Notes:
A concrete syntax tree, also known as a parse tree or parsing tree, is a data structure that represents the syntactic structure of a string of text according to a context-free grammar. A context-free grammar is a set of rules that describe how words and phrases in a language can be combined to form sentences that are grammatically correct.
A concrete syntax tree is constructed by applying the rules of a context-free grammar to a string of text, and represents the hierarchical structure of the sentence. Each node in the tree represents a word or phrase in the sentence, and the relationships between nodes represent the grammatical relationships between the words or phrases. For example, the root node of the tree might represent the subject of the sentence, and child nodes might represent the verb and object of the sentence.
Concrete syntax trees are used in a variety of applications, including natural language processing, programming language analysis, and automated theorem proving. They can be used to represent the syntactic structure of a sentence, to identify and classify the parts of speech in a sentence, and to help determine the meaning of a sentence.
Concrete syntax trees (CSTs) can be used in the development and implementation of dialog systems to help the system understand and interpret the structure and meaning of user input. CSTs can be used in combination with natural language processing (NLP) techniques to analyze the syntactic structure of user input and to identify the parts of speech and grammatical relationships between words and phrases.
For example, a dialog system might use a CST to analyze a user’s input and identify the main verb or action in the sentence. This information can be used to determine the intent behind the user’s input, and to select an appropriate response or action.
In addition to helping the system understand and interpret user input, CSTs can also be used to generate natural-sounding responses to users. By analyzing the structure and syntax of a user’s input, a dialog system can generate responses that use similar structures and syntactic patterns, which can help to create a more natural and conversational feel to the interaction.
Wikipedia:
See also:
100 Best Decision Tree Videos | Apple Pie Parser | Conversation Trees | Grammar Parsers & Dialog Systems | Grammar Trees & Dialog Systems | HPSG Parsers | LALR Parser | Ontology Parsers | Sentence Parsers & Dialog Systems
Semantic parsing for task oriented dialog using hierarchical representations
S Gupta, R Shah, M Mohit, A Kumar… – arXiv preprint arXiv …, 2018 – arxiv.org
… Page 3. • Execution Our approach can be seen as a simple generalization of traditional dialog systems, meaning that existing infrastructure can easily be adapted to … We briefly review the RNNG model – The parse tree is constructed using a sequence of transitions, or ‘actions’ …
Building dialogue structure from discourse tree of a question
B Galitsky – Workshops at the Thirty-Second AAAI Conference on …, 2018 – aaai.org
… Galitsky, B. 2013. Machine learning of syntactic parse trees for search and classification of text. Engineering Application of AI , 26(3) 1072-91 … 2016. On the evaluation of dialogue systems with next utterance classification. In Special Interest Group on Discourse and Dia- logue …
Experiments in proactive symbol grounding for efficient physically situated human-robot dialogue
J Arkin, TM Howard – Late-breaking Track at the SIGDIAL Special …, 2018 – robodial.github.io
… the action is understood or by a dialog system when the action is ambiguous. Mathematically, we consider PSG to reduce the number of phrases that we need to evaluate for a novel instruction, defined as a reduction in phrases ˆ? as a function of the original parse tree ? and …
Distinguishing between facts and opinions for sentiment analysis: Survey and challenges
I Chaturvedi, E Cambria, RE Welsch, F Herrera – Information Fusion, 2018 – Elsevier
… 29] and political [30] forecasting, e-health [31] and e-tourism [32], human communication comprehension [33] and dialogue systems [34], etc … Natural language data take discrete structures (known as parse tree) hence co-evolution kernels such as sequence and tree kernels are …
Iris: A conversational agent for complex tasks
E Fast, B Chen, J Mendelsohn, J Bassen… – Proceedings of the …, 2018 – dl.acm.org
… the conversation. The resulting conversation data and parse tree can then be used to train more advanced models. We … of tasks. RELATED WORK Iris is inspired by other dialogue systems that engage with complex tasks. Like …
Recent trends in deep learning based natural language processing
T Young, D Hazarika, S Poria… – ieee Computational …, 2018 – ieeexplore.ieee.org
… processed in less than a second [1]. NLP enables computers to perform a wide range of natural language related tasks at all levels, ranging from parsing and part- of-speech (POS) tagging, to machine translation and dialogue systems …
The natural language decathlon: Multitask learning as question answering
B McCann, NS Keskar, C Xiong, R Socher – arXiv preprint arXiv …, 2018 – arxiv.org
… Goal-Oriented Dialogue. Dialogue state tracking is a key component of goal-oriented dialogue systems. Based on user utterances, actions taken already, and conversation history, dialogue state trackers keep track of which …
Building and learning structures in a situated blocks world through deep language understanding
I Perera, J Allen, CM Teng, L Galescu – Proceedings of the First …, 2018 – aclweb.org
… We focus on two tasks for evaluating our system within the context of a natural language dialogue system … Next, the features are extracted from the same parse tree, which typically contains a feature name as an arrangement name (eg, a column), a scale (eg, width-scale), or a …
