Chatbot Architecture – Meta-Guide.com

Notes:

System architecture is the structure and organization of a system, including the hardware, software, and data components that make up the system and the relationships between them. System architecture is an important aspect of software engineering, as it determines how the different components of the system will interact and work together to achieve the desired goals.

A typical system architecture of chatbots includes the following components:

User interface: This is the component that allows users to interact with the chatbot, typically through a chat window or a voice interface.
Natural language processing (NLP) module: This is the component that processes and analyzes the user’s input, extracting information such as the user’s intent, entities, and sentiments. The NLP module may use techniques such as tokenization, part-of-speech tagging, or named entity recognition to extract information from the user’s input.
Dialogue manager: This is the component that manages the flow of the conversation and selects the appropriate response based on the user’s input and the chatbot’s goals. The dialogue manager may use techniques such as state tracking, decision trees, or rule-based systems to determine the appropriate response.
Knowledge base: This is the component that stores the information that the chatbot has access to, such as a list of frequently asked questions or a database of products or services. The knowledge base may be a structured database or a collection of unstructured documents.
Natural language generation (NLG) module: This is the component that generates the chatbot’s responses, converting the selected response into a form that can be understood by the user. The NLG module may use techniques such as template-based generation or machine translation to generate the response.

Network architecture is the design and organization of a network, including the hardware, software, and protocols that are used to connect devices and transmit data. Network architecture is an important aspect of computer networking, as it determines how devices will communicate and access resources on the network.

A typical network architecture of chatbots includes the following components:

Client devices: These are the devices that users use to interact with the chatbot, such as smartphones, laptops, or tablets.
Network infrastructure: This includes the hardware and software components that are used to connect the client devices to the chatbot server, such as routers, switches, and networking protocols.
Chatbot server: This is the server that hosts the chatbot application and handles requests from the client devices. The chatbot server may be a single machine or a cluster of machines that are used to scale the chatbot to handle a large number of users.
Data storage: This includes the hardware and software components that are used to store the data that the chatbot uses, such as the user’s input, the chatbot’s responses, and any relevant data such as product information or knowledge base articles.

Cognitive architecture is the structure and organization of a system’s cognitive processes, including the mechanisms and strategies that are used to perceive, reason, and act. Cognitive architecture is an important aspect of artificial intelligence and cognitive computing, as it determines how a system will process and analyze information and make decisions.

A typical cognitive architecture of chatbots includes the following components:

Perception: This is the component that processes the raw sensory data that the chatbot receives from the user’s input, such as text or speech. The perception component may use techniques such as tokenization, part-of-speech tagging, or named entity recognition to extract information from the user’s input.
Reasoning: This is the component that analyzes the information that the chatbot has received from the user’s input and makes decisions about how to respond. The reasoning component may use techniques such as rule-based systems, decision trees, or machine learning algorithms to determine the appropriate response.
Action: This is the component that generates the chatbot’s response and sends it back to the user. The action component may use techniques such as template-based generation or machine translation to generate the response.

Neural network architecture refers to the structure and organization of a neural network, including the number and arrangement of the neurons and the connections between them. Neural network architecture is an important aspect of machine learning, as it determines how the neural network processes and analyzes data and makes predictions.

A typical neural network architecture for chatbots includes the following components:

Input layer: This is the layer that receives the raw input data, such as text or speech, and converts it into a form that can be processed by the neural network.
Hidden layers: These are the layers that process the input data and extract features or patterns that are relevant to the task. The number and size of the hidden layers can vary depending on the complexity of the task and the amount of data that the neural network has to process.
Output layer: This is the layer that produces the final prediction or classification based on the processed input data. The output layer may have a single neuron for binary classification tasks, or multiple neurons for multi-class classification tasks

Platform architecture is the structure and organization of a platform, including the hardware, software, and data components that make up the platform and the relationships between them. Platform architecture is an important aspect of software engineering, as it determines how the different components of the platform will interact and work together to provide the desired functionality and services.

A typical platform architecture for chatbots includes the following components:

Hardware infrastructure: This includes the physical components of the platform, such as servers, storage devices, and networking equipment.
Operating system: This is the software that manages the hardware resources of the platform and provides a common interface for other software to access those resources.
Application runtime: This is the software that provides the environment for the chatbot application to run on the platform, including libraries, frameworks, and services.
Chatbot application: This is the software program that implements the chatbot, including the user interface, natural language processing, dialogue management, knowledge base, and natural language generation components.
Data management: This includes the hardware and software components that are used to store and manage the data that the chatbot uses, such as user input, chatbot responses, and any relevant data such as product information or knowledge base articles.

Tier architecture, also known as three-tier architecture or multi-tier architecture, is a software design approach that involves dividing a system into three logical layers: the presentation layer, the application logic layer, and the data storage layer.

A typical tier architecture for chatbots includes the following components:

Presentation layer: This is the layer that handles the interaction with the user, such as displaying the chat window or processing the user’s input.
Application logic layer: This is the layer that contains the core functionality of the chatbot, such as natural language processing, dialogue management, and knowledge base management.
Data storage layer: This is the layer that handles the storage and retrieval of data, such as user input, chatbot responses, and any relevant data such as product information or knowledge base articles.

Security architecture is the structure and organization of a system’s security measures, including the policies, controls, and technologies that are used to protect the system and its data from unauthorized access, use, or disclosure. Security architecture is an important aspect of software engineering, as it determines how the system will protect itself and its data from potential security threats.

