents can be used together to understand the meaning of a user’s input and to determine how to respond appropriately. For example, if a user asks a chatbot about the weather in a specific location, the chatbot might use named entity recognition to identify the location mentioned in the user’s message, and then use intent detection to understand that the user is asking for information about the weather. The chatbot could then use this information to provide the appropriate response, such as by looking up the current weather conditions for the specified location and returning them to the user.

Belief tracking is a technique used in artificial intelligence and natural language processing to track and update an AI system’s beliefs about the state of the world or a particular topic. Belief tracking involves continuously updating the AI’s beliefs based on new evidence or information that becomes available, in order to accurately represent the current state of the world or topic.
Intent detection is a process of identifying and interpreting the intent or purpose behind a piece of text or speech. In natural language processing, intent detection is often used to understand the goals or objectives of a user or to identify the underlying meaning of a message.
Proof tree is a graphical representation of the steps or reasoning used to reach a logical conclusion. In artificial intelligence and logic, proof trees are often used to demonstrate the validity of a conclusion by showing how it follows logically from a set of premises or assumptions.
Slot filling is a technique used in natural language processing to identify and extract specific pieces of information from a text or speech input. Slot filling involves identifying “slots” or specific fields that need to be filled in with information, and then using natural language processing techniques to extract the relevant information from the input. For example, a slot filling system might be used to extract the date, location, and time of an event mentioned in a sentence. Slot filling can be useful for extracting structured data from unstructured text or for identifying specific pieces of information in a conversational context.

Resources:

Wikipedia:

References:

Intent Detection and Slots Prompt in a Closed-Domain Chatbot
A Nigam, P Sahare, K Pandya – 2019 IEEE 13th International …, 2019 – ieeexplore.ieee.org
… shows how we can solve two different yet connected problems of intent detection and … Vocabulary Size 4229 Number of Entities 14 Number of Intents (subcategories) 19 Training … shown how using context specific Named Entity Tagging has helped us improve the performance …

A Novel In-House Implementation of a Chatbot Framework
A Singh, K Ramasubramanian, S Shivam – Building an Enterprise Chatbot, 2019 – Springer
… restTemplate = new RestTemplate(); /* This method takes a user utterance and session as an input, obtains matched intent from an intent classification service, performs named entity recognition on slots … We covered intent, intent matcher service, and matched intents so far …

Real-World Conversational AI for Hotel Bookings
B Li, N Jiang, J Sham, H Shi… – 2019 Second International …, 2019 – ieeexplore.ieee.org
… IV. MODELS Our conversational AI uses machine learning for three separate, cascading tasks: intent classification, named entity recognition (NER), and … A. Intent model The intent model processes each incoming user message and classifies it as one of several intents …

Development of the text analysis software agent (chat bot) for the library based on the question and answer system TWIN
A Ivanovskaya, K Aksyonov, I Kalinin… – ITM Web of …, 2019 – itm-conferences.org
… Named entity is a word or phrase intended for a specific, well-defined object or phenomenon … sent by the user are shown as lines starting with * in the format intent{“entity1”:”value … defines the universe in which assistant operates (see figure 7). It specifies the intents, entities, slots …

EMERGENCY PATIENT CARE SYSTEM USING CHATBOT
P Raj, R Murali Krishna, SM Krishna, KH Vardhan… – ijtre.com
… Named Entity Recognition: The medical chatbot looks for categories of words, like the name of the product, the user?s name or address … For the previous example, the category(intent) is#pain … When the user’s input is received, the conversation recognizes both intents and entities …

Chatbot in English Classrooms
M Vogel, I Nussbaumer – fhnw.ch
… The named entity recognition (NER) component identifies real world objects in tokens … It maps different wordings of a request to a common intent. This reduces the types of requests to a finite set of intents the application supports. 2.3 Language error detection …

# MeTooMaastricht: Building a chatbot to assist survivors of sexual harassment
T Bauer, E Devrim, M Glazunov, WL Jaramillo… – … Conference on Machine …, 2019 – Springer
… we used approach based on universal language model fine-tuning for named entity recognition, namely … In our case, intents are the different type of harassment, and entities are the … More specifically, we define three intent categories: physical abuse, verbal abuse and non-verbal …

Survey of Textbased Chatbot in Perspective of Recent Technologies
B Som, S Nandi – … Conference, CICBA 2018, Kalyani, India, July …, 2019 – books.google.com
… The other is the word-level information extraction such as named entity recognition and slot filling … user input is semantically checked with the prior knowledge to trigger corre- sponding intent … 1. Smarter and can learn alternative phrases which can trigger intents and alternative …

Contract Statements Knowledge Service for Chatbots
B Ruf, M Sammarco… – 2019 IEEE International …, 2019 – ieeexplore.ieee.org
… Chatbot framework Chatbot client Ask question 1. Intent classification (knowledge service selection) 2. Named-entity recognition (parameter value extraction) HTTP GET(query) HTTP 422 – Missing parameter Request parameter value Send parameter value HTTP GET …

Chatbots Assisting German Business Management Applications
F Steinbauer, R Kern, M Kröll – International Conference on Industrial …, 2019 – Springer
… Two existing libraries qualify for the task of German Named Entity Extraction, ie Stanford’s CoreNLP (cf … For each intent the user sent an average of 2.6 turns before the conversation was terminated or an intent switch was performed. A distribution by intents is given in Fig …

Automating Chalkboard support processes using a chatbot
JPY Brown-Pobee – 2019 – air.ashesi.edu.gh
… (NER_CRF) as the algorithm for entity extraction [11]. Named Entity Recognition is used … For instance, if a user types ‘I am unable to log in,’ the intent here is to report difficulty with logging in. I defined intents for our system listed below: Page 26. 19 …

Unsupervised dialogue intent detection via hierarchical topic model
A Popov, V Bulatov, D Polyudova… – Proceedings of the …, 2019 – aclweb.org
… we report a success in formalizing the clustering process suitable for unsupervised in- ference of user intents. The realization that any intent consists of two crucial parts: the entity relevant to the user’s re … of a hybrid bi-lstm-crf model to the task of russian named entity recognition …

Introduction to Microsoft Bot, RASA, and Google Dialogflow
A Singh, K Ramasubramanian, S Shivam – Building an Enterprise Chatbot, 2019 – Springer
… It also uses its Named Entity Recognition (NER) matching techniques to identify named entities in the user utterance … by the console as well, and your bot can be trained on missed intents that the … you simulate the model, it gets trained on the latest data provide to its intent engine …

Hybrid Question Answering System based on Natural Language Processing and SPARQL Query
M Rajosoa, R Hantach, SB Abbes, P Calvez – pdfs.semanticscholar.org
… Thus, these two proper names are linked together. Named entity recognition (NER) indicated the type of these two names which is “PERSON” type … For example: dealing with several intents in a question … First, we will have to rework the intent of the bot …

Deploying natural language intents with Lumi
AS Jacobs, RJ Pfitscher, RH Ribeiro… – Proceedings of the …, 2019 – dl.acm.org
… present Lumi, a novel intent reinement and deployment framework that allows network operators to express intents in natural … Figure 1: Intent reinement process … 2 LUMI Information extraction: we rely on Named Entity Recog- nition (NER) [5], which leverages machine learning to …

Server-Less Rule-Based Chatbot Using Deep Neural Network
SK Nagarajan – 2019 – diva-portal.org
… Short Term Memory AWS Amazon Web Services NLU Natural Language Understanding NER Named Entity Recognizer GRU … Deploy a scalable machine learning model for user intent prediction in … The term chatbot was coined by Mauldin[3] to represent systems aiming to pass …

Cognitive services and intelligent chatbots: current perspectives and special issue introduction
A Sheth, HY Yip, A Iyengar… – IEEE Internet Computing, 2019 – ieeexplore.ieee.org
… Examples from each category include: 1) language services are named entity recogni- tion and linking, sentiment analysis, and intent classification; 2 … While success so far is modest, engaging voice conversations (rather than text) in chatbot hold a significant promise for …

Potential of Bots for Encyclopedia
M Saracevic, M Ebner, M Ebner – intelligence (AI) – ipsitransactions.org
… The “geo search” agent has seven intents categorized in two groups, the “search” and the … The intent groups help the chatbot understand when users want to search and when … is concerned with input processing, followed with input understanding where named entity and intent …

Multi-platform chatbot modeling and deployment with the jarvis framework
G Daniel, J Cabot, L Deruelle, M Derras – International Conference on …, 2019 – Springer
… This implies registering the user intents to the selected Intent Recognition Provider, connecting … An IntentDefinition is a named entity representing an user intention … The SpecifyRepository intent follows the OpenNewIssue one, and defines one outContext RepositoryContext, with …

An Architecture for Dynamic Conversational Agents for Citizen Participation and Ideation
S Ahmed – researchgate.net
… Actions and Fullfillment Once a Chatbot identifies the intent, it could optionally trigger an action to fulfill … sented by states and intents corresponding to state transitions. In this section, we … as Named Entity Recognition, language modeling, and sentence level classification. [18] 15 …

Improving NLU Training over Linked Data with Placeholder Concepts
T Schmitt, C Kulbach, Y Sure-Vetter – International Conference on …, 2019 – library.oapen.org
… is to link these static approaches by generalizing SQA into 3 steps (Named Entity Recognition and … and the classification of intents can be regarded as two separate tasks that can be … The intent classification pipeline uses the tokenized utterances created by the spaCy model [9 …