A multi-view fusion neural network for answer selection
L Sha, X Zhang, F Qian, B Chang, Z Sui – Thirty-Second AAAI Conference …, 2018 – aaai.org
… In human-computer dialog systems, for example, the dialog agent needs to respond to questions is- sued by the user … Traditional methods are typically based on lexical and syntactic features, eg, the edit distance between parse trees (Heilman and Smith 2010) …
Arabic Speech Act Recognition Techniques
L Sherkawi, N Ghneim, OA Dakkak – ACM Transactions on Asian and …, 2018 – dl.acm.org
… Its importance comes from its wide variety of applications, such as in tutorial dialogue systems (Ezen-Can and Boyer 2015b; Rus 2017), machine translation in dialogue systems, conversational analysis … (2014) used syntactic features derived from a deep parse tree to recognize …
On the effects of using word2vec representations in neural networks for dialogue act recognition
C Cerisara, P Kral, L Lenc – Computer Speech & Language, 2018 – Elsevier
… Their approach gives 95.8% DA recognition accuracy on Czech train ticket reservation corpus with 4 DA classes. A recent work in the dialogue act recognition field (Král and Cerisara, 2014) also successfully uses a set of syntactic features derived from a deep parse tree …
Applying pragmatics principles for interaction with visual analytics
E Hoque, V Setlur, M Tory… – IEEE transactions on …, 2018 – ieeexplore.ieee.org
… In order to generate the analytical function representation of the whole utterance, we traverse the corresponding parse tree (generated by the parser described in [35]) in post-order and apply the above two rules iteratively on the phrases as illustrated in Figure 5. Here, the …
Graph Convolutional Network with Sequential Attention For Goal-Oriented Dialogue Systems
S Banerjee, MM Khapra – 2018 – openreview.net
… Goal-oriented dialogue systems which can assist humans in various day-to-day activities have widespread applications in several domains such as e … In particular, we compute the dependency parse tree for each utterance in the conversation and use a GCN to capture the …
Information-Oriented Evaluation Metric for Dialogue Response Generation Systems
P Liu, S Zhong, Z Ming, Y Liu – 2018 IEEE 30th International …, 2018 – ieeexplore.ieee.org
… (a) Declarative Sentence (b) Special Question Figure 1. Dependency Parse Tree Generated by Spacy The triple extraction of special question is different from the non-special question sentence … [3] Liu, Chia-Wei, et al. “How NOT To Evaluate Your Dialogue System: An Empirical …
Tree-Structured Neural Machine for Linguistics-Aware Sentence Generation
G Zhou, P Luo, R Cao, Y Xiao, F Lin, B Chen… – Thirty-Second AAAI …, 2018 – aaai.org
… Instead of generating the response to a given input post directly, we aim to gener- ate the dependency parse tree of the corresponding response in top-down fashion … For example, to gen- erate the constituency parse tree for a sentence (shown in Fig …
Jointly Parse and Fragment Ungrammatical Sentences
HB Hashemi, R Hwa – Thirty-Second AAAI Conference on Artificial …, 2018 – aaai.org
… The methods jointly learn to parse a sentence and prune implausible head-modifier arcs of the parse tree considering the grammatical errors that might ex- ist in the sentence … 2015), grammar error correction (Schmaltz et al. 2016), and dialogue systems (Serban et al. 2015) …
Intelligent conversation system using multiple classification ripple down rules and conversational context
D Herbert, BH Kang – Expert Systems with Applications, 2018 – Elsevier
… all suffered from poor inter-domain applicability; considerable effort is needed as grammars are complex and parse trees need to be … although such systems are primarily concerned with NL querying interfaces to databases (and not as spoken dialog systems or conversational …
A Review on Artificial Intelligence Decision Making Support System
SS Harnish Shah – j-asc.com
… Various tasks in Natural Language Processing (NLP) can be presented as a question answering problem. Moreover, QA can be used to develop dialogue systems and chatbots … Here’s what the beginning of the parse tree will look like for our sentence …
Conversation Analysis Structured Dialogue for Multi-Domain Dialogue Management
N Duran, S Battle – 2018 – researchgate.net
… We also highlight a number of approaches to dialogue systems that use DA to inform the selection of subsequent dialogue turns. 3.0.1 Dialogue Structure … Similarly, DA are used in [3] to automatically create ‘parse-tree-like’ task/subtask structures in task-oriented dialogues …
Dynamic Fuzzy Parser to Parse English Sentence Using POS Tagger and Fuzzy Max-Min Technique
SG Kanakaraddi, SS Nandval – 2018 International Conference …, 2018 – ieeexplore.ieee.org
… mainly limiting the discussion to the domain of computational linguistic only and computes the meaning representation.In spoken dialogue system, NLU component is … In natural language, the syntactic analysis is the method of assigning a parse tree to a given natural language …
Applying Coreference Resolution for Usage in Dialog Systems
G Rolih – 2018 – diva-portal.org
… In chapter 4 we describe our adaptation of a rule-based coreference algorithm and its integration into the Teneo dialog system … Hobbs algorithm traverses the surface parse tree breadth-first, left-to-right, and looks for an antecedent that matches the pronoun in gender and …
TBCNN for Dependency Trees in Natural Language Processing
L Mou, Z Jin – Tree-Based Convolutional Neural Networks, 2018 – Springer