A typical security architecture for chatbots includes the following components:

Access controls: These are the policies and controls that are used to manage and restrict access to the chatbot and its data. Access controls may include authentication methods, such as passwords or biometric authentication, and authorization policies, which determine which users or groups are allowed to access which resources.
Encryption: This is the process of encoding data in such a way that it can only be accessed by authorized users with the appropriate decryption key. Encryption is used to protect data in transit and at rest, to ensure that it cannot be accessed by unauthorized parties.
Security monitoring: This is the process of monitoring the chatbot and its data for security threats, such as attempted attacks or unauthorized access. Security monitoring may include techniques such as log analysis, intrusion detection, and vulnerability scanning.
Risk management: This is the process of identifying, assessing, and mitigating potential security risks to the chatbot and its data. Risk management may involve implementing controls to prevent or minimize the impact of potential risks, or creating contingency plans to deal with the consequences of a security breach.

BDI (Belief-Desire-Intention) architecture is a type of cognitive architecture that is used to model the decision-making and reasoning capabilities of intelligent agents, such as chatbots. BDI architecture is based on the idea that intelligent agents have beliefs, desires, and intentions that drive their behavior.

A typical BDI architecture for chatbots includes the following components:

Beliefs: These are the agent’s beliefs about the state of the world and the information that it has access to. Beliefs may include things like the user’s name, the current time, or the location of the chatbot.
Desires: These are the agent’s goals or objectives, which drive its behavior. Desires may include things like completing a task, answering a question, or providing a service to the user.
Intentions: These are the agent’s plans or actions that are intended to achieve its desires. Intentions may include things like asking the user a question, providing information to the user, or taking a specific action.
Reasoning engine: This is the component that processes the agent’s beliefs, desires, and intentions and selects the appropriate action to take. The reasoning engine may use techniques such as rule-based systems, decision trees, or probabilistic models to make decisions.

Pipeline architecture is a software design approach that involves dividing a system into a series of stages or steps, each of which performs a specific task or function. Pipeline architectures are often used in systems that process large amounts of data or perform complex tasks, as they allow developers to break the task down into smaller, more manageable components.

A typical pipeline architecture for chatbots might include the following components:

Input processing: This is the stage that processes the raw input data, such as text or speech, and converts it into a form that can be processed by the chatbot. Input processing may include tasks such as tokenization, part-of-speech tagging, or named entity recognition.
Natural language processing (NLP): This is the stage that analyzes the input data and extracts information such as the user’s intent, entities, and sentiments. NLP may involve techniques such as dependency parsing, sentiment analysis, or topic modeling.
Dialogue management: This is the stage that manages the flow of the conversation and selects the appropriate response based on the user’s input and the chatbot’s goals. Dialogue management may use techniques such as state tracking, decision trees, or rule-based systems to determine the appropriate response.
Response generation: This is the stage that generates the chatbot’s response, converting the selected response into a form that can be understood by the user. Response generation may use techniques such as template-based generation or machine translation to generate the response.

Memory architecture is the structure and organization of a system’s memory, which is the component that stores data and instructions that are used by the system. Memory architecture is an important aspect of software engineering, as it determines how the system will access and use its memory resources.

A typical memory architecture for chatbots might include the following components:

Main memory: This is the primary memory that is used by the chatbot to store data and instructions that are currently being used or accessed. Main memory is typically divided into smaller units called memory cells or memory locations, which can be accessed individually or in groups.
Cache memory: This is a type of high-speed memory that is used to store frequently accessed data and instructions. Cache memory is typically much smaller than main memory, but it is much faster, which allows the chatbot to access data and instructions more quickly.
Virtual memory: This is a type of memory that allows the chatbot to use more memory than is physically available by temporarily storing data and instructions on disk. Virtual memory allows the chatbot to run larger programs or handle larger datasets than would be possible with the physical memory alone.

LSTM (Long Short-Term Memory) architecture is a type of recurrent neural network (RNN) architecture that is used to process sequential data, such as text or speech. LSTM architecture is particularly useful for tasks such as natural language processing (NLP), as it is able to learn long-term dependencies in the data and can handle variable-length sequences.

A typical LSTM architecture for chatbots includes the following components:

Input layer: This is the layer that receives the raw input data, such as text or speech, and converts it into a form that can be processed by the neural network.
LSTM layers: These are the layers that process the input data and extract features or patterns that are relevant to the task. LSTM layers consist of LSTM cells, which are able to remember and learn from past input data and can handle variable-length sequences. The number and size of the LSTM layers can vary depending on the complexity of the task and the amount of data that the neural network has to process.
Output layer: This is the layer that produces the final prediction or classification based on the processed input data. The output layer may have a single neuron for binary classification tasks, or multiple neurons for multi-class classification tasks.

CNN (Convolutional Neural Network) architecture is a type of neural network architecture that is particularly well-suited to processing and analyzing data that has a grid-like structure, such as images or text. CNN architecture is based on the idea of convolutional layers, which are able to learn local patterns and features in the data by applying a set of filters or kernels to the input data.

A typical CNN architecture for chatbots might include the following components:

Input layer: This is the layer that receives the raw input data, such as images or text, and converts it into a form that can be processed by the neural network.
Convolutional layers: These are the layers that apply a set of filters or kernels to the input data, extracting local patterns and features that are relevant to the task. The number and size of the convolutional layers can vary depending on the complexity of the task and the amount of data that the neural network has to process.
Pooling layers: These are the layers that downsample the output of the convolutional layers, reducing the size and dimensionality of the data while preserving the important features and patterns. Pooling layers are typically used to reduce the computational complexity of the network and to improve its generalization ability.
Fully-connected layers: These are the layers that perform the final classification or prediction based on the processed input data. The fully-connected layers typically have a large number of neurons and are connected to all the neurons in the previous layer, allowing them to process the entire input data and make a prediction.

This is a list of terms associated with chatbot architecture ranked in descending order based on the number of academic papers in Google Scholar results (March 2018).