Incrementalizing RASA’s Open-Source Natural Language Understanding Pipeline
A Rafla, C Kennington – arXiv preprint arXiv:1907.05403, 2019 – arxiv.org
… user utterances are processed, for example an utterance can pass through a tokenizer, named entity recog- nizer … We use accuracy of intent and entity recog- nition as our task and metric … work as a reference resolution component to physical objects, not ab- stract intents), nor are …

Towards Better Understanding of Spontaneous Conversations: Overcoming Automatic Speech Recognition Errors With Intent Recognition
P ?elasko, J Mizgajski, M Morzy, A Szymczak… – arXiv preprint arXiv …, 2019 – arxiv.org
… Otherwise, we provide an approxima- tion of this list by running a named entity recog- nition model predictions on an n-best list (see Fig- ure 4). Finally, the null symbol ? means that … We perform the experiments with an intent library comprised of 313 intents in total …

Sémantické porozum?ní konverzaci
P Lorenc – 2019 – dspace.cvut.cz
… is a central component of the conversation AI system, we classify intent, do named entity recognition, analyze … to move to London.” We would like to extract the information that the intent is “change … system Alquist2, we require to catch not only the true named entities defined here …

Comparative Analysis of Approaches to Building Medical Dialog Systems in Russian
A Vatian, N Dobrenko, N Andreev… – … on Intelligent Data …, 2019 – Springer
… https://teamtreehouse.com/library/intents-entities-and-dialogs … Quimbaya, AP, Munera, AS, Rivera, RAG et al.: Named entity recognition over electronic health records through a combined … N., Fan, W., Li, Y., Lu, C.-T., Yu, PS: Bringing Semantic Structures to User Intent Detection in …

Chat with Bots Intelligently: A Critical Review & Analysis
R Dsouza, S Sahu, R Patil… – … on Advances in …, 2019 – ieeexplore.ieee.org
… If the users were to pose long questions, containing several intents, then the bot would likely pick the intent with the highest probability and reply to that … Classification of intent into categories and subcategories using RNNs, Finding entities using Named Entity Taggers in …

Automatically responding to customers
R Huijzer – pure.tue.nl
… For example, ‘London’ is a location and ‘tomorrow’ is a date. Intents and entities are used by chatbots to understand the text written by users … Often the chatbot needs to know more than just the intent … Named-entity recognition (NER) can be used to find this information …

An Information Retrieval-based Approach for Building Intuitive Chatbots for Large Knowledge Bases.
A Lommatzsch, J Katins – LWDA, 2019 – ceur-ws.org
… detec- tion of user intents several dozen training examples per intent are needed … this approach not applicable for scenarios characterized by a large collection of intents … knowledge representation [5,9]. Linguistic approaches are applied, such as Named Entity Recognition and …

Building Chatbots with Python
S Raj, S Raj, Karkal – 2019 – Springer
… 42 Named-Entity Recognition ….. 44 … 71 Creating Intents and Adding Utterances ….. 72 … 72 Item Description Intent and Belonging Entities ….. 73 …

A hybrid convolutional and recurrent network approach for conversational AI in spoken language understanding
IMTL Douai – Fourth Conference on Software Engineering and …, 2019 – seim-conf.org
… In training, we compared between dif- ferent models for NER (Named Entities Recognition) system … tasks in the natural language processing community, such as parsing and named entity extraction … focused on slot tagging without paying attention to the other intent classi- fication …

AskCO: A Multi-language and Extensible Smart Virtual Assistant
M Atzeni, M Atzori – 2019 IEEE Second International …, 2019 – ieeexplore.ieee.org
… Some features used by AskCO include semantic similarity measures computed using Word Embeddings and Named Entity Disambiguation … All such intents implement a common Intent interface and refer to contexts like: ? renewing documents; ? booking doctor’s appointments …

AnaBot: Lessons from Building a Serial Chatbot in Collaboration with Analysts and Linguists
H Liu, J Yang, Q He – kdd.org
… in that it is the first end-to-end machine learning model based chatbot on knowledge … 3. Question2SQL: If the question carries a metric intent, we generate an SQL query to retrieve … The components in yellow are handled by the Spacy Named entity tagger [3]. The component in …

Question Understanding Based on Sentence Embedding on Dialog Systems for Banking Service
KJ Oh, HJ Choi, S Kwon, S Park – 2019 IEEE International …, 2019 – ieeexplore.ieee.org
… Finally, the system analyze meanings and intents of the questions, and searching correct … technology, we have been able to more accurately analyze the intent of the … Choi, ”Machine learning Based Boundary Detection and Dictionary Expansion for Named Entity Recognition …

Conversational AI: An Overview of Methodologies, Applications & Future Scope
P Kulkarni, A Mahabaleshwarkar… – 2019 5th …, 2019 – ieeexplore.ieee.org
… A. Named Entity Recognition (NER) NER deals with identifying and separating the named entities of a … successful than earlier and traditional machine learning methods at intent classification … [18] have proposed two deep hierarchical LSTM models for classifying dialogue intents …

Graph2Bots, Unsupervised Assistance for Designing Chatbots
JL Bouraoui, S Le Meitour, R Carbou… – Proceedings of the 20th …, 2019 – aclweb.org
… We begin with an anonymization pro- cess to replace the named entities (like customer name, phone number … architecture, he can use it to feed the dialog flow in a chatbot creation tool. The speech turns may constitute ex- amples for the intent detection; the most represen- tative …

Deep neural architecture with character embedding for semantic frame detection
FZ Daha, S Hewavitharana – 2019 IEEE 13th International …, 2019 – ieeexplore.ieee.org
… system of representation has been used in some recent work, especially in Named-Entity Recognition (NER) … 4,478 13,084 # Dev 500 700 # Test 893 700 |V | 722 11,241 # Intents 21 7 … slightly better in the slot filling task, BiLSTM outperforms BiGRU in intent detection, leading to …

Chatting with Plants (Orchids) in Automated Smart Farming using IoT, Fuzzy Logic and Chatbot
S Wiangsamut, P Chomphuwiset, S Khummanee – researchgate.net
… algorithm breaks down the query something like this: Orchid [intent] / need: temperature [intent] / inside farm … machine learning algorithms which has the following steps: Tokenization, Sentiment Analysis, Normalization, Named Entity Recognition and … Figure 3: Chatbot’s workflow …

Cognitive interaction with virtual assistants: From philosophical foundations to illustrative examples in aeronautics
D Bernard, A Arnold – Computers in Industry, 2019 – Elsevier
… Finally, we wonder whether a state-of-the-art chat bot framework actually implements the needed level of cognitive … intentions is partially acknowledged in today’s frameworks to develop virtual assistants or chatbots: processing a user query starts by understanding his “intent” …

A chatbot for the banking domain
P Schmidtová – 2019 – dspace.cuni.cz
… 4.1 Processing a List of Possible Intents … In this thesis, we will refer to the meaning of the user’s message as intent … tagging and lemmatization (Straková et al., 2014), UDPipe for dependency parsing (Straka and Straková, 2017), and NameTag for named entity tagging (Straková …

Applied machine learning for smart data analysis
N Dey, S Wagh, PN Mahalle, MS Pathan – 2019 – books.google.com
… registered trademarks, and are used only for identification and explanation without intent to infringe … 1 1. Hindi and Urdu to English Named Entity Statistical Machine Transliteration Using Source … The origin for source language named entities are taken as either Indo-Aryan-Hindi …

Process Mining and Natural Language
C Brüß, EG Rocha, G Kudchadker, M Singhal… – 2019 – di-lab.tum.de
… Due to the limitations of intent recognition, we decided to only use intents for triggering sequences of … Figure 3: Google Dialogflow’s interface to create new intents … relies on spaCy, a free, open-source Python NLP library which offers tokenization, named entity recognition and …

Building an enterprise chatbot: Work with protected enterprise data using open source frameworks
A Singh, K Ramasubramanian, S Shivam – 2019 – books.google.com
… Chatbot for an Insurance Use Case…..230 Creating the Intents…..233 IrisConfiguration … into identifying the sources of data to mine for the intent from customer … how to deploy a complete in-house-built chatbot using an …

Building Conversational Interface for Customer Support Applied to Open Campus an Open Online Course Provider
A Herrera, L Yaguachi, N Piedra – 2019 IEEE 19th International …, 2019 – ieeexplore.ieee.org
… Intents Management Intent and sub-intent recognition/parsing … The component includes the following modules: tokenization, normalization, correction of typographical errors and common spelling mistakes, named entity recognition, and dependency parsing to discover …

Named entity recognition using gazetteer of hierarchical entities
M Štravs, J Zupan?i? – … Conference on Industrial, Engineering and Other …, 2019 – Springer
… Chatbot needs to extract information from the text it receives from a conversation. It needs to understand the intent of the text and important entities mentioned in the text. Named entity recognition (NER) is about finding the names of the entities in unstructured text …

Developing Enterprise Chatbots
B Galitsky – 2019 – Springer
… 20 2.1.6 Named Entities and Their Templates . . . . . 20 2.1.7 Information Retrieval . . . . . 22 2.1.8 Personalization . . . . . 22 2.1.9 Architecture of a Task-Oriented Chatbot . . . . . 23 2.2 History of Chatbots …