… Statistics of the Stanford Natural Language Inference dataset where each sentence is parsed into a dependency parse tree … are better than CNNs in most text generation applications, eg, machine translation, abstractive summarization, and human–computer dialog systems …
Response selection from unstructured documents for human-computer conversation systems
Z Yan, N Duan, J Bao, P Chen, M Zhou, Z Li – Knowledge-Based Systems, 2018 – Elsevier
… Prior work in measuring the relevance between question and answer focuses mainly on the syntactic level by matching parse trees. Wang et al. [22] present a probabilistic model to learn tree-edit operations on a dependency parse tree …
Enhancing automatic speech recognition for mathematical applications via incremental parsing
M Isaac, E Pfluegel, G Hunter… – Proceedings of the …, 2018 – researchgate.net
… from dictation systems to voice control of household devices (through systems such as Alexa and Amazon Echo) and dialogue systems for telephone … efficient, by only reparsing those parts of the program code which had actually changed, and merging the parse trees of the …
Response Selection and Automatic Message-Response Expansion in Retrieval-Based QA Systems using Semantic Dependency Pair Model
MH Su, CH Wu, KY Huang, WH Lin – ACM Transactions on Asian and …, 2018 – dl.acm.org
… The study proposed syntactic filtering and content-based retrieval of Twitter sentences to select appropriate sentences used for response generation in a dialog system … In this study, we construct the SDG from the parse tree of the sentence using the CKIP- PCFG parser …
Identifying Participant Mentions and Resolving Their Coreferences in Legal Court Judgements
S Hingmire, GK Palshikar… – Text, Speech, and …, 2018 – books.google.com
… For this classifier, we derived 36 features using the dependency and constituency parse trees … Identifying participant mentions and grouping their coreferents together is a challenging task in Legal text mining and Legal dialogue systems …
A Tensor-based Vector Space Semantics for Dynamic Syntax
M Sadrzadeh, M Purver, R Kempson – matrix – eecs.qmul.ac.uk
… based on the grammatical structures given by Lambek’s pregroup grammars (Lambek, 1997); in (Coecke et al., 2013) we show how this semantics also works starting from the parse trees of Lambek’s … Processing self-repairs in an incremental type-theoretic dialogue system …
Sentiment classification using N-ary tree-structured gated recurrent unit networks
V Tsakalos, R Henriques – Proceedings of the 10th International Joint …, 2018 – run.unl.pt
… Moreover, the SST have each sentence structured as constituent parse trees, so we will use the N-ary Tree Structured LSTM(Tai et al., 2015) as a comparison to our model. 4.2 Classification Model … POMDP-based statistical spoken dialog systems: A review …
Identifying Participant Mentions and Resolving Their Coreferences in Legal Court Judgements
A Gupta, D Verma, S Pawar, S Patil, S Hingmire… – … Workshop on Temporal …, 2018 – Springer
… For this classifier, we derived 36 features using the dependency and constituency parse trees … Identifying participant mentions and grouping their coreferents together is a challenging task in Legal text mining and Legal dialogue systems …
Exploring Semantic Incrementality with Dynamic Syntax and Vector Space Semantics
M Sadrzadeh, M Purver, J Hough… – arXiv preprint arXiv …, 2018 – arxiv.org
… DS has sufficient expressivity to capture the dialogue phenomena in (1) and has been used to provide incremental interpretation and gen- eration for dialogue systems (Purver et al., 2011 … (2013) show how this semantics also works starting from the parse trees of Lambek’s …
Modeling Linguistic and Personality Adaptation for Natural Language Generation
Z Hu, JF Tree, M Walker – Proceedings of the 19th Annual SIGdial …, 2018 – aclweb.org
Previous work has shown that conversants adapt to many aspects of their partners’ language. Other work has shown that while every person is unique, they often share general patterns of behavior. Theories of personality aim to explain these shared patterns, and …
External Memory Enhanced Sequence-to-Sequence Dialogue Systems
J Verdegaal – 2018 – pdfs.semanticscholar.org
… Although the aforementioned dialogue system showed that content can be learned to some extent by the seq2seq model, a problem could arise when the system … Therefor it is much harder to use grammatical based models such as context free grammars and parse trees …
Artificial Intelligence Mark-up Language Based Written and Spoken Academic Chatbots using Natural Language Processing
AA ARAIN, A MANZOOR, K BROHI… – Sindh University …, 2018 – sujo-old.usindh.edu.pk
… The output of this stage is a parse tree … Applications of NLP 1 Information extraction 2 Question answering 3 Automatic summarization 4 Machine translation 5 Dialogue system 6 Speech recognition 7 Word segmentation 8 Parts of speech tagging 9 Parsing 10 Human computer …
Natural Language Interface for Databases Using a Dual-Encoder Model
IA Hosu, RCA Iacob, F Brad, S Ruseti… – Proceedings of the 27th …, 2018 – aclweb.org
… NaLIR (Li and Jagadish, 2014) also uses dependency parse trees and several hand-made rules and heuristics to generate candidate SQL statements … 2017. Training end-to-end dialogue systems with the ubuntu dialogue corpus. Dialogue & Discourse, 8(1):31–65 …
Deep Learning in Conversational Language Understanding
G Tur, A Celikyilmaz, X He, D Hakkani-Tür… – Deep Learning in Natural …, 2018 – Springer
… over the sentence sequentially; convolutional neural networks, which accumulate information using filters over short local sequences of words or characters; and tree-structured recursive neural networks (RecNNs), which propagate information up a binary parse tree (Socher et …