System architecture (708)
Network architecture (491)
Software architecture (341)
Cognitive architecture (164)
General architecture (155)
Neural network architecture (122)
Modular architecture (106)
Platform architecture (61)
Deep learning architecture (60)
Systems architecture (59)
Tier architecture (59)
Hybrid architecture (56)
Security architecture (53)
BDI architecture (47)
Pipeline architecture (37)
Memory architecture (35)
Generic architecture (34)
LSTM architecture (33)
Convolutional neural network architecture / CNN architecture (32)
Data architecture (32)
Master-slave architecture (28)
Traditional architecture (28)
Unified architecture (28)
Parallel architecture (27)
ALICE architecture (26)
Game architecture (25)
Serverless architecture (25)
Social architecture (12)
Connectionist architecture (10)
Emotion architecture (10)
Object-oriented architecture (10)
Recurrent architecture (10)
Emotional architecture (8)
REST architecture (8)
Schematic architecture (6)
Infrastructure architecture (5)
Access architecture (4)
ACT-R architecture (4)
Algorithmic architecture (3)
Knowledge-base architecture (3)
Adaptable architecture (2)
Generator architecture (2)
HRED architecture (2)
SOA architecture (2)
Constrained architecture (1)
EBDM architecture (1)
Higher-order architecture (1)
Text architecture (1)

Wikipedia:

References:

Automatic Extraction of Chatbot Training Data from Natural Dialogue Corpora
B AbuShawar, E Atwell – RE-WOCHAT: Workshop on Collecting … – pdfs.semanticscholar.org
… Since that time, a range of new chatbot architectures have been developed, such as: MegaHAL (Hutchens, 1996), CONVERSE (Batacharia et al … In this paper, ALICE/AIML chatbot architecture and the pattern matching techniques used within it are presented in section 2. Section …

Evaluating natural language understanding services for conversational question answering systems
D Braun, A Hernandez-Mendez, F Matthes… – Proceedings of the 18th …, 2017 – aclweb.org
… While there exist different documented chatbot architectures for concrete use cases, no universal model of how a chatbot should be designed has emerged yet. Our proposal for a universal chatbot architecture is shown in Figure 1. It consists of three main parts: Request Inter …

Addressing challenges in promoting healthy lifestyles: the al-chatbot approach
A Fadhil, S Gabrielli – Proceedings of the 11th EAI International …, 2017 – dl.acm.org
… way. 2. AI-CHATBOT ARCHITECTURE FOR HEALTHY LIFESTYLE PROMOTION Current research shows that most chatbot systems are used to access information or communicate simple instructions to the audience. A few …

From chatbots to dialog systems
T Klüwer – International Journal, 2011 – books.google.com
… basis for dialog functionality. The stimulus-response algorithm is the core of the chatbot architecture. It determinesthereaction to a user input via a database containing a fixed set of pattern-template pairs. The pattern can be …

Chatbots are natural web interface to information portals
BA Shawar – Proc. of INFOS 2008 The Sixth International …, 2008 – pdfs.semanticscholar.org
… ALICE/AIML chatbot architecture and how the chatbot was trained by dialogue corpora then turned to be trained with FAQ domain are presented in section 2. Section 3 describes how the program was adapted to deal with WWWFAQs and the problems we faced …

Challenges facing the development of the Arabic chatbot
ES AlHagbani, MB Khan – First International Workshop on …, 2016 – spiedigitallibrary.org
… In Chakrabarti and Luger (2012) 4 study, they describe the chatbot architecture and process in three main components as shown in Figure 1. Firstly, The Chat Interface which is the first module that interact with the user … Figure 1. Chat Bot Architecture …

Comparative study of cloud platforms to develop a Chatbot
A Patil, K Marimuthu, R Niranchana – International Journal of …, 2017 – sciencepubco.com
… We need to analyze user input message, and the bot response as well[13]. Figure 2 Shows the general chatbot architecture … Next im-portant module in chatbot architecture is response generator. It uses some external APIs and algorithm to generate the response …

EHeBby: An evocative humorist chat-bot
G Pilato, A Augello, G Vassallo, S Gaglio – Mobile Information Systems, 2008 – hindawi.com
… The work is an evolution of the architecture illustrated in [16]. In particular, we propose an enhanced chat-bot architecture, named EHeBby, with both rational and associative capabilities … EHeBby: An evocative humorist chat-bot 169 Fig. 2. The evocative chat-bot architecture …

NCI Hub: Technical Report
E Coleman – 2017 – trap.ncirl.ie
… Page 17. NCI Hub Page 9 2.2.1 Typical Chat Bot Architecture Simple Chatbot Architecture Figure 6: Simple Chat Bot Architecture This use case illustrates a simple chat bot that is only connected to a natural language interface in this case API.ai …

Using learning analytics to understand the design of an intelligent language tutor–Chatbot lucy
YF Wang, S Petrina – Editorial Preface, 2013 – Citeseer
… Chatbot architecture integrates a language model and computational algorithms to emulate informal chat communication between a human user and a … and natural-language interface research in the late 80s encouraged the creation of many new chatbot architectures such as …

A semantic layer on semi-structured data sources for intuitive chatbots
A Augello, G Pilato, G Vassallo… – Complex, Intelligent and …, 2009 – ieeexplore.ieee.org
… In the remainder of the paper the chat-bot architecture, divided into the afore- mentioned reasoning areas is presented. Some examples of AIML categories and a dialogue interaction are reported. Finally, conclusions are given. 2 Semantic Wikipedia … 3 Chatbot Architecture …

Impact of agent’s answers variability on its believability and human-likeness and consequent chatbot improvements
M Xuetao, F Bouchet, JP Sansonnet – Proc. of AISB, 2009 – fbouchet.vorty.net
… 1. Technical feasability: is it possible to handle variability with a chatbot architecture? 2. Need: do people notice variability … Conclusion • Possibility to handle variability with a chatbot architecture • Users notice variability in agents • Agents with variability are perceived as …