Natural Language Understanding in Smartdialog: A Platform for Vietnamese Intelligent Interactions
NTT Trang, NH Ky, H Son, NT Hung… – Proceedings of the 2019 …, 2019 – dl.acm.org
… the first problem, ie entity recognition, we need to locate and classify named entity mentioned in … and the training interface, the NLU workers that predict the entities and user’s intents … high accuracy of approximately 98.7% in “entity recognition” and 97.1% in “intent classification” …

Slugbot: Developing a computational model andframework of a novel dialogue genre
KK Bowden, J Wu, W Cui, J Juraska, V Harrison… – arXiv preprint arXiv …, 2019 – arxiv.org
… also developed our own named entity recognizer SlugNERDS [9, 7] because the existing named entity recognizers were … We develop an utterance intent ontology and develop a Neural Network model to recognize user intents. The intent ontology consists of 33 discrete intents …

Building an Enterprise Chatbot
A Singh, K Ramasubramanian, S Shivam – Springer
… Creating the Intents …..233 … you understand the processes in the banking industry and delves into identifying the sources of data to mine for the intent from customer … Learn how to deploy a complete in-house-built chatbot using an …

Multi-attribute categorization of MOOC forum posts and applications to conversational agents
N Capuano, S Caballé – International Conference on P2P, Parallel, Grid …, 2019 – Springer
… It is reasonable to suppose that similar considerations hold for intent, confusion and urgency … examples, it is possible to apply further NLU methodologies like named entity recognition [26] … The developed tool is able to detect intents, topics, sentiment, confusion and urgency of …

An overview of NLP based Chatbot
J Ghorpade-Aher, R Kontamwar, S Kukreja, T Karpe… – universalreview.org
… intent of the input instead of just obtaining information about the intent itself … i. Named Entity Recognition: It looks for different categories of words, similar to the name of … discusses the most commonly used supervised machine learning algorithms for the implementation of chatbot …

FASTDial: Abstracting Dialogue Policies for Fast Development of Task Oriented Agents
SS Tekiroglu, B Magnini, M Guerini – … of the 57th Annual Meeting of the …, 2019 – aclweb.org
… SAGE: SAVINGS AR: STATE: INFO CHECK SUCCESS AC: MESSAGE: EXECUTE INTENT AR: MESSAGE … setting up a completely functional dialogue agent with all 9 intents required from 3 … Explor- ing named entity recognition as an auxiliary task for slot filling in conversational …

Explainable and Transferrable Text Categorization
T Eljasik-Swoboda, F Engel, M Hemmje – International Conference on …, 2019 – Springer
… A primary task for digital assistants or chat bots is intent recognition: The detection of the task … The actual benchmark focuses on named-entity recognition within text. Therefore the benchmark contains the original text as well as one that is annotated with relevant named entities …

Chatbot Components and Architectures
B Galitsky – Developing Enterprise Chatbots, 2019 – Springer
… This module consists of a Named Entity Recognition and Disambiguation (NER) model and a template selection model … Intent analysis component will identify the user intent, so the system can handle the conversation with different strategies based on the intents …

Gunrock: A social bot for complex and engaging long conversations
D Yu, M Cohn, YM Yang, CY Chen, W Wen… – arXiv preprint arXiv …, 2019 – arxiv.org
… tion so that a named entity will not be segmented into multiple parts and an utterance with a … the sequence pipeline to generate complete segments, Gunrock detects (1) topic, (2) named entities, and (3 … In order to extract the intent for each segment, we designed MIDAS, a human …

Intelligent Chatbot for Requirements Elicitation and Classification
CSRK Surana, DB Gupta… – 2019 4th International …, 2019 – ieeexplore.ieee.org
… A training data file is prepared that consists of various possible intents and example user responses for … is used for the classification, and spaCy English language model is used for Named Entity Recognition … The chatbot is able to clearly identify the intent of the user, whether it is …

Towards European Portuguese Conversational Assistants for Smart Homes
M Ketsmur, A Teixeira, N Almeida… – 8th Symposium on …, 2019 – drops.dagstuhl.de
… While intents represent the purpose or goal, entities represent the context for that purpose. They are important nouns and named entities in the input text … Table 3 Illustrative examples for training Watson intents. Intent Examples English translation request Qual foi o [consumo] …

Katecheo: A Portable and Modular System for Multi-Topic Question Answering
S Hirekodi, S Sunny, L Topno, A Daniel… – arXiv preprint arXiv …, 2019 – arxiv.org
… 2 or DialogFlow3. To do this, a user would need to program an intent for each … It would be advanta- geous for such a chatbot to answer questions about food and entertainment, but … with each topic, the user supplies the sys- tem with a pre-trained Named Entity Recognition (NER …

Question-answering dialogue system for emergency operations
HY Chan, MH Tsai – International Journal of Disaster Risk Reduction, 2019 – Elsevier
… This is similar to the intent detection and the slot filling of language understanding modules. There are two tasks in QA: named entity recognition (NER) and question classification (QC). NER parses the afore-mentioned information (named entities) in the user’s input …

Improving the Annotation Efficiency and Effectiveness in the Text Domain
M Zlabinger – European Conference on Information Retrieval, 2019 – Springer
… The first project is about annotation of named-entities in medical publications … One annotation project that I am working on is about named-entity recognition in the medical domain—more … Third, the annotator marks questions in the list that have the same intent as the candidate …

A study of incorrect paraphrases in crowdsourced user utterances
MA Yaghoub-Zadeh-Fard, B Benatallah… – Proceedings of the …, 2019 – aclweb.org
… high quality train- ing samples, typically in the form of user ut- terances and their associated intents … For instance, in Example 8 of Table 1, the intent of paraphrase is to turn off … are caused by sentences that contain unusual words such as misspellings and named entities in the …

Identifying facts for chatbot’s question answering via sequence labelling using recurrent neural networks
M Nuruzzaman, OK Hussain – Proceedings of the ACM Turing …, 2019 – dl.acm.org
… Example of Hidden events are part-of-speech tags or Named Entity classes … This dataset contains annotations for 4 different types of named entities such as PERSON, LOCATION … first priority as template-based strategies such as entity-based templates, intent templates, and …

* Thing: Improve Anything to Anything Collaboration
G Corti, L Ambrosini, R Guidi, N Rizzo – Future of Information and …, 2019 – Springer
… for time expression recognition and temporal tagging, NLTK [14] and spaCy [15] for tokenization and Named Entity Recognition) as … Goal: The eventual intent of the collaborating parties … Intents: User intents interpreted by the interpretation layer that the story might need or want to …

Subject Recognition in Chinese Sentences for Chatbots
F Li, H Wei, Q Hao, R Zeng, H Shao… – … Conference on Natural …, 2019 – Springer
… extraction is usually based on linguistic rules which are constructed by named entity recognition and … choose the most important one: (1) Prioritize the parts which contain chatbots function intents … Speech Recognition, there exist a large number of mistakes in chatbot corpus that …

Computational linguistics: Introduction to the thematic issue
A Gelbukh – Computación y Sistemas, 2019 – cys.cic.ipn.mx
… Tunga Gungor from Japan and Turkey in her paper “Joint Learning of Named Entity Recognition and … social media platforms allow users to freely express their beliefs, opinions, thoughts, and intents … Identification of purchase intent in Twitter sphere is of utmost interest as it is …

Towards coherent and engaging spoken dialog response generation using automatic conversation evaluators
S Yi, R Goel, C Khatri, A Cervone, T Chung… – arXiv preprint arXiv …, 2019 – arxiv.org
… turns of the con- versation as a matrix (DAs × entities), these features are designed to capture the patterns of topic and intent shift distribution … Named Entity (NE) Overlap: We use named entity overlap between … Our named entities are obtained using SpaCy2. Papaioannou et al …

An Approach for Ex-Post-Facto Analysis of Knowledge Graph-Driven Chatbots–The DBpedia Chatbot
R Jalota, P Trivedi, G Maheshwari, ACN Ngomo… – … Workshop on Chatbot …, 2019 – Springer
… we use unsupervised clustering algorithms 9 to group user utterances and treat them as latent intents … Thus, simply relying on candidate pairs is not sufficient for intent classification … we use DBpedia Spotlight [9] which provides us the underlying schema type for named entities …

Self-Attentional Models Application in Task-Oriented Dialogue Generation Systems
M Saffar Mehrjardi – 2019 – era.library.ualberta.ca
… MLP Multi-Layer Peceptron NER Named-entity Recognition NLG Natural Language Generation … engaged when they feel that they have become friends with the chatbot. Ama … chatbots, and customer-service chatbots. Deployment of task-oriented chat …

Security vulnerability information service with natural language query support
C Rodriguez, S Zamanirad, R Nouri, K Darabal… – International Conference …, 2019 – Springer
… We identify the intents above by first focusing on intent type (i). We take each key token … In some cases, users may indicate the intent of finding items that satisfy a condition … Tokenization, dependency parsing and named-entity recognition were done using Stanford Core NLP 3.8 …

Augmenting dialogue response generation with unstructured textual knowledge
Y Wang, W Rong, Y Ouyang, Z Xiong – IEEE Access, 2019 – ieeexplore.ieee.org
… primary challenge is to model and generate informative words, such as named entities, especially when … [14] used latent variables to learn a distribution over potential conversational intents and generates … Assigning a fixed personality to a chatbot is one of the main challenges in …