Chat Discrimination for Intelligent Conversational Agents with a Hybrid CNN-LMTGRU Network
DS Moirangthem, M Lee – Proceedings of The Third Workshop on …, 2018 – aclweb.org
… The chit-chat dialog systems enable users to have an open-ended chat conversations with the system … In recent sentence representation learning works, neural network models are constructed upon either the input word sequences or the trans- formed syntactic parse tree …
From Compute to Data: Across-the-Stack System Design for Intelligent Applications
Y Kang – 2018 – deepblue.lib.umich.edu
… We have observed that the complexity of building dialogue system for a real-world use case is often substantially greater than those studied in the re … classification in a real-world intelligent dialogue system? 1.2 Across-the-Stack System Design for Intelligent Applica- tions …
A deep ensemble model with slot alignment for sequence-to-sequence natural language generation
J Juraska, P Karagiannis, KK Bowden… – arXiv preprint arXiv …, 2018 – arxiv.org
… Abstract Natural language generation lies at the core of generative dialogue systems and conversa- tional agents … We identify these in the utterance’s parse-tree produced by the Stanford CoreNLP toolkit (Manning et al., 2014) by defining a set of rules for extracting the discourse …
Deep learning for sentiment analysis: A survey
L Zhang, S Wang, B Liu – Wiley Interdisciplinary Reviews: Data …, 2018 – Wiley Online Library
Skip to Main Content …
Learning to map context-dependent sentences to executable formal queries
A Suhr, S Iyer, Y Artzi – arXiv preprint arXiv:1804.06868, 2018 – arxiv.org
… For learning, they required full super- vision, including annotated parse trees and con- textual dependencies.2 Zettlemoyer and Collins (2009) addressed the … Context-dependent language understand- ing was also studied for dialogue systems, in- cluding with ATIS Tür et al …
Human interaction with shopping assistant robot in natural language
G Sidorov, I Markov, O Kolesnikova… – Journal of Intelligent & … – content.iospress.com
… Furthermore, we will perform a more complex analysis of each utterance in the dialog based on the parse tree obtained by a … M. Hepple and R. Catizone , Machine learning approaches to human dialogue modeling, In Advances in Natural Multimodal Dialogue Systems, 2005, pp …
Characterizing Variation in Crowd-Sourced Data for Training Neural Language Generators to Produce Stylistically Varied Outputs
J Juraska, M Walker – arXiv preprint arXiv:1809.05288, 2018 – arxiv.org
… The restaurant domain has always been the domain of choice for NLG tasks in dialogue systems (Stentetal., 2004; Gašicetal., 2008; Mairesse et al … judge the level of desirability of specific discourse phenomena in our context, and devise rules based on the parse tree to extract …
A Bi-Encoder LSTM Model for Learning Unstructured Dialogs
D Shekhar – 2018 – digitalcommons.du.edu
… growing rapidly. A Dialog System can communicate with human in text, speech or both … Discourse Ambiguity 16 Page 25. Syntactic ambiguity arises from different types part-of-speech parsing that form differ- ent parse trees for the same sentence. This is illustrated in Figure 1.6 …
Syntactic based approach for grammar question retrieval
L Fang, LA Tuan, SC Hui, L Wu – Information Processing & Management, 2018 – Elsevier
… Moschitti and Basili (2006) proposed tree kernels to generate a large feature set from syntactic parse trees for non-factoid answers classification … To capture the focus of a grammar MCQ, we propose a new structure named as parse-key tree based on syntactic parse tree …
A hierarchy-to-sequence attentional neural machine translation model
J Su, J Zeng, D Xiong, Y Liu, M Wang… – IEEE/ACM Transactions on …, 2018 – dl.acm.org
Page 1. IEEE/ACM TRANSACTIONS ON AUDIO, SPEECH, AND LANGUAGE PROCESSING, VOL. 26, NO. 3, MARCH 2018 623 A Hierarchy-to-Sequence Attentional Neural Machine Translation Model Jinsong Su , Jiali Zeng …
Question Answering for Technical Customer Support
Y Li, Q Miao, J Geng, C Alt, R Schwarzenberg… – … Conference on Natural …, 2018 – Springer
… [3] use a large corpus of support dialogs in the operating system domain to train an end-to-end dialog system for answering … examples include methods based on deeper semantic analysis [7] and quasi-synchronous grammars [8] that match the dependency parse trees of the …
Slug2Slug: A Deep Ensemble Model with Slot Alignment for Sequence-to-Sequence Natural Language Generation
J Juraska, P Karagiannis, KK Bowden, MA Walker – macs.hw.ac.uk
… Natural language generation lies at the core of generative dialogue systems and conversa- tional agents … We identify these in the utterance’s parse-tree produced by the Stanford CoreNLP toolkit (Man- ning et al., 2014) by defining a set of rules for ex- tracting the discourse …
The rapidly changing landscape of conversational agents
V Mathur, A Singh – arXiv preprint arXiv:1803.08419, 2018 – arxiv.org
… Initially, the interactive dialogue systems were based on and limited to speaker independent recognition of isolated words and phrases or limited … The parser made use of alternative word hypotheses represented in a lattice or graph in constructing a parse tree and allowance …
Natural Language Core Tasks and Applications
VN Gudivada – … of Natural Languages: Principles, Methods and …, 2018 – books.google.com
… The lexical information carried over to the root of a parse tree through this process is called the headword of the parse tree … NER results drive other NLP tasks such as coreference resolution, WSD, semantic parsing, QA, dialog systems, textual entailment, IE, information retrieval …