Enhancement Algorithms for SQL-Based Chatbot
AS Lokman, JM Zain – … on Software Engineering and Computer Systems, 2011 – Springer
… In an as- pect of managing knowledge-based data (some call it as the chatbots brain), an evolvement in chatbots architecture can be … chatbot named ViDi (acronyms for Virtual Diabetes physician) [5], two components need to be in- corporated into chatbot architecture in order to …

Deploying embodied AI into virtual worlds
DJH Burden – Knowledge-Based Systems, 2009 – Elsevier
… Download full-size image. Fig. 1. Embodied Chatbot Architecture for Second Life. In order to better isolate the bot functions from the virtual world we have been seeking to identify XML specifications which can be implemented by the avatar interface. What we have in mind are: • …

Designing a Teachable Agent with Social Intelligence
A Silvervarg, A Gulz, M Haake, B Sjöden… – … Virtual Agents, 2010, 2010 – researchgate.net
… Rather than designing a complex and knowledge intense architecture we aim at reaching our goal of a socially intelligent conversational agent through simple means and techniques, for example the conversational module is based on chatbot architecture …

Effects of cognitive styles on an MSN virtual learning companion system as an adjunct to classroom instructions
SW Hsieh – Journal of Educational Technology & Society, 2011 – JSTOR
… The aim of a chatbot system is to simulate a human conversation; the chatbot architecture integrates a language model and computational … Since that time, a range of new chatbot architectures have been developed, such as CONVERSE (Batacharia et al., 1999), ELIZABETH …

Chatbots as interface to ontologies
A Augello, G Pilato, G Vassallo, S Gaglio – Advances onto the Internet of …, 2014 – Springer
… In last years we have proposed hybrid chatbot architectures combining symbolic and sub-symbolic methodologies for knowledge representation and reasoning, simulating rational and intuitive … 4 Integration of CyD and LSAbot: A Rational/Intuitive Chatbot Architecture …

The Department Store Metaphor: Organizing, Presenting and Accessing Cultural Heritage Components in a Complex Framework.
U Maniscalco, G Mascari, G Pilato – WIRN, 2009 – books.google.com
… 2. The Chat-bot Architecture In order to simulate the department store employee we propose to apply an intuitive chatbot architecture [4]. This kind of chat-bot is characterized by two typical behaviors: the first one is rational, and is given by the utilization of the taxonomies, the …

I-ChatbIT: an Intelligent Chatbot for the Italian Language
A Pipitone, V Cannella, R Pirrone – … of the First Italian Conference on …, 2014 – fileli.unipi.it
… Abstract English. A novel chatbot architecture for the Italian language is presented that is aimed at implementing cognitive under- standing of the query by locating its cor- respondent subgraph in the agent’s KB by means of a graph matching strategy pur- posely devised …

Designing Service-Oriented Chatbot Systems Using a Construction Grammar-Driven Natural Language Generation System
MC Jenkins – 2011 – ueaeprints.uea.ac.uk
… 4 2 Chatbot architectures 5 2.1 Introduction … 4 Page 20. Chapter 2 Chatbot architectures 2.1 Introduction In this chapter we investigate previous work undertaken in building SOCS and other types of conversational system …

Building a chatbot with serverless computing
M Yan, P Castro, P Cheng, V Ishakian – … on Mashups of Things and APIs, 2016 – dl.acm.org
… Figure 2. Chatbot Architecture Page 3. The third level of processing is for domain specific chatbot “abilities.” Each ability has to do at least two things … Our focus was on creating an extensible chatbot architecture using serverless and this we did not optimize for performance …

Implementation of an inquisitive chatbot for database supported knowledge bases
S Reshmi, K Balakrishnan – S?dhan?, 2016 – Springer
… 2 Chatbot architecture. Chatbot analyzes the user input and gives a suitable response using natural language processing (NLP) and artificial intelligence … Open image in new window. Figure 1 Chatbot architecture. 3 Existing chatbots …

A model of a social chatbot
A Augello, M Gentile, L Weideveld… – … Multimedia Systems and …, 2016 – Springer
… 3 Toward a Social Chatbot Architecture. The architecture of the social chatbot is shown in Fig. 1 and it is composed of three main modules named Social Practice Selection, Identity and Deliberation Engine … 1 Social chatbot architecture. 3.1 A Case Study …

Chatbot Design-Reasoning about design options using i* and process architecture
Z Babar, A Lapouchnian, E Yu – 2011 – cs.toronto.edu
… A report from The Economist Intelligence Unit (2009) 3. Surmenok, P.: Chatbot Architecture, March 10, 2017, http://pavel.surmenok.com/2016/09/11/chatbot-architecture/ 4. Augello, A., Gentile, M., Weideveld, L., Dignum, F.: A model of a social chatbot …

Talking Open Data
S Neumaier, V Savenkov, S Vakulenko – European Semantic Web …, 2017 – Springer
… the individual data items from them. In the future work we plan to extend the chatbot to search within the content of the datasets rather than merely in the metadata. 2 Chatbot Architecture. We implemented a prototype as a proof …

Real conversations with artificial intelligence: A comparison between human–human online conversations and human–chatbot conversations
J Hill, WR Ford, IG Farreras – Computers in Human Behavior, 2015 – Elsevier
… A variety of new chatbot architectures and technologies (eg, Ultra Hal, ALICE, Jabberwacky, Cleverbot) have arisen recently, each attempting to simulate natural human language more accurately and thoroughly (Carpenter, nd a; Shawar & Atwell, 2007; Wallace, Tomabechi, & …

Virtual social networks online and mobile systems
M Safar, H Sawwan, M Taha, T Al-Fadhli – Mobile Information Systems, 2009 – hindawi.com
… All rights reserved Page 2. 234 M. Safar et al. / Virtual social networks Similar mobile applications relevant to the context of social networks were developed in [10,19]. The work in [19] presents an enhanced chat-bot architecture (EHeBby) …