Chatting about data
L Martinico – project-archive.inf.ed.ac.uk
… 43 5.1.1 Pretraining Language models . . . . . 44 5.1.2 Named Entity Recognition . . . . . 44 5.1.3 Wordreplacement … In this private conversation mode, use of chatbots is disabled; the only commercial chatbot platforms that …

A Robust Methodology for Building an Artificial Intelligent (AI) Virtual Assistant for Payment Processing
AP Sam, B Singh, AS Das – 2019 IEEE Technology & …, 2019 – ieeexplore.ieee.org
… software which helps the business serve multilingual customers; (iii) natural language processing algorithms like named entity extraction (NER … This is done through utterance intent mapping. But, before we begin the section, let us see what utterances and intents are from the …

Question generation based on chat?response conversion
SH Zhong, J Peng, P Liu – Concurrency and Computation: Practice … – Wiley Online Library
… However, the responses proposed by the chat?bot are only a passive answer or assentation, which does not arouse the … A. Named entity recognition … In the following, we use Stanford NER to identify Organization, Person, Location named entities in vocabulary and then match …

CHATBOT A digital assistant with built-in AI
F Gadea Llopis – 2019 – theseus.fi
… that seeks to locate and classify named entity mentions in unstructured text into pre-de … mendations. If the response has the intents IN, Type and Recommendations, the path 1 is obtained … There are different ways to implement the chatbot. This chatbot was for public use, and, it …

Automatic documentation of results during online architectural meetings
O Klymenko – 2019 – wwwmatthes.in.tum.de
… tasks include but are not limited to Part-Of-Speech (POS) tagging, Named Entity Recognition (NER … Table 2.2.: Overall scores for intent and entity [31 … offers manual transcripts with detailed annotations, including word-level timings, dialogue acts, named entities, topic segmentation …

Semantic vector learning for natural language understanding
S Jung – Computer Speech & Language, 2019 – Elsevier
… Visualization. 1. Introduction. Natural language understanding (NLU) is a central technique to implement natural user interfaces such as chatbot, mobile secretary, and smart speakers … follow: • Intent Matching: Intents of A and B are same. (eg …

Automatic Ontology Population Using Deep Learning for Triple Extraction
MH Su, CH Wu, PC Shih – 2019 Asia-Pacific Signal and …, 2019 – ieeexplore.ieee.org
… In Dialog State Tracking (DST), Mehta et al. [10] constructed a decision tree to determine the user intent with the help of the ontology … Therefore, ontology is useful for a chatbot system [14]-[15] … This task is like the Named Entity Recognition (NER) task …

Training Set Expansion Using Word Embeddings for Korean Medical Information Extraction
YM Kim – … Data Management, Polystores, and Analytics for …, 2019 – Springer
… to start from designing the overall conversational process as well as intent and slot … Unlike named entities, there are not many newly coined words if a benchmark dataset is … Using traditional metrics for named entity recognition is excessive because our result needs a manual …

Could you tell a bit more about your experience with the chatbot?
E de Louw, S Wubben – 2019 – drewhendrickson.github.io
… In the case that the chatbot misses a required entity for the intent of the user … discussion, sensitivity to social concerns or the ability to detect meaning or the right intents … Future works include detecting seasonal trends and Named Entity disambiguation by taking into account the …

Assessing the robustness of conversational agents using paraphrases
J Guichard, E Ruane, R Smith, D Bean… – 2019 IEEE …, 2019 – ieeexplore.ieee.org
… Paraphrases are identified based on common named entities (such as proper nouns), and are … and informal lexical substitutions (IS’).The robustness results for each intent are presented in … the same understanding difficulties for the CancelFlight and ChangeFlight intents, and for …

MSc in Computer Science
RB Sulaiman – researchgate.net
… 2.6.3.3 N-GRAMS ….. 31 2.6.3.4 NAMED ENTITY RECOGNITION (NER) …. 32 … Chatbot technology ? Types of chatbot ? Comparison of chatbots ? Functions of chatbot ? Syntactic analysis …

Natural Language Processing, Understanding, and Generation
A Singh, K Ramasubramanian, S Shivam – Building an Enterprise Chatbot, 2019 – Springer
… Since this book is about building an enterprise chatbot, we will focus more on the applications of PUG in natural languages rather than going deep into the foundations of the subject … Named Entity Recognition. Once we have the POS of the text, we can extract the named entities …

Artificial Intelligence for Innovation Readiness Assessment
T Eljasik-Swoboda, C Rathgeber… – … on Innovation and …, 2019 – ieeexplore.ieee.org
… Another task is to detect intent which is, what the user wants the AI to do. This can actually also be modeled as TC problem in which different intents that the AI … 27] C. Nawroth, F. Engel, T. Eljasik-Swoboda, M. Hemmje, “Towards enabling emerging named entity recognition as …

Artificial intelligence (AI) and its implications for market knowledge in B2B marketing
J Paschen, J Kietzmann, TC Kietzmann – Journal of Business & …, 2019 – emerald.com
… among others, automatic text summarization, personality insights, sentiment analysis, topic extraction and named entity recognition, ie classifying named entities in text … sources, Source Media creates prospect profiles and segments them based on users’ needs and intents …

Recent advances in neural question generation
L Pan, W Lei, TS Chua, MY Kan – arXiv preprint arXiv:1905.08949, 2019 – arxiv.org
… factors, including question type, content words, function words, and named entities … type identification, which is correlated with the question intention, as different intents may yield … exploring ques- tion pragmatics, where external contextual infor- mation (such as intent) can inform …

FastText-Based Intent Detection for Inflected Languages
K Balodis, D Deksne – Information, 2019 – mdpi.com
… are used for speech recognition and generation, machine translation, text classification, named entity recognition, text … There were 121 intents to be used for this dataset … For every predefined intent, the experts created approximately 10 utterances, with 1231 utterances in total …

Learning from Others’ Experience
S Höhn – Artificial Companion for Second Language …, 2019 – Springer
… Avatars, talking heads and embodied agents as well as integration of text-to-speech engines became nice-to-have extensions for chatbots because they appeared to positively influence users’ engagement in chat, though a simple chatbot was still hiding behind them (Stewart …

TUM Data Innovation Lab
H Agarwala, R Becker, M Fatima, L Riediger, A Belitski… – 2019 – di-lab.tum.de
… 4.1.5 NER CRF NER CRF is short for ”named entity recognition – conditional random fields”. The method of CRF is used to extract entities of the input … Additionally, we do not only get the confidence of the most likely intent but of all trained intents …

Spoken Dialogue Processing for Multimodal Human?Robot Interaction
T Kawahara – 2019 – researchgate.net
Page 1. 2019/10/14 1 Spoken Dialogue Processing for Multimodal Human?Robot Interaction Tatsuya Kawahara (Kyoto University, Japan) http://www.sap.ist.i.kyoto?u.ac.jp/~kawahara /pub/ICMI19?tutorial.pdf 1 Spoken Dialogue Systems (SDS) are prevailing …

Spjallmennis ráðgjafi-Íba
D Haberbusch, HR Steinarsdóttir, LOR Franca – 2019 – skemman.is
… Íba is able to successfully perform named entity recognition ?- a technique for information extraction that seeks to locate and classify named entities in text … The NLU library does the classification of ?intent ?(the outcome of a behavior) and extracts the ?entity ?(the …

Natural language understanding for dialogue systems using n-best lists
S Mansalis – MS thesis, 2019 – aueb.gr
… and non-task-oriented dialogue systems (also known as chatbots). Task-oriented dialogue … For example, a domain can be viewed as a group of intents which belong to the domain, and an intent consists of one or multiple slots/tags that define semantic keywords of this intent …

Linguistic classification: dealing jointly with irrelevance and inconsistency
L Franzoi, A Sgarro, A Dinu, LP Dinu – 12th International Conference on …, 2019 – arts.units.it
… topics, including but not limited to: deep learning; machine translation; opinion mining and sentiment analysis; semantics and discourse; named entity recognition; coreference … On a Chatbot Providing Virtual Dialogues Boris Galitsky, Dmitry Ilvovsky and Elizaveta Goncharova …

Pumice: A multi-modal agent that learns concepts and conditionals from natural language and demonstrations
TJJ Li, M Radensky, J Jia, K Singarajah… – Proceedings of the …, 2019 – dl.acm.org
… 1] use natural language inputs to identify parameterization in demonstrations, and APPINITE [21] uses natural language explanations of intents to resolve the … it’s hot” is true, but does not know how to perform this action (also known as intent fulfillment in chatbots [23]) …

Knowledge Management & Intelligent Search
A Masood, A Hashmi – Cognitive Computing Recipes, 2019 – Springer
… use of Microsoft Cognitive Service APIs such as Key-Phrase Extraction, Named Entity Recognition, OCR … the app is created, the browser will automatically navigate to the Intents screen … Click the Create new intent button, enter Complaints.SearchByCompany in the Intent name …

Natural language processing
R Akerkar – Artificial Intelligence for Business, 2019 – Springer
… Some businesses use chatbots to answer routine questions in help desks … Sentiment analysis, which determines the attitude, emotional state, judgement or intent of the writer … Named entity recognition: extracts the names of drugs, diseases, patients and pharma companies using …