Tree2Tree Learning with Memory Unit
N Miao, H Wang, R Le, C Tao, M Shang, R Yan… – 2018 – openreview.net
… For decoding and tree generation process (Zhang et al., 2015) applies top-down Tree-LSTM to generate dependency parse tree … Frederic Bechet, Yannick Esteve, and Renato De Mori. Tree-based language model dedicated to natural spoken dialog systems …
Improving Object Disambiguation from Natural Language using Empirical Models
D Prendergast, D Szafir – Proceedings of the 2018 on International …, 2018 – dl.acm.org
… (2013) intro- duced a framework of “Generalized Grounding Graphs,” or G3, that dynamically correlates the parse tree of a … Our approach is heavily inspired by the visually situated dialog system in [11], which provides a compelling example of how RO selection might be used as …
Entity-aware Image Caption Generation
D Lu, S Whitehead, L Huang, H Ji… – arXiv preprint arXiv …, 2018 – arxiv.org
… We first apply the Stanford dependency parser (De Marneffe and Manning, 2008) on pre- processed captions. Then, we traverse the parse tree from the root (eg’pours’) via <governor, grammatical relations, dependent> triples using breadth-first search …
Neural Transition-based Syntactic Linearization
L Song, Y Zhang, D Gildea – arXiv preprint arXiv:1810.09609, 2018 – arxiv.org
… tomatically parsed. To train our linearizer, we first generate training examples {(si,ti)}m i=1 from the training sentences and their gold parse trees, where si is a state, and ti ? T is the correspond- ing oracle transition. We use …
German and French Neural Supertagging Experiments for LTAG Parsing
TBA van Cranenburgh Younes, SL Kallmeyer – researchgate.net
… 3 LTAG induction from the French Treebank Inducing a grammar from a treebank entails iden- tifying a set of productions that could have pro- duced its parse trees … 2002. Hid- den markov model-based supertagging in a user- initiative dialogue system …
Learning to Generate Structured Queries from Natural Language with Indirect Supervision
Z Bai, B Yu, B Wu, Z Wang, B Wang – arXiv preprint arXiv:1809.03195, 2018 – arxiv.org
… Nowadays, task oriented dialogue systems al- low intuitive interaction through natural language, where natural language understanding (NLU) is an … one or more of the following techniques, rule based pattern matching, syntac- tic grammars based parse tree mapping, semantic …
German and French Neural Supertagging Experiments for LTAG Parsing
T Bladier, A van Cranenburgh, Y Samih… – Proceedings of ACL …, 2018 – aclweb.org
… 3 LTAG induction from the French Treebank Inducing a grammar from a treebank entails iden- tifying a set of productions that could have pro- duced its parse trees … 2002. Hid- den markov model-based supertagging in a user- initiative dialogue system …
Building a Neural Semantic Parser from a Domain Ontology
J Cheng, S Reddy, M Lapata – arXiv preprint arXiv:1812.10037, 2018 – arxiv.org
… 1. In this work, a derivation tree refers to a parse tree that graphically represents the semantic information of how a meaning representation is derived from a context-free grammar, which does not reply on tokens in the corresponding utterance—this is slightly different from the …
Deep Dialog Act Recognition using Multiple Token, Segment, and Context Information Representations
E Ribeiro, R Ribeiro, DM de Matos – arXiv preprint arXiv:1807.08587, 2018 – arxiv.org
… However, when the discourse model is based on a CNN or a bidirectional LSTM unit, it considers information from future segments, which is not available for a dialog system … Then, it uses the syntactic contexts derived from automatically produced dependency parse-trees …
Interactive Question Answering Using Frame-Based Knowledge Representation
EG Boroujerdi – 2018 – yorkspace.library.yorku.ca
… generated from the constituent parse tree of a sentence. STM encodes syntactic, semantic, and lexical features extracted from tree kernels [19] of questions. This method needs no training data and is robust to minor grammatical errors. 2.4 Dialogue Systems for QA …
Corpus Annotation and Inference with Episodic Logic Type Structure
G Kim – 2018 – cs.rochester.edu
… activity and requirement for understanding. We do not want a dialogue system or other NLU system to jump to unwarranted conclusions about the reality of ghosts or about rats that are bigger than elephants. In a sense, the omissions …
Computational Analysis and Understanding of Natural Languages: Principles, Methods and Applications
CR Rao, VN Gudivada – 2018 – books.google.com
… Classes and Corresponding Languages 3.1 Regular Languages 3.2 Context-Free Languages 3.3 Parse Trees 3.4 Context … entail- ment, language generation, semantic analysis, grammar correction, question- answering systems, spoken dialog systems, chatbots, passage …
Structured Neural Models for Natural Language Processing
M Ma – 2018 – ir.library.oregonstate.edu
… Liang Huang Most tasks in natural language processing (NLP) involves structured information from both input (eg, a sentence or a paragraph) and output (eg, a tag sequence, a parse tree or a translated sentence) … 3 1.2 An example of dependency parse tree …
Interpretable Semantic Textual Similarity Using Lexical and Cosine Similarity
G Majumder, P Pakray, DEP Avendaño – … of the Computer Society of India, 2018 – Springer
… The first task is to produce the parse trees for the sentences (ie identify the chunks) … This work is related to the field of NLU, which gives an explanatory layer is important, with applications in dialogue system, interactive system and educational system …
Lemmatization for Ancient Languages: Rules or Neural Networks?