Patient’s Chatting Mechanism Serious Game for Internal Medicine Practice
L SIEW – 2013 – core.ac.uk
… 10 4.2 Patient-Doctor Recorded Conversation 12-13 4.3 Chatbot Architecture Design Model 14 … 2006). When chatbot technology evolves, in an aspect of managing knowledge-based data (chatbot?s brain), an evolvement in chatbots architecture can be justified. The …

Chatbots for troubleshooting: A survey
C Thorne – Language and Linguistics Compass, 2017 – Wiley Online Library
… 3.1 Chatbot architecture … We have outlined the key properties of troubleshooting dialogs, of troubleshooting chatbot architectures, reviewed a number of recent troubleshooting chatbots described in dialog system literature, and discussed the main evaluation strategies currently …

Analysis of temporal evolution of social networks
M SAFAR, H FARAHAT – Journal of Mobile Multimedia, 2009 – researchgate.net
… For example, the work in [1] presents an enhanced chat-bot architecture (EHeBby) in which a humoristic conversational agent is capable to generate, propose, tell and answer to the user: humoristic expressions, riddles, and jokes …

A modular system oriented to the design of versatile knowledge bases for chatbots
G Pilato, A Augello, S Gaglio – ISRN Artificial Intelligence, 2012 – downloads.hindawi.com
… The proposed solution tries to overcome the main limits of pattern-matching-based chatbot architectures, which are based on a rigid knowledge base, time consuming to establish and maintain, and a limited dialogue engine which does not take into account the semantic content …

An AI framework to teach English as a foreign language: CSIEC
J Jia – AI Magazine, 2009 – aaai.org
… Brennan (2006) defined a chatbot as “an artificial construct that is designed to converse with human beings using natural language as input and out- put.” A chatbot architecture integrates a language model and computational algorithms to emulate communication between a …

A Chatbot as a natural web Interface to Arabic web QA
BA Shawar – International Journal of Emerging Technologies in …, 2011 – online-journals.org
… Results and conclusion are discussed in sections VI and VII consecu- tively. II. ALICE/AIML CHATBOT ARCHITECTURE We have worked with the ALICE open-source chatbot initiative. ALICE5 is the Artificial Linguistic Internet Computer Entity, originated by Wallace in 1995 …

Case Study: Building a Serverless Messenger Chatbot
J Lehvä, N Mäkitalo, T Mikkonen – International Conference on Web …, 2017 – Springer
… 5 Towards Serverless Chatbot Architecture. The main motivation for serverless computing approach is that the developer doesn’t need to manage servers … Architecture of the Chatbot has been depicted in Fig. 2. The user sends a message using the Messenger application …

Usefulness, localizability, humanness, and language-benefit: additional evaluation criteria for natural language dialogue systems
B AbuShawar, E Atwell – International Journal of Speech Technology, 2016 – Springer
… We used the ALICE/AIML chatbot architecture as a platform to develop a range of chatbots covering different languages, genres, text-types, and user-groups, to illustrate qualitative aspects of natural language dialogue system evaluation … 2 The ALICE/AIML chatbot architecture …

Toward the implementation of a topic specific dialogue based natural language chatbot as an undergraduate advisor
S Ghose, JJ Barua – Informatics, Electronics & Vision (ICIEV) …, 2013 – ieeexplore.ieee.org
… The purpose of a chatbot system is to simulate a human conversation; the chatbot architecture integrates a language model and computational algorithm to emulate information chat communication between a human user and a computer using natural language …

RMRSBot–using linguistic information to enrich a chatbot
T Klüwer – International Workshop on Intelligent Virtual Agents, 2009 – Springer
… results from a semantic analysis. 2 System In the presented system the Heart of Gold (HoG) [3] a middleware for vari- ous linguistic components was integrated into a chatbot architecture. The HoG delivers results from different …

An Intelligent Web-Based Human-Computer Interaction System with Natural Language CSIEC and its Integration into English Instruction
J Jia – Learning Culture and Language through ICTs …, 2009 – books.google.com
… A chatbot architecture integrates a language model and computational algorithms to emulate communication between a human user and a computer using natural language (Abu Shawar and Atwell, 2007). ELIZA (Weizenbaum, 1966) was the first chat- bot …

Intelligent Chat Bot for Banking System
A Dole, H Sansare, MR Harekar… – … Journal of Emerging …, 2015 – pdfs.semanticscholar.org
… The purpose of a chat bot system is to simulate a human conversation; the chat bot architecture integrates a language model and computational algorithm to emulate information chat communication between a human user and a computer using natural language …

Arabic question-answering via instance based learning from an FAQ corpus
BA Shawar, E Atwell – Proceedings of the CL 2009 International …, 2009 – academia.edu
… Results and conclusions are discussed in sections 6 and 7 consecutively. 2. ALICE/AIML chatbot architecture We have worked with the ALICE open-source chatbot initiative. ALICE1 is the Artificial Linguistic Internet Computer Entity, originated by Wallace in 1995 …

Sub-Symbolic knowledge representation for evocative chat-bots
G Pilato, A Augello, G Vassallo, S Gaglio – Interdisciplinary Aspects of …, 2008 – Springer
… S3 S3 S2 S2 S1 S1 Fig. 1 The evocative Chat-bot architecture synsets. The relations are characterized by a hierarchical structure. In fact a hyper- nymy relation connects each synset with his higher synset. A synset s1 is hypernym of the synset s2 if s1 conceptually includes s2 …

A novel approach for medical assistance using trained chatbot
D Madhu, CJN Jain, E Sebastain… – Inventive …, 2017 – ieeexplore.ieee.org
… The purpose of a Chatbot system is to simulate a human conversation; the Chatbot architecture integrates a language model and computational algorithms [7] to emulate informal chat communication between a human user and a Computer using natural language …

An Intelligent Career Counselling Bot A System for counselling
A Parab, S Palkar, S Maurya, S Balpande – 2017 – irjet.net
… The purpose of a chat bot system is to simulate a human conversation; the chat bot architecture integrates a computational algorithm and language model to emulate information chat communication between a human user and a computer using natural language …