Semantic Analysis
D Sarkar – Text Analytics with Python, 2019 – Springer
… cars, computers beating experienced players in their own games like Chess and Go, and more recently chatbots … scheme they use on their website at https://spacy.io/api/annotation#named- entities … We present the main named entity tags in the table depicted in Figure 8-4. Open …

Understanding EFL Linguistic Models through Relationship between Natural Language Processing and Artificial Intelligence Applications.
MS Keezhatta – Arab World English Journal, 2019 – academia.edu
… The techniques used in semantic analysis include named entity recognition (NER) or identifying such … sense of the human languages by machine operations like online chatbots, text summarization … it easier to detect such linguistic characteristics related to intent, timing, locations …

An Improved Word Representation for Deep Learning Based NER in Indian Languages
A AP, S Mary Idicula – Information, 2019 – mdpi.com
… reports that 60% of the total queries in search engines are named entities [3]. Hence identification of named entities from unstructured text has got significant attention in query processing. Question answering systems also make use of Named Entity Recognition …

Augmenting Abstract Meaning Representation for human-robot dialogue
C Bonial, L Donatelli, S Lukin, S Tratz… – Proceedings of the First …, 2019 – aclweb.org
… ticipants and floors into units according to the joint realization of an initiator’s intent … This latter moti- vation is especially important given that the tar- get human-robot dialogue is physically situated and therefore distinct from other dialogue systems, such as chat bots, which do not …

Expanding the Text Classification Toolbox with Cross-Lingual Embeddings
M M’hamdi, R West, A Hossmann, M Baeriswyl… – arXiv preprint arXiv …, 2019 – arxiv.org
… 5) with two flavors of CLTC (long news stories to be classified by top- ics versus short tweets to be classified for churn intent) show that … Other work that multi-task training the multi- lingual embeddings with the task at hand include (Wang et al., 2017) for named entity recognition …

Challenge discussion: advancing multimodal dialogue
J Allen, E André, PR Cohen, D Hakkani-Tür… – The Handbook of …, 2019 – dl.acm.org
… strategy in which one party starts a conversation, and provides information about their intent after which a … a plan standing behind the utterances, but for most of these systems, be they chatbot systems or … If someone asks for a named entity we extract that and we go and look for it …

Discourse-Level Dialogue Management
B Galitsky – Developing Enterprise Chatbots, 2019 – Springer
… These users’ intents of navigating from one portion of text to another can be represented … chatbot attempts to build a set of possible topics, possible understanding of user intent … Entity extraction, also known as entity name extraction or named entity recognition, is an information …

Seq-DNC-seq: Context Aware Dialog Generation System Through External Memory
D Kang, M Lee – 2019 International Joint Conference on Neural …, 2019 – ieeexplore.ieee.org
… If the dialog generation system does not properly catch the named entity, the user … K. Wegner, “The necessity of new paradigms in measuring human-chatbot interaction,” in … Continuous timescale long-short term memory neural network for human intent understanding,” Frontiers …

Dependency Parsing for Spoken Dialog Systems
S Davidson, D Yu, Z Yu – arXiv preprint arXiv:1909.03317, 2019 – arxiv.org
… Finally, NER only provides informa- tion about named entities which may or may not be the … The alternative would involve annotators trying to infer user intent from context, which makes … We collected a corpus of humans conversing with an open-domain dialog chatbot based on …

IrideR G: an Industrial Perspective on Production Grade End To End Dialog System
C Giannone, V Bellomaria, A Favalli, R Romagnoli – 2019 – ceur-ws.org
… 2019. Multi- lingual intent detection and slot filling in a joint bert- based model … 2018. Transfer learning for industrial appli- cations of named entity recognition … 2017. Sequential matching network: A new architecture for multi-turn response selection in retrieval-based chatbots …

A multi-task hierarchical approach for intent detection and slot filling
M Firdaus, A Kumar, A Ekbal… – Knowledge-Based Systems, 2019 – Elsevier
… Only after the correct detection of intents, the appropriate slots of the utterance can be extracted … Also, by handling intent and slot together, we can build an end-to-end natural language understanding (NLU) module for any task-oriented chatbot …

Enabling a Bot with Understanding Argumentation and Providing Arguments
B Galitsky – Developing Enterprise Chatbots, 2019 – Springer
… 13.1). Open image in new window Fig. 13.1. Fig. 13.1 A Chatbot handling argumentation. The purpose of argumentation analysis for chatbots is twofold. Firstly, it is a chatbot participation in an argumentation – driven dialogue …

A context-aware conversational agent in the rehabilitation domain
T Mavropoulos, G Meditskos, S Symeonidis… – Future Internet, 2019 – mdpi.com
… The intent of the presented, still ongoing, work is to rectify this deficiency by … beyond patient monitoring; it focuses on patient–doctor interaction over a chatbot-driven telemedicine … models are used for the extraction of sentence information such as named entities, speech act, or …

Conversational agents and negative lessons from behaviourism
M Gnjatovi? – Innovations in Big Data Mining and Embedded …, 2019 – Springer
… to implement socially believable 2 conversational agents whose functionalities go substantially beyond chatbots … not contain information that could help in recovering the intent encoded in … such as Wikipedia, Goodreads, Foursquare, etc.) that can be indexed with named entities …

Knowledge Graph-Driven Conversational Agents
J Bockhorst, D Conathan, G Fung – Knowledge Representation & …, 2019 – kr2ml.github.io
… parse in the system’s grammar that is in agreement with the user’s intent (right side of … called “small talk” for when users inquire about the age of the chatbot or where it … and statistical models learned with machine learning approaches akin to methods for named entity recognition …

Intent classification through conversational interfaces: Classification within a small domain
S Lekic, K Liu – 2019 – diva-portal.org
… order to be able to recognize the intents behind the user input within a small domain? 1.3 Purpose … intent behind it, that is, assign the input a certain category, and output the category … is enough. • Named Entity Recognition (NER) is a type of information extraction …

Viana: Visual interactive annotation of argumentation
F Sperrle, R Sevastjanova, R Kehlbeck… – … IEEE Conference on …, 2019 – ieeexplore.ieee.org
… enables various novel, linguistically-informed applications like semantic search en- gines, chatbots or human … Semantic interactions are typ- ically performed with the intent of refining or steering a … example, BRAT [61] can be used for the annotation of POS tags or named entities …

The datafication of the workplace
J Sánchez-Monedero, L Dencik – 2019 – orca.cf.ac.uk
… For example, Named Entity Recognizer (NER) allows for the label sequences of words such as ‘person’, ‘organization’, ‘time’, etc … Automated interview via chatbot Some companies are using chatbots to arrange interviews, perform preliminary interviews, get …

A Social Promotion Chatbot
B Galitsky – Developing Enterprise Chatbots, 2019 – Springer
… conversational thread, CASP needs to obtain a topic, or main entity (named entity) of this … to generate a query, we just identify its noun phrases and named entities and form … in big data exploration efficiency since they form multiple hypotheses concerning user intent and explore …

IMPLEMENTATION OF AN AUTOMATIC QUESTION ANSWERING SYSTEM USING MACHINE LEARNING
SA ABIR – 2019 – researchgate.net
… 1. The closed domain chatbots are those which can reply to a limited number of … This service can apply rules and generate scripted responses based on the user’s intent and data that is … internal mechanism and classification of artificial intelligence services to build a chatbot to …

ICSC 2019
L de Alwis, A Dissanayake, S Jiang, TF Hagelien… – computer.org
… Muthu Kumaran (Samsung R&D, Institute Bangalore),Session 4: Semantic Description,,Named Entity Recognition on … Zhou (Google, Mountain View) and Binbin Ruan (Google, Mountain, View),Intent Detection and Slots Prompt in a Closed-Domain Chatbot , 340, Amber …

Discovering the Functions of Language in Online Forums
Y Ismaeil, O Balalau, P Mirza – Proceedings of the 5th Workshop on …, 2019 – aclweb.org
… One of the most influential subsequent work by Searle (1976) focused on the addresser’s intent in using … an emotive message calls for a thoughtful and empathetic response) are beneficial for building smarter chatbots … Named entity recognition in tweets: An ex- perimental study …

Predicting User’s Intent from Text using Machine Learning Methods
A Katsalis – 2019 – repository.ihu.edu.gr
… Search engines, spoken language understanding (SLU) systems, chatbots and even … Table 1: Distribution percentages of intents Intent Distribution Percentage abbreviation 3% aircraft 1.55% airfare 8.06% airline 3.36% airport 0.65% capacity 0.63% cheapest 0.02% city 0.43 …

MessageOnTap: A Suggestive Interface to Facilitate Messaging-related Tasks
F Chen, K Xia, K Dhabalia, JI Hong – … of the 2019 CHI Conference on …, 2019 – dl.acm.org
… of the arrows) are related to functionality offered by another app, indicat- ing an intent to use … across differ- ent messages, and 2) there is ambiguity in user-expressed intents and it … Language API [32] for part-of-speech tagging (noun, verb, etc) and named entity recognition (classi …

Fujitsu’s Approach to Its AI Business and Cutting-Edge Technologies
Y Yamakage, F Maruyama – FUJITSU SCIENTIFIC & TECHNICAL …, 2019 – fujitsu.com
… lead in developing AI applications in 2015, and various ICT vendors declared their intent to enter … the following markets: 1) New user experience (UX) in ICT systems such as chatbots 2) Knowledge … Domain-specific semantic search Named entity extraction (natural text analysis) …