O Dereza – Conference on Artificial Intelligence and Natural …, 2018 – Springer
… 27], but it is not a very suitable source of data for machine learning because it is represented as parse trees in PSD … to-phoneme encoding [49], OCR post-processing, spelling correction, lemmatisation [41], machine translation [2, 7] and even dialogue systems development [48] …
Gunrock: Building A Human-Like Social Bot By Leveraging Large Scale Real User Data
CY Chen, D Yu, W Wen, YM Yang, J Zhang, M Zhou… – dex-microsites-prod.s3.amazonaws …
… news retrieval Figure 1: Social Bot Framework Figure 1 depicts the social bot dialog system framework … We used the Stanford CoreNLP constituency parser [15] to extract noun phrases and local noun phrases (the leaf level of the parse tree) from the input sentence …
Natural Language Data Management and Interfaces
Y Li, D Rafiei – Synthesis Lectures on Data Management, 2018 – morganclaypool.com
… Second, the success of IBM’s Watson [Ferrucci, 2012] at Jeopardy and the emergence of natural language dialog systems such as Apple’s Siri, Google’s Home, Ama- zon’s Alexa, and Microsoft’s Cortana has further ignited the interest in natural language data analysis and …
An Active Information Seeking Model for Goal-oriented Vision-and-Language Tasks
E Abbasnejad, Q Wu, I Abbasnejad, J Shi… – arXiv preprint arXiv …, 2018 – arxiv.org
… Neural Module Networks (NMNs) were introduced by Andreas et al. in [1, 2]. There the question parse tree is turned into an assembly of modules from a predefined set, which are then used to answer the question. Johnson et al …
The Characteristics of Voice Search: Comparing Spoken with Typed-in Mobile Web Search Queries
I Guy – ACM Transactions on Information Systems (TOIS), 2018 – dl.acm.org
… (2008) defined voice search as “the technology underlying many spoken dialog systems that provide users with the information they request with a spoken query” and reviewed key challenges, such as en- vironmental noise, pronunciation variance, and linguistic issues …
Word Representations for Emergent Communication and Natural Language Processing
M KÅGEBÄCK – research.chalmers.se
Page 1. THESIS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY Word Representations for Emergent Communication and Natural Language Processing MIKAEL KÅGEBÄCK Department of Computer Science and Engineering …
State-of-the-Art Approaches for German Language Chat-Bot Development
N Boisgard – 2018 – ec.tuwien.ac.at
… conversational systems. 2.2.1 Conversational Systems Conversational system, also known as dialog systems, are computer programs which communicate with users using natural language [Jurafsky and Martin, 2017a]. They fall …
Mapping natural language sentences to semantic graphs
X Peng – 2018 – urresearch.rochester.edu
… as a deeper understanding of natural language is increasingly important for user appli- cations such as information extraction, question answering and dialogue systems … tions such as question answering, information extraction, machine comprehension, and dialogue systems …
Selecting and Generating Computational Meaning Representations for Short Texts
C Finegan-Dollak – 2018 – deepblue.lib.umich.edu
Page 1. Selecting and Generating Computational Meaning Representations for Short Texts by Catherine Finegan-Dollak A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy …
Language-Based Bidirectional Human and Robot Interaction Learning for Mobile Service Robots
V Perera – 2018 – reports-archive.adm.cs.cmu.edu
… 38 4.1 Templateexamples . . . . . 44 4.2 Parse tree for the sentence “If the door is open go to the lab and to my office” . . 45 4.3 Corpuscomplexitylevels . . . . . 46 4.4 Complexcommandsexamples …
Deep reinforcement learning for sequence to sequence models
Y Keneshloo, T Shi, CK Reddy… – arXiv preprint arXiv …, 2018 – arxiv.org
… SPICE is a recent evaluation metric proposed for image captioning that tries to solve some of the problems of CIDEr and METEOR by mapping the dependency parse trees of the caption to the semantic scene graph (contains objects, attributes of objects, and relations) ex …
A Survey of Knowledge Representation and Retrieval for Learning in Service Robotics
D Paulius, Y Sun – arXiv preprint arXiv:1807.02192, 2018 – arxiv.org
Page 1. A Survey of Knowledge Representation and Retrieval for Learning in Service Robotics David Pauliusa, Yu Suna,? aUniversity of South Florida, 4220 E Fowler Ave, Tampa, FL, United States, 33620 Abstract Within the …
The First Financial Narrative Processing Workshop (FNP 2018)
M El-Haj, P Rayson, A Moore – 2018 – lrec-conf.org
… v Page 7. Table of Contents An Ontology-Based Dialogue Management System for Banking and Finance Dialogue Systems Duygu Altinok … 59 vi Page 8. An Ontology-Based Dialogue Management System for Banking and Finance Dialogue Systems …
Robust Parsing for Ungrammatical Sentences
H Baradaran Hashemi – 2018 – d-scholarship.pitt.edu