Arabic question-answering via instance based learning from an FAQ corpus
B Abu Shawar, ES Atwell – Proceedings of the CL2009 …, 2009 – eprints.whiterose.ac.uk
… Results and conclusions are discussed in sections 6 and 7 consecutively. 2. ALICE/AIML chatbot architecture We have worked with the ALICE open-source chatbot initiative. ALICE1 is the Artificial Linguistic Internet Computer Entity, originated by Wallace in 1995 …

Emotionally responsive robotic avatars as characters in virtual worlds
S Slater, D Burden – Games and Virtual Worlds for Serious …, 2009 – ieeexplore.ieee.org
… their own agent AI systems. In this work, the E-AI architecture was applied to a currently existing commercial AI and chatbot architecture. Keywords – Virtual Worlds, Emotion Modeling, AI I. INTRODUCTION Whether the user …

AIML knowledge base construction from text corpora
G De Gasperis, I Chiari, N Florio – Artificial intelligence, evolutionary …, 2013 – Springer
… (1988). A rebirth of research on chatbot architecture has begun since the ’80s (Shawar and Atwell 2007a) … 2 Corpus Based Chatbots and Linguistic Issues In the last few years a number of tools have been developed combining the chatbot architecture with corpora …

Chatbots as a Novel Access Method for Government Open Data?
S Porreca, F Leotta, M Mecella, T Catarci – ceur-ws.org
… There are numerous approaches and methodologies proposed for this; in this work, we followed the approach that divides the chatbot architecture in three parts: responder, classifier and graph- master [1]. The responder is the interface by which users access the system …

This work can be found from: https://doi. org/10.1007/978-3-319-74433-9_6 To cite this work, use
C In, I Garrigós, M Wimmer – 2018 – researchgate.net
… It’s easy to set up and Amazon provides web interface to browse the tables in the database. 5 Towards Serverless Chatbot Architecture … The designed chatbot architecture turned out to be extensible and scalable, requiring close to zero management and even to be cost efficient …

ANALYSIS OF THE CHATBOT OPEN SOURCE LANGUAGES AIML AND CHATSCRIPT: A Review
S Arsovski, AD Cheok, M Idris, MRBA Raffur – researchgate.net
… Authors [3] agreed that the best way to facilitate Human Computer Interaction (HCI) is by allowing users “to express their interest, wishes, or queries directly and naturally, by speaking, typing, and pointing”. Numerous chat-bot architectures have been developed since then …

A personal intelligent coach for smart embodied learning environments
A Augello, I Infantino, A Manfré, G Pilato, F Vella… – … Multimedia Systems and …, 2016 – Springer
… conversational agent. Traditional chatbot architectures can be improved by considering semantic analysis and reasoning methodologies in order to make the chatbot answers as coherent as possible with the requests of the user. The …

Accessing Government Open Data Through Chatbots
S Porreca, F Leotta, M Mecella, S Vassos… – … Conference on Web …, 2017 – Springer
… There are numerous approaches and methodologies proposed for this; in this work, we followed the approach that divides the chatbot architecture in three parts: responder, classifier and graphmaster [1]. The responder is the interface by which users access the system …

In the shades of the uncanny valley: An experimental study of human–chatbot interaction
L Ciechanowski, A Przegalinska, M Magnuski… – Future Generation …, 2018 – Elsevier
… interface research [15]. Since that time, a range of new chatbot architectures have been developed, such as MegaHAL [16], CONVERSE [17], and ALICE [18], which was first implemented by Wallace in 1995. ALICE’s knowledge …

Comedy, Creativity, Agency: The Hybrid Individual
M Meany – The Creative System in Action, 2016 – Springer
… The chat-bot then pro- cesses that input to create an appropriate response. Atomic and Romeo were built on the Artificial Linguistic Internet Computer Entity or ALICE (ALICE AI Foundation 2011) chat-bot architecture developed by Dr Richard Wallace …

Effects of individual difference variables on a virtual companion system as an adjunct to an economics course
SW Hsieh, CC Lee, MC Hsieh – 2012 – irbis-nbuv.gov.ua
… and Wilensky et al. (1988). Since then, several new chatbot architectures have been developed, such as, ELIZABETH (Abu Shawar & Atwell, 2002), Jabberwacky (Fryer & Carpenter, 2006) and ALICE (2010). As chat bot design …

Managing Conversation Uncertainty in TutorJ.
V Cannella, R Pirrone – AAAI Fall Symposium: Cognitive and Metacognitive …, 2009 – aaai.org
… agents. Then the extensions to the conventional chatbot architecture, and the new AIML tags for integration of Bayesian networks will be presented … reasoning. The new chatbot architecture is general, and can be used apart from TutorJ …

“C? Mon dude!”: Users adapt their behaviour to a robotic agent with an attention model
L Cavedon, C Kroos, D Herath, D Burnham… – International Journal of …, 2015 – Elsevier
… In the simple configuration used here, speech recognition and speech-synthesis—using off-the-shelf components (eg, Dragon Naturally Speaking)—facilitate basic spoken interaction; dialogue management is implemented by a chatbot architecture enhanced with task-specific …

A corpus-based NLP-chain for a web-based Assisting Conversational Agent
M Xuetao, JP Sansonnet, F Bouchet – Third Workshop on …, 2008 – researchgate.net
… on pattern matching rules. Typical chatbot architectures are organized in two simple layers/phases: 1) The chunking phase: the textual utterance is trimmed from punctuation, accentuated characters, etc. and coerced into uppercase …

Augmented Reality in Academia-Changing Landscape of Education
D Sharma, A Bhatia, S Chethan – Journal of Engineering and Applied …, 2017 – docsdrive.com
… Any text to speech API can be used like ones provided by IBM Cyre Stored Response « | | eee Input kkLLLL kkk kkSkkk S – – | | Tables Spellcheck||Keyboard|| Palem || Log | Fig. 2: Chat bot architecture Watson and Amazon Polly …