Multi-disciplinary Trends in Artificial Intelligence: 13th International Conference, MIWAI 2019, Kuala Lumpur, Malaysia, November 17–19, 2019, Proceedings
R Chamchong, KW Wong – 2019 – books.google.com
… Hossain, and Zunayeed Bin Zahir Domain-General Versus Domain-Specific Named Entity Recognition: A … Szabó, Péter Földesi, and László T. Kóczy Identification of Conversational Intent Pattern Using Pattern-Growth Technique for Academic Chatbot …

Benchmarking benchmarks: introducing new automatic indicators for benchmarking Spoken Language Understanding corpora
F Béchet, C Raymond – 2019 – hal.archives-ouvertes.fr
… lately a particular atten- tion as one of the crucial component of spoken chatbots and many … previous one but the training set is limited to 70 queries per intent, randomly chosen … not use any pretrained embed- dings or any knowledge base such as named entity dictionnaries since …

I think it might help if we multiply, and not add: Detecting Indirectness in Conversation
P Goel, Y Matsuyama, M Madaio, J Cassell – 9th International Workshop …, 2019 – Springer
… Accurate automated detection of indirectness may help conversational agents better understand their users’ intents, gauge the current relationship with the user in … B, De Neve W, Van de Walle R (2015) Multimedia lab@ acl w-nut ner shared task: named entity recognition for …

Multi-disciplinary Trends in Artificial Intelligence
R Chamchong, KW Wong – Springer
… Hossain, and Zunayeed Bin Zahir Domain-General Versus Domain-Specific Named Entity Recognition: A … Szabó, Péter Földesi, and László T. Kóczy Identification of Conversational Intent Pattern Using Pattern-Growth Technique for Academic Chatbot …

Proceedings of the 11th International Workshop Data analysis methods for software systems
J Bernatavi?ien? – Vilnius University Proceedings, 2019 – zurnalai.vu.lt
Page 1. 11th International Workshop on DATA ANALYSIS METHODS FOR SOFTWARE SYSTEMS Druskininkai, Lithuania, Hotel “Europa Royale” http://www.mii.lt/DAMSS LITHUANIAN COMPUTER SOCIETY VILNIUS UNIVERSITY …

ScratchThat: Supporting Command-Agnostic Speech Repair in Voice-Driven Assistants
J Wu, K Ahuja, R Li, V Chen, J Bigham – Proceedings of the ACM on …, 2019 – dl.acm.org
… and system errors), but it requires that additional “fallback handlers” (ie, error states) be created for each actionable intent in the … 3.2.2 Named Entities. ScratchThat can use a combination of automatic named entity recognition and values from a user-specific entity list to revise …

NLP-based chatbot for HAMK
D Trifunovic – 2019 – theseus.fi
… JSON JavaScript Object Notation KPI Key Performance Indicator LUIS Language Understanding Intelligent Service NER Named Entity Recognition NLP … How can the administrative effort be reduced by the chatbot operation … 2 2 ARTIFICIAL INTELLIGENCE AND CHATBOTS …

Text Summarization
C Room – Architecture, 2019 – devopedia.org
… Event elements are typically named entities (Person, Organisation, Location, Time … production, financial research, patent research, legal contract analysis, tweeting about new content, chatbots that answer … With topic representation, the intent is to identify the main topics in the text …

Learning Multilingual Semantic Parsers for Question Answering over Linked Data. A comparison of neural and probabilistic graphical model architectures
S Hakimov – 2019 – pub.uni-bielefeld.de
… term Memory NED Named Entity Disambiguation NEL Named Entity Linker NER Named Entity Recognizer NLI … Some chatbots use NLU methods to interpret the intent of user messages, which increases … Xiaoice3 is a chatbot developed by Microsoft that engages with users via …

Third International Workshop on Recent Trends in News Information Retrieval (NewsIR’19)
D Albakour, M Martinez, S Tippmann, A Aker… – Proceedings of the …, 2019 – dl.acm.org
… whereas disinformation is false content written with a deliberate intent to mislead … identification and disambiguation • Evaluation of news retrieval systems • Conversational journalism and chat bots … to the CoNLL-2003 shared task: Language-independent named entity recognition …

ParlAmI: a multimodal approach for programming intelligent environments
E Stefanidi, M Foukarakis, D Arampatzis, M Korozi… – Technologies, 2019 – mdpi.com
… In the recent past, chatbots have been utilized as the intelligent mechanism behind disembodied conversational agents (DCAs) and embodied … This work presents ParlAmI [24], a conversational framework featuring a multimodal chatbot that permits users to create “if-then” rules …

A dynamic speaker model for conversational interactions
H Cheng, H Fang, M Ostendorf – Proceedings of the 2019 Conference of …, 2019 – aclweb.org
… First, a speaker’s utterances reflect intents, speaking style, etc … The so- cialbot engages the user in the conversation using a wide range of content indexed by topics, where a topic corresponds to a noun or noun phrase that refers to a named entity (eg, Google) or a concept (eg …

Text analytics with Python: a practitioner’s guide to natural language processing
D Sarkar – 2019 – books.google.com
… 523 Word Sense Disambiguation….. 533 Named Entity Recognition….. 536 Building an NER Tagger from Scratch …

Mobile Medical Question and Answer System with Improved Char-level based Convolution Neural Network and Sparse Auto Encoder
G Yan, J Li – Proceedings of the 2019 Asia Pacific Information …, 2019 – dl.acm.org
… Concepts • Theory of computation?Models of learning •Information systems?Query intent • Information systems … Siri and the emergence of major manufacturers of different chatbots, question-answering … on the features of words, part of speech (POS), named entity and semantics …

Example-Driven Question Answering
D Wang – 2019 – lti.cs.cmu.edu
… 97 C Chatbots Interview: bStarWars vs bTrump vs bHillary … On the one hand, these data sources reflect real user intents and cover a wide variety of knowledge … introduced a wide range of NLP technologies to the question analysis task, in- cluding Named Entity Recognition (NER …

Multi-Document Information Consolidation (Dagstuhl Seminar 19182)
I Daga, I Gurevych, D Roth, A Stent – Dagstuhl Reports, 2019 – drops.dagstuhl.de
… Sebastian Arnold suggested a vector space approach for representing local “hotspots” of selected aspects (eg topics or named entities) coherently over long documents, building on existing sentence embeddings and aligning them with the context of the document using distant …

Linguistic Fundamentals for Natural Language Processing II: 100 Essentials from Semantics and Pragmatics
EM Bender, A Lascarides – Synthesis Lectures on Human …, 2019 – morganclaypool.com
… about how humans use language to express and understand communicative intents … speakers can use sentence meaning to convey communicative intent (pragmatics) … parsing to semantic representations, discourse processing, sentiment analysis, named entity resolution, and …

At the Lower End of Language—Exploring the Vulgar and Obscene Side of German
E Eder, U Krieg-Holz, U Hahn – Proceedings of the Third Workshop on …, 2019 – aclweb.org
… technically slightly more advanced means of camouflage, such as fake Web identities, including non-benevolent software agents and chatbots (McIntire et … tologic “Scheiße” (shit)), ‘Insult’ (clear intent to offend someone) and ‘Abuse’ (an even stronger form of ‘Insult’, ie, an abusive …

Learning Discourse-Level Structures for Question Answering
B Galitsky – Developing Enterprise Chatbots, 2019 – Springer
… The demand for access to different types of information via a chatbot has led … more complex information needs that cannot be answered by simply extracting named entities (persons, organization … actions (either verbs or multi-words implicitly indicating a communicative intent of …

Question answering for suicide risk assessment using reddit
A Alambo, M Gaur, U Lokala… – 2019 IEEE 13th …, 2019 – ieeexplore.ieee.org
… Once suicidal tweets are detected, they performed Named Entity Recognition (NER) using Re- current Neural … are identified as attempt while states related to planning or intent are linked to … and can also be integrated with intelligent conversational agents or chatbots to reduce …

Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language …
K Inui, J Jiang, V Ng, X Wan – Proceedings of the 2019 Conference on …, 2019 – aclweb.org
Page 1. EMNLP-IJCNLP 2019 2019 Conference on Empirical Methods in Natural Language Processing and 9th International Joint Conference on Natural Language Processing Proceedings of the Conference November 3–7, 2019 Hong Kong, China Page 2 …

Folksonomy Based Question Answering System
S Ramaswamy – 2019 – utd-ir.tdl.org
… For coreference resolution, EMLo was able to improve the existing best model’s average F1 score by 3.2%. In the task of Named Entity extraction on Reuters RCV1 corpus, EMLo enhanced biLSTM-CRF achieved an average of 92.22% F1 score over 5 runs. In semantic analysis …

Improving IT Support by Enhancing Incident Management Process with Multi-modal Analysis
A Mandal, S Agarwal, N Malhotra, G Sridhara… – … Conference on Service …, 2019 – Springer
… Our proposed approach is generic enough to be applied to chatbots and QA systems … terms and entities we use a Conditional Random Fields (CRF) based Named Entity Recognition (NER … with information from the ticket enrichment module, understands the user intent and uses …