… on statistical parsers. We also hypothesize that breaking up parse trees from problematic parts prevents NLP applications from degrading due to incorrect syntactic analysis … analyses make sense. We call this task parse tree fragmentation. The experimental results suggest …
Using natural language processing for question answering in closed and open domains
M Latifi – 2018 – upcommons.upc.edu
… IX Figure ?1.1: The IR-based question answering system ….. 3 Figure ?2.1: Minipar parse tree for the question “Find 2 vendors who sell enzyme products” …. 28 …
Parsing and Generation for the Abstract Meaning Representation
J Flanigan – 2018 – jflanigan.github.io
… be infinite. Examples of structured prediction tasks include predicting a linear sequence of words, predicting a parse tree, or predicting a graph. These tasks can sometime be formulated as a sequence of multi-class classification decisions, but the view from struc …
A study of model parameters for scaling up word to sentence similarity tasks in distributional semantics
D Milajevs – 2018 – qmro.qmul.ac.uk
… 106 Bibliography 109 A Experimental data 120 9 Page 10. List of Figures 1.1 Three pieces of written natural language . . . . . 15 2.1 A syntactic tree . . . . . 23 2.2 The final parse tree . . . . . 24 …
Answering why-not questions on SPARQL queries
M Wang, J Liu, B Wei, S Yao, H Zeng, L Shi – Knowledge and Information …, 2018 – Springer
… graph. Then, the modified graph pattern will be utilized as an explanation. (iii) If the absence occurs at the query operator level, ANNA will trace the expected items on the query parse tree through a post-order traversal. To save …
Divergently seeking clarification: The emergence of clarification interaction
J Ginzburg, D Kolliakou – Topics in cognitive science, 2018 – Wiley Online Library
Page 1. Topics in Cognitive Science (2018) 1–32 Copyright © 2018 Cognitive Science Society, Inc. All rights reserved. ISSN:1756-8757 print / 1756-8765 online DOI: 10.1111/tops.12333 This article is part of the topic “Miscommunication …
Survey of the state of the art in natural language generation: Core tasks, applications and evaluation
A Gatt, E Krahmer – Journal of Artificial Intelligence Research, 2018 – jair.org
… For example, the generation of spoken utterances in dialogue systems (eg, Walker, Stent, Mairesse, & Prasad, 2007; Rieser & Lemon, 2009; Dethlefs, 2014) is another applica- tion of nlg, but typically it is closely related to dialogue management, so that management and …
Automatic Comprehension of Customer Queries for Feedback Generation
NE Okwunma – 2018 – wiredspace.wits.ac.za
Page 1. Automatic Comprehension of Customer Queries for Feedback Generation Nnamdi Ekene Okwunma (Student Number: 818576) School of Computer Science and Applied Mathematics, University of the Witwatersrand, Johannesburg …
Natural Language Processing with Java: Techniques for building machine learning and neural network models for NLP
RM Reese, AS Bhatia – 2018 – books.google.com
… Evaluation Summary Chapter 10: Using Parsers to Extract Relationships Relationship types Understanding parse trees Using extracted … You’ll learn about statistical machine translation, summarization, dialog systems, complex searches, supervised and unsupervised NLP, and …
Annotation of semantic roles for the Turkish Proposition Bank
GG ?ahin, E Adal? – Language Resources and Evaluation, 2018 – Springer
In this work, we report large-scale semantic role annotation of arguments in the Turkish dependency treebank, and present the first comprehensive Turkish semantic role labeling (SRL) resource: …
Natural Language Understanding for Healthcare Queries
V Raghuram – 2018 – eecs.berkeley.edu
… an utterance a challenge for a computer system. This imposes significant limitations on the capabilities of information retrieval systems (and dialogue systems, Q&A systems, etc.). We attempt to address this problem by adding …
Extracting Linguistic Resources from the Web for Concept-to-Text Generation
G Lampouras, I Androutsopoulos – arXiv preprint arXiv:1810.13414, 2018 – arxiv.org
… Figure 2: Parse tree of a retrieved sentence and its noun phrases … To convert an np to an nl name, we first obtain the pos tags of its words from the parse tree of the sentence the np was extracted from.13 For example, the np “the Red Wine” becomes …
Creating New Concept-Based Representations for Superior Text Analysis and Retrieval
W Shalaby – 2018 – search.proquest.com
… 209 REFERENCES 216 APPENDIX A: LIST OF PUBLICATIONS 235 Page 17. xvi LIST OF FIGURES FIGURE 1: Example Parse Trees 8 FIGURE 2: Distribution of Claim-1 Length 9 FIGURE 3: Architecture of the Knowledge-based Dimensionality Reduc- tion System 25 …
Detecting New, Informative Propositions in Social Media
N Dewdney – 2018 – etheses.whiterose.ac.uk
Page 1. DOCTORAL THESIS Detecting New, Informative Propositions in Social Media Author: Nigel Dewdney Supervisor: Prof. Robert GAIZAUSKAS A thesis submitted in fulfillment of the requirements for the degree of Doctor of Philosophy …