Chatbot Enhanced Algorithms: A Case Study on Implementation in Bahasa Malaysia Human Language
AS Lokman, JM Zain – International Conference on Networked Digital …, 2010 – Springer
… In this paper, we propose an enhanced algorithm of a chatbot by taking advantages of re- lational database model to design the whole chatbot architecture that enable several features that cannot or difficult to be done in previous state of computer science programming …

A Conversational Chatbot Based on Kowledge-Graphs for Factoid Medical Questions
A Minutoloa, M Espositoa… – New Trends in Intelligent …, 2017 – books.google.com
… entities in the graph. 3. The chatbot architecture The main components of the proposed conversational chatbot are shown in Figure 1. Figure 1. The main components of the proposed conversational chatbot. The Knowledge Graph …

Contextualizing Customer Complaints by Identifying Latent Beliefs and Tailoring a Chatbot’s Dialog through Epistemic Reasoning
C Anantaram, A Sangroya – mrc.kriwi.de
… for example latent beliefs such as “customer(harrassed)”. Such an abstraction facili- tates focus on the hidden states that are not explicitly pro- cessed in various chatbot architectures. Additionally, one of the advantages of our …

A Survey of Design Techniques for Conversational Agents
K Ramesh, S Ravishankaran, A Joshi… – International Conference …, 2017 – Springer
… arXiv preprint arXiv:1607.00970 (2016). 22. Pavel, S.: Chatbot Architecture (2016). http://pavel.surmenok.com/2016/09/11/chatbot-architecture/. 23. Denny, B.: Deep Learning for Chatbots (2016). http://www.wildml.com/2016/04/deep-learning-for-chatbots-part-1-introduction …

A Survey of Design Techniques for Conversational Agents
K Chandrasekaran – … Conference, ICICCT 2017, New Delhi, India …, 2017 – books.google.com
… conversation. arXiv preprint arXiv: 1607.00970 (2016) Pavel, S.: Chatbot Architecture (2016). http://pavel. surmenok. com/2016/09/11/chatbot- architecture/ Denny, B.: Deep Learning for Chatbots (2016). http://www. wildml. com …

Towards a game-chatbot: extending the interaction in serious games
P Van Rosmalen, J Eikelboom… – … on Games Based …, 2012 – search.proquest.com
… 2. Parsing (AIML level). The chatbot will try to recognize sentences. 3. Semantic level. Chatbot can use semantical structures for reply generation or improved handling of multiple abstraction levels. Level 3 is an extension to a typical chatbot architecture, and part of our research …

Introducing a creative process on a cognitive architecture
A Augello, I Infantino, G Pilato, R Rizzo… – Biologically Inspired …, 2013 – Elsevier
… threshold. On the other hand, our humanoid tries to catch emotions that characterize the user through a dialogue. The dialogue mechanism has been realized by using a chatbot architecture based on ALICE framework. 3 The …

A new friend in our smartphone?: observing interactions with chatbots in the search of emotional engagement
M Portela, C Granell-Canut – … of the XVIII International Conference on …, 2017 – dl.acm.org
Page 1. A new friend in our Smartphone? Observing Interactions with Chatbots in the search of emotional engagement Manuel Portela Universitat Jaume I Av. Sos Baynat, S/N Castellón de la Plana, Spain 12007 portela@uji.es Carlos Granell-Canut Universitat Jaume I Av …

An overview of open-source chatbots social skills
A Augello, M Gentile, F Dignum – researchgate.net
… the social practice. In our opinion, the integration of the social practice model in the chatbot architecture, could enhance a simple chatbot with social skills, obtaining as consequence, more realistic conversations. To adopt this …

Building Kurdish Chatbot Using Free Open Source Platforms
KM Kaka-Khan – UHD Journal of Science and Technology, 2017 – journals.uhd.edu.iq
… 862-868, Jun. 2017. [15] J. Cahn. “CHATBOT: Architecture, design, and development.” University of Pennsylvania School of Engineering and Applied Science Department of Computer and Information Science, Apr. 26, 2017.

Complex Intelligent Information/Services Networks: a case study from Cultural Heritage
GF Mascari, U Maniscalco, L Moltedo, P Moscati… – infomus.org
… In order to simulate the department store employee we propose to apply an intuitive chatbot architecture [9]. This kind of chatbot is characterized by two typical behaviors: the first one is rational, and is given by the utilization of the taxonomies, the ontology and the standard AIML …

Creativity evaluation in a cognitive architecture
A Augello, I Infantino, G Pilato, R Rizzo… – Biologically Inspired …, 2015 – Elsevier
… 6) (Augello et al., 2007; Coursey, 2004), and of a lexicon used for the subjectivity analysis (Riloff & Wiebe, 2003). Fig. 6 shows the chatbot architecture. Download full-size image. Fig. 6. Architecture of the dialogue module used for the external evaluation …

I Can Parse You: Grammars for Dialogs
M Hirzel, L Mandel, A Shinnar, J Siméon… – LIPIcs-Leibniz …, 2017 – drops.dagstuhl.de
… Automated Speech Recognition (ASR) Natural Language Understanding (NLU) Dialog Interpreter Text to Speech (TTS) Natural Language Generation (NLG) Figure 15 Basic chat bot architecture. Undefined Filled Confirmed Rejected Fill Confirm Reject Repair …

Implementation of a Bangla chatbot
TD Orin – 2017 – dspace.bracu.ac.bd
Page 1. IMPLEMENTATION OF A BANGLA CHATBOT A thesis submitted in partial fulfillment for the Bachelor in Computer Science and Engineering Tasnim Dewan Orin ID-13101224 ?Supervised By: ?Dr. Mahbub Alam Majumdar Professor …

Evaluation of Modern Tools for an OMSCS Advisor Chatbot
E Gregori – 2017 – smartech.gatech.edu
… agent. The human agent will get back to you with an answer as soon as possible.” Chatbot Architecture Up until very recently, chatbots have only supported a single adjacency pair. This is referred to as a one-shot conversation …

Commercial chatbot: performance evaluation, usability metrics and quality standards of embodied conversational agents
K Kuligowska – 2015 – papers.ssrn.com
… behavior. The biggest challenge in designing a chatbot architecture is inventing the mechanism of dialogue context detection, which makes the chatbot keeping pace with a constantly changing topic of conversation. Conversational …

An Oral Exam for Measuring a Dialog System’s Capabilities.
D Cohen, I Lane – AAAI, 2016 – aaai.org
… landscape of capabilities. (Vinyals and Le 2015) presents a novel chatbot architecture, and uses human evaluators to compare systems by how crowd-sourced human evaluators prefer their responses to questions. However, there …

Divalite: A Framework for DOM-based Embodied Conversational Agents Draft V0—December 7, 2011
JP Sansonnet, DW Correa, P Jaques, A Braffort… – perso.limsi.fr
… This is quite analogous to the way Short Mes- saging Service language (SMS) is used (eg “Takako wru”=“Takako who are you?” [6]). Also to simplify, liteTalk adopts main conventions of traditional chatbots architectures such as: not case-sensitive; discards most non alphanu …

TEATIME: a Formal Model of Action Tendencies in Conversational Agents
A Yacoubi, N Sabouret – perso.limsi.fr
… This corresponds to the re-appraisal pro- cess as described by Frijda (Frijda, 1986). 5 IMPLEMENTATION EXAMPLE The TEATIME formal model has been imple- mented in Java and integrated within a virtual agents and chatbot architecture for Customer Relationship Service …

Corpus linguistics and language learning: bootstrapping linguistic knowledge and resources from text
ES Atwell – 2008 – etheses.whiterose.ac.uk
… involves using corpora in machine-learning chatbot systems [136] (Abu Shawar and Atwell 2005). The AIML chatbot architecture requires a set of input-reply patterns or templates, which allow the chatbot to find an appropriate response to any user input …

Chatbot for Laundry and Dry Cleaning Service
BJ K?íž – is.muni.cz
Page 1. Masaryk University Faculty of Informatics Chatbot for Laundry and Dry Cleaning Service Master’s Thesis Bc. Jakub K?íž Brno, Spring 2017 Page 2. Masaryk University Faculty of Informatics Chatbot for Laundry and Dry Cleaning Service Master’s Thesis Bc. Jakub K?íž …

A chatbot service for use in video game development
AJ Larsen – 2015 – 146.141.12.21
Page 1. A Chatbot Service for use in Video Game Development Alec John Larsen A dissertation submitted to the Faculty of Engineering and the Built Environment, University of the Witwatersrand, Johannesburg, in fulfilment of the requirements for …

liteTalk: A Framework for Conversational Interaction with DOM-based Agents Draft V1. 0–March 23, 2012.
JP Sansonnet – perso.limsi.fr
Page 1. liteTalk: A Framework for Conversational Interaction with DOM-based Agents Draft V1.0 – March 23, 2012. Jean-Paul Sansonnet1 1CNRS-LIMSI, Paris-Sud University, France Abstract. In this draft we present liteTalk …

Sabbiu Shah (070/BCT/531) Sagar Adhikari (070/BCT/533) Samip Subedi (070/BCT/536)
U Chalise – 2017 – researchgate.net
Page 1. TU IE Central Campus, Pulchowk A MAJOR PROJECT REPORT ON WVA By: Sabbiu Shah (070/BCT/531) Sagar Adhikari (070/BCT/533) Samip Subedi (070/BCT/536) Utsab Chalise (070/BCT/548) A PROJECT WAS …

liteTalk: A Framework for Conversational Interaction with DOM-based Agents Draft V1. 1–April 3, 2012.
JP Sansonnet – perso.limsi.fr
Page 1. liteTalk: A Framework for Conversational Interaction with DOM-based Agents Draft V1.1 – April 3, 2012. Jean-Paul Sansonnet1 1CNRS-LIMSI, Paris-Sud University, France Abstract. In this draft we present liteTalk, a …

A Chatbot for Psychiatric Counseling in Mental Healthcare Service Based on Emotional Dialogue Analysis and Sentence Generation
KJ Oh, D Lee, B Ko, HJ Choi – Mobile Data Management (MDM …, 2017 – ieeexplore.ieee.org
… To talk like the example, the Chatbot should remember the temporal and spatial context and respond appropriately according to the context. IV. EMOTIOANL DIALOGUE ANALYSIS Figure 6. The counseling chatbot architecture. 374 Page 5 …

Modeling tools for the integration of structured data sources
J Venkataramanan – 2010 – dspace.mit.edu
… 56 Figure 17. Screen capture of implementation of schema sub-model ….. 57 Figure 18. Chat bot Architecture based on the structured data parser presented in this research ….. 60 Page 10. 10 Page 11. 1. Introduction …

E-AI an emotion architecture for agents in games & virtual worlds
S Slater – 2010 – wlv.openrepository.com
Page 1. I E-AI an Emotion Architecture for Agents in Games & Virtual Worlds Stuart Slater B.Eng (Hons) MSc A Thesis Submitted in Partial Fulfilment of the Requirements of the University of Wolverhampton for the Degree of Doctor of Philosophy March 2010 …

Robust dialog management through a context-centric architecture
VC Hung – 2010 – stars.library.ucf.edu
Page 1. University of Central Florida Electronic Theses and Dissertations Doctoral Dissertation (Open Access) Robust Dialog Management Through A Context- centric Architecture 2010 Victor C. Hung University of Central Florida …