Toolkits for Building Multimodal Systems and Applications
M Feld, R Ne?selrath – The Handbook of Multimodal-Multisensor …, 2019 – books.google.com
… compo- nent might perform a classification of a textual representation into intents, or do … be implemented (eg, pro-active assistant, question answering system, troubleshooting chatbot, social bot … Modality Fusion describes the process of resolving the semantic intent of a dialogue …

The artificial facilitator: guiding participants in developing causal maps using voice-activated personal assistant
S Reddy, T Reddy – 2019 – knowledgecommons.lakeheadu.ca
… significant differences across systems. Unlike chat-bots, smart conversa … dictionaries requires a great deal of human effort, and many types of named entities often find it difficult to obtain good coverage. The … to the automatic construction of Named Entity Recognition(NER) …

Parsimonious Vole: a Systemic Functional Parser for English
E Costetchi – 2019 – media.suub.uni-bremen.de
… Relevant NLP tasks for gathering market intelligence are named entity recognition (NER), event … attitude, judgement, emotions and intent of the speaker, and co-reference resolution … for extended insights. They deploy chat bots for increased responsiveness by providing …

Improving IT Support by Enhancing Incident Management Process with Multi-modal Analysis
A Ray, D Swarup – … , ICSOC 2019, Toulouse, France, October 28 …, 2019 – books.google.com
… Our proposed approach is generic enough to be applied to chatbots and QA systems … terms and entities we use a Conditional Random Fields (CRF) based Named Entity Recognition (NER … with information from the ticket enrichment module, understands the user intent and uses …

4Software Platforms and Toolkits for Building Multimodal Systems
M Feld, R Neßelrath, T Schwartz – The Handbook of Multimodal-Multisensor … – dl.acm.org
… compo- nent might perform a classification of a textual representation into intents, or do … be implemented (eg, pro-active assistant, question answering system, troubleshooting chatbot, social bot … Modality Fusion describes the process of resolving the semantic intent of a dialogue …

Software platforms and toolkits for building multimodal systems and applications
M Feld, R Ne?elrath, T Schwartz – The Handbook of Multimodal …, 2019 – dl.acm.org
… compo- nent might perform a classification of a textual representation into intents, or do … be implemented (eg, pro-active assistant, question answering system, troubleshooting chatbot, social bot … Modality Fusion describes the process of resolving the semantic intent of a dialogue …

Survey on publicly available sinhala natural language processing tools and research
N de Silva – arXiv preprint arXiv:1906.02358, 2019 – arxiv.org
… Semantic layer attempts to derive the meanings from the word level to the sentence level. Starting with Named Entity Recognition (NER) at the word level and working its way up by identifying the contexts they are set in until arriving at overall meaning …

Duets Ex Machina: On The Performative Aspects of Double Acts in Computational Creativity.
T Veale, P Wicke, T Mildner – ICCC, 2019 – pdfs.semanticscholar.org
… That would require her to re- entrantly jump in and out of her narration intent, at least if she needs to execute other tasks … to a highly-charged plot verb; the GOOD evaluative reaction to an exciting stretch; the NEW character reaction to the introduction of another named entity to a …

AInix: An open platform for natural language interfaces to shell commands
D Gros – 2019 – cs.utexas.edu
… In this, the user’s utterance is first classified into one of many intents … Intent/slotfilling is relatively simple and can be both accurate and scalable with current techniques … even more so than traditional machine translation datasets, never-previously- seen named entity values are …

A Deep Generative Approach to Search Extrapolation and Recommendation
FX Han, D Niu, H Chen, K Lai, Y He, Y Xu – Proceedings of the 25th ACM …, 2019 – dl.acm.org
… CCS CONCEPTS • Information systems ? Query log analysis; Query sugges- tion; Query intent … is that [34] constructs an end-to-end trainable Seq2Seq chatbot that jointly … For search queries, this problem is commonly caused by missing keywords, or unknown Named- Entities …

Towards the Learning, Perception, and Effectiveness of Teachable Conversational Agents
N Chhibber – 2019 – uwspace.uwaterloo.ca
… 11, 34]. Since then, researchers have explored the use of active learning with support vector machines [125], Bayesian networks [124], named entity recognition [102], and natural language processing [103]. However, several …

Text Summarization for Chatbots
M Lustig – 2019 – support.dce.felk.cvut.cz
… the chatbot’s responses but also taking care of the speech recognition and basic intent detection … The transcribed text is analyzed and detected intents and entities govern the next actions … the Switch endpoint can be easily rewritten for any of them making the chatbot transferable …

Structured Knowledge Discovery from Massive Text Corpus
C Zhang – arXiv preprint arXiv:1908.01837, 2019 – arxiv.org
… Figure 1 illustrates three scenarios on community Q&A, voice assistant/chatbot, and service center Q&A … may embody multiple intents … first define an intent graph that bring structures to concept mentions and semantic transitions. Definition 4 (Intent Graph) …

Hotel Review Sentiment Analysis using Natural Language Processing
A Lykesas – 2019 – ikee.lib.auth.gr
… Its true value derives from the use cases, for example information retrieval (google search that finds relevant and similar results), machine translation, speech recognition, text summarization and categorization, chat bots that are able to understand the intent of the conversation …

Deep learning for spoken dialogue systems: application to nutrition
MB Korpusik – 2019 – dspace.mit.edu
… 65 4-2 An illustration of how BERT is used for named entity recognition, or se- mantic tagging in our case (Devlin et al., 2018). . . . 71 … 198 A-5 An example interaction illustrating the importance of intent detection, which …

Cognitive Computing Recipes
A Masood, A Hashmi – Springer
… 5-1. Extract Intent from Audio ….. 227 Problem ….. 227 Solution ….. 227 …

Anemone: a Visual Semantic Graph
J Ficapal Vila – 2019 – diva-portal.org
… As a matter of fact, our intent is to enrich the world’s knowledge in the cause, which … serve to identify, together with some customized method, whether a word is a named entity or not … only those that have a desired length, and then start and end with the respective named entities …

Artificial intelligence for business
R Akerkar – 2019 – Springer
Page 1. SPRINGER BRIEFS IN BUSINESS 123 Rajendra Akerkar Arti cial Intelligence for Business Page 2. SpringerBriefs in Business Page 3. More information about this series at http://www.springer.com/series/8860 Page 4. Rajendra Akerkar Artificial Intelligence for Business …

Standardized representations and markup languages for multimodal interaction
R Tumuluri, D Dahl, F Paternò… – The Handbook of …, 2019 – dl.acm.org
… Amodal (that is, generic modality-independent) system intents created by the IM undergo fission into separate multimodal outputs, which are sent to the … For expressing emotions, the IM can generate a modal intent for the system to express a particular emotion, again sent to the …

Deep learning for drug–drug interaction extraction from the literature: a review
T Zhang, J Leng, Y Liu – Briefings in Bioinformatics, 2019 – academic.oup.com
Page 1. Tianlin Zhang is currently pursuing a masters degree with the School of Computer Science and Technology, University of Chinese Academy of Sciences, China. JiaXu Leng is currently pursuing a PhD degree with the …

IoT Student Advisor and Best Lifestyle Analyzer (ISABELA)
IPA Mota – 2019 – eg.uc.pt
… One of the main objectives was achieved, as the system informs the participant when it detects “bad be- havior”, through messages from the ChatBot. This module, also, served to better understand the platform and learn to work with its components … 16 3.4 ChatBot …

Adaptive and Personalized Systems Based on Semantics
P Lops, C Musto, F Narducci, G Semeraro – Semantics in Adaptive and …, 2019 – Springer
In the introduction of this book, we have thoroughly discussed the importance of adaptive and personalized systems in a broad range of applications. In particular, we have motivated the use of…

A Spell Checking Web Service API for Smart City Communication Platforms
VS Barletta, D Caivano, A Nannavecchia… – Open Journal of Applied …, 2019 – scirp.org
… IBM Watson because of its difficulty in managing fallbacks (for the Italian language), moreover the management of the execution logic through API is cumbersome, the transfer of intents and examples between different applications is not immediate; furthermore, it is a tool with a …

A conceptual modeling approach for the rapid development of chatbots for conversational data exploration
N CASTALDO – 2019 – politesi.polimi.it
… Then, after the dialogue engine is trained ac- cording to this model, the chatbot is able to match the received phrases against these intents while maintaining … Moreover, the developer can specify custom actions which will be called when a specific intent is matched, as well …

Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics
A Korhonen, D Traum, L Màrquez – … of the 57th Annual Meeting of the …, 2019 – aclweb.org
Page 1. ACL 2019 The 57th Annual Meeting of the Association for Computational Linguistics Proceedings of the Conference July 28 – August 2, 2019 Florence, Italy Page 2. Diamond Sponsors: Platinum Sponsors: ii Page 3. Gold sponsors: Keiosk Analytics Silver sponsors …

Enriching a question-answering system with user experience concepts
LV Simons – 2019 – dspace.library.uu.nl
… This is different from question-answering through a chatbot, in which a dialog is … like part-of-speech (POS) tagging, syntactic parsing, semantic relations, named entity extraction, dictionaries … The intent, context, and content components of natural language and the word order are …

Survey on evaluation methods for dialogue
JM Deriu, A Rodrigo, A Otegi, E Guillermo, S Rosset… – 2019 – digitalcollection.zhaw.ch
… 2011]: (i) identification of domain (if multiple domains), (ii) identification of intents (that is the question type, the dialogue act, etc.) and (iii) identification of the slot. In an utterance such as I want to book a hotel room for Monday 8th, the domain is hotel, the intent hotel booking and …