Linguistic and Gestural Adaptation
Z Hu – 2018 – escholarship.org
… I am very fortunate to have him. Several members of the Natural Language and Dialog Systems Lab have contributed … “Entrainment in Pedestrian Direction Giving: How many kinds of entrainment?” Workshop on Spoken Dialog Systems (IWSDS 2014), Napa, CA, USA, Jan …
Teaching Machines to Classify from Natural Language Interactions
S Srivastava – 2018 – pstorage-cmu-348901238291901.s3 …
Page 1. Teaching Machines to Classify from Natural Language Interactions Shashank Srivastava September 2018 CMU-ML-18-109 School of Computer Science Carnegie Mellon University Pittsburgh, PA 15213 Thesis Committee …
Tackling Sequence to Sequence Mapping Problems with Neural Networks
L Yu – arXiv preprint arXiv:1810.10802, 2018 – arxiv.org
Page 1. Tackling Sequence to Sequence Mapping Problems with Neural Networks Lei Yu Mansfield College University of Oxford A thesis submitted for the degree of Doctor of Philosophy Trinity 2017 arXiv:1810.10802v1 [cs.CL] 25 Oct 2018 Page 2 …
Argumentation Mining
M Stede, J Schneider – Synthesis Lectures on Human …, 2018 – morganclaypool.com
… Semantic Role Labeling Martha Palmer, Daniel Gildea, and Nianwen Xue 2010 Spoken Dialogue Systems Kristiina Jokinen and Michael McTear 2009 Introduction to Chinese Natural Language Processing Kam-Fai Wong, Wenjie Li, Ruifeng Xu, and Zheng-sheng Zhang 2009 …
Multimodal Sentiment Analysis
S Poria, A Hussain, E Cambria – 2018 – Springer
… Examples of the second domain will include, but not limited to: computational and psychological models of emotions, bodily manifestations of affect (facial expressions, posture, behavior, physiology), and affective interfaces and applications (dialogue systems, games, learning …
Diving Deep into Event Semantics
Z Liu – 2018 – hunterhector.github.io
Page 1. September 28, 2018 DRAFT Thesis Proposal Diving Deep into Event Semantics Zhengzhong Liu October 2018 School of Computer Science Carnegie Mellon University Pittsburgh, PA 15213 Thesis Committee: Teruko …
Anaphora with non-nominal antecedents in computational linguistics: A survey
V Kolhatkar, A Roussel, S Dipper… – Computational …, 2018 – MIT Press
… For instance, consider the following dialogue from Gundel, Hegarty, and Borthen (2003): Here, a dialogue system aware of non-NAs could generate a clarification request: What should be repeated, the act of eating three pieces of cake or the statement …
Quality Estimation for Machine Translation
L Specia, C Scarton… – Synthesis Lectures on …, 2018 – morganclaypool.com
… Semantic Role Labeling Martha Palmer, Daniel Gildea, and Nianwen Xue 2010 Spoken Dialogue Systems Kristiina Jokinen and Michael McTear 2009 Introduction to Chinese Natural Language Processing Kam-Fai Wong, Wenjie Li, Ruifeng Xu, and Zheng-sheng Zhang 2009 …
Representation learning for natural language
O Mogren – 2018 – mogren.one
… humans (Turing 1950). This was published long before machines were anywhere near being able to succeed at this, while substantial progress has been made in recent years using dialog systems trained on large corpora. Most of …
Identifying Author Topic Stance in Online Discussion Forums
G Patterson – 2018 – escholarship.org
… both sides of an issue. It could also be used to learn the linguistic and rhetorical devices that make for successful persuasive arguments, or the expressions of disagreement, which could then be used in other dialog systems or chatbots. Furthermore, this methodology …
Literature Survey and Datasets
S Poria, A Hussain, E Cambria – Multimodal Sentiment Analysis, 2018 – Springer
… auto-associated memories [126, 176]. Recursive neural networks predict the sentiment class at each node in the parse tree and attempt to capture the negation and its scope in the entire sentence. In the standard configuration …
Lower Bound Resource Requirements for Machine Intelligence
T Gilmanov – 2018 – search.proquest.com
… proaches to solving problems ranging from mobile robot navigation and autonomous self-driving cars to personal assistants, logic game players and dialogue systems … the more complicated dialogue system, the Autonomous Moving Agent (AMA), and the 3-D facial …
Deep Semantic Learning for Conversational Agents
M Morisio, M Mensio – 2018 – webthesis.biblio.polito.it
Page 1. POLITECNICO DI TORINO Master of Science in Computer Engineering Master’s Thesis Deep Semantic Learning for Conversational Agents Supervisor Prof. Maurizio Morisio Candidate Martino Mensio Tutor Istituto Superiore Mario Boella Dr. Giuseppe Rizzo April 2018 …
Automatic Image Captioning with Style
AP Mathews – 2018 – openresearch-repository.anu.edu.au
Page 1. Automatic Image Captioning with Style Alexander Mathews A thesis submitted for the degree of Doctor of Philosophy The Australian National University November 2018 Page 2. c Alexander Mathews 2018 Page 3. Except …
Natural Language Processing and Chinese Computing: 7th CCF International Conference, NLPCC 