Social Media and Chatbots use for chronic disease patients support: case study from an online community regarding therapeutic use of cannabis
AR Teixeira – 2019 – repositorio-aberto.up.pt
… discussing the therapeutic use of cannabis for chronic diseases? • What contributions can a chatbot offer to improve this dynamic beyond technical limitations … making, online health communities and health related chatbots …

Augmenting MPI Programming Process with Cognitive Computing
P Kazilas – 2019 – diva-portal.org
… The number of named entities of the right type in the passage * The number of question keywords in the passage * The longest exact sequence of question keywords that occurs in the passage * The rank of the document from which the passage was extracted …

Voice assistants and how they affect consumer behavior
A Esmailzadeh, M Rolandsson – 2019 – odr.chalmers.se
… Cover: Image from Chatbots Magazine (2019). See bibliography for URL. Gothenburg, Sweden 2020 Page 5 … published in the 1950’s (Turning, 2009). Chatbots are described as “robots designed to simulate how a human would behave as a conversational partner”, and the …

Unsupervised Text Representation Learning with Interactive Language
H Cheng – 2019 – digital.lib.washington.edu
… different, ie question, declarative or imperative, the illocutionary force of the speaker, mainly the underlying intent, is always the same, ie making a request … Such systems Page 25. 14 (aka chatbots) have been developed for entertainment, companionship and education purpose …

A Systematic Approach for Automatically Answering General-Purpose Objective and Subjective Questions
LP Acharya – 2019 – repository.lib.fit.edu
… between humans and machines. Similar to a chatbot, ELIZA uses pattern matching and … Cognition group at LIMSI-CNRS) uses named entities to answer the factoid questions. Wordnet semantic database was used when the answer type is not a named entity. Page 29. 17 …

BACHELORS THESIS
ME Adam – 2019 – researchgate.net
… Therefore, chatbots need to both, understand emotions and be empathic [FBX+18 … tried to address empathy and emotional intelligence when implementing the later chatbot, as they … As described in section 4.3 Dialogue Strategies & Conversation Flow, the chat- bot developed by …

Commonsense reasoning for natural language understanding: A survey of benchmarks, resources, and approaches
S Storks, Q Gao, JY Chai – arXiv preprint arXiv:1904.01172, 2019 – researchgate.net
… on the type of the missing word to predict, which can be a named entity, common noun … Named entities are identified in the data, and are used to fill the blanks for the cloze … PersonX’s intent: to express anger, to vent their frustration, to get PersonY’s full attention PersonX’s reaction …

Machine Learning from Casual Conversation
A Mohammed Ali – 2019 – stars.library.ucf.edu
… 2.1 Conversational Agents and Chatbots There is a long history of studying conversational agents and chatbots. The earliest known chatbot was ELIZA [132], which was designed to emulate a Rogerian therapist. To provide its responses …

Learning to Memorize in Neural Task-Oriented Dialogue Systems
CS Wu – arXiv preprint arXiv:1905.07687, 2019 – arxiv.org
… logue history, domains, intentions, slots, slot values, states, and external knowledge base (KB). Dialogue history does not mean the whole conversational history between chatbots and users … an intent class from intent candidates …

Implementation and evaluation of a shopping assistance chatbot in an e-commerce case
T Böger – 2019 – run.unl.pt
… NLP forms the frame for pure language processing, NLU describes the actions and intents derived from … Areas like machine translation and concluding the correct intent from an utterance are far from … At first, a definition of the term chatbot is given to then explain different types of …

Natural Language Processing and Chinese Computing: 8th CCF International Conference, NLPCC 2019, Dunhuang, China, October 9–14, 2019 …
J Tang, MY Kan, D Zhao, S Li, H Zan – 2019 – books.google.com
Page 1. Jie Tang· Min-Yen Kan · Dongyan Zhao · Sujian Li· Hongying Zan (Eds.) Natural Language Processing and Chinese Computing 8th CCF International Conference, NLPCC 2019 Dunhuang, China, October 9–14, 2019 Proceedings, Part I 123 Page 2 …

Learning to Converse With Latent Actions
T Zhao – 2019 – lti.cs.cmu.edu
… systems compared to the classic pipeline approach. We define latent actions as the hidden discourse-level intents that the system-side speaker has used in the raw conversational data. Unlike vanilla E2E system that naively …

Decompositional Semantics for Events, Participants, and Scripts in Text
R Rudinger – 2019 – jscholarship.library.jhu.edu
… What’s new? Human: I’ve eaten nothing all day. AI: How did it taste? Figure 1.1: An example of an award-winning chatbot, “Mitsuku,” failing to respond appropriately to a human user. (Inappropriate responses in red italics.) https: //www.pandorabots.com/mitsuku …

Contextual language understanding Thoughts on Machine Learning in Natural Language Processing
B Favre – 2019 – hal-amu.archives-ouvertes.fr
… system has to guess the actual sequence, which often implies understanding the intent of the … The ELIZA chatbot (Weizenbaum 1976) or contestants to the Loeb- ner Prize competition (Stephens … 1. define the task, be it part-of-speech tagging, named entity recognition, machine …

A Multi-Modal Intelligent Agent that Learns from Demonstrations and Natural Language Instructions
TJJ Li – 2019 – pdfs.semanticscholar.org
… An error handling approach for programmable intelligent agents that can help users recover from com- mon errors in various stages of the processing pipeline (ie, speech recognition, intent classification, entity resolution, and task fulfillment) …

Recent advances in natural language inference: A survey of benchmarks, resources, and approaches
S Storks, Q Gao, JY Chai – arXiv preprint arXiv:1904.01172, 2019 – arxiv.org
… Many early efforts focused on collecting large-scale annotations to support data-driven approaches for low-level tasks such as POS tagging (Marcus, Santorini, & Marcinkiewicz, 1993) and named entity recognition (Grishman & Sundheim, 1996) …

Towards Literate Artificial Intelligence
M Sachan – 2019 – ml.cmu.edu
Page 1. Towards Literate Artificial Intelligence Mrinmaya Sachan June 2019 CMU-ML-19-110 Machine Learning Department School of Computer Science Carnegie Mellon University Pittsburgh, PA Thesis Committee Eric P. Xing, Chair Jaime Carbonell Tom Mitchell Dan Roth …

Making Corporations More Humane Through Artificial Intelligence
MR Siebecker – J. Corp. L., 2019 – HeinOnline
… techniques .. .[including] Part-of-Speech tagging, Named Entity Recognition, and Parsing.”). 52. See id. at 13 (“Animals are able to process (visual or other) information from their environment and react adaptively to a changing situation …

Voice wars: smart speakers, voice assistants, and strategies for building a successful voice ecosystem
H Wang – 2019 – dspace.mit.edu
… across many domains in the home Reliability – the degree to which the assistant can perform consistently well for a particular set of tasks (both in the context of ASR and intent) Trust – a measure of the user’s confidence on the reliability of their digital assistant …

Bibliography on Weihrauch complexity
V Brattka, DD Dzhafarov, A Marcone… – Dagstuhl Reports, Vol …, 2019 – drops.dagstuhl.de
Page 23. Vasco Brattka, Damir D. Dzhafarov, Alberto Marcone, and Arno Pauly 21 6 Bibliography on Weihrauch Complexity For an always up-to-date version of this bibliography see http://cca-net. de/publications/ weibib. php …

Editors: Eunika Mercier-Laurent Mieczys?aw L. Owoc Waltraut Ritter
W Ritter, AEF Segrouchni, D Sarne, A Jiang – academia.edu
Page 1. Proceedings 7 th International Workshop on Artificial Intelligence for Knowledge Management (AI4KM 2019) AI for Humans August 11th, 2019, Macao, China Editors: Eunika Mercier-Laurent Mieczys?aw L. Owoc Waltraut Ritter Organizing Committee …

Cognitive architecture of multimodal multidimensional dialogue management
A Malchanau – 2019 – scidok.sulb.uni-saarland.de
… While statistical dialogue systems may perform well on simple information-transfer tasks and end-to-end approaches handle well chatbot conversations, they are mostly unable to manage real-life communication in complex settings like, for example, multi-party conver- sations …

CA5211 C PROGRAMMING AND DATA STRUCTURES LABORATORY LTPC
P PO – DEPARTMENT OF INFORMATION SCIENCE AND … – management.ind.in
Page 38. CA5211 C PROGRAMMING AND DATA STRUCTURES LABORATORY LTPC 0 0 4 2 OBJECTIVES: • To introduce the concepts of structured programming language. • To develop skills in design and implementation of data structures and their applications …

Corpus linguistics for online communication: A guide for research
LC Collins – 2019 – books.google.com
… or corporate names may be trademarks or registered trademarks, and are used only for identification and explanation without intent to infringe … Weizenbaum published details on a program called ELIZA1 (Weizenbaum, 1966) that we might now recognise as a Chatbot and which …

Ontological Traceability using Natural Language Processing
E Rosa Benitez – 2019 – dspace.library.uu.nl
Page 1. Ontological Traceability using Natural Language Processing A master thesis presented by Edder de la Rosa Benitez Submitted to the Department of Organization and Information in partial fulfillment of the requirements for the degree of Master of Science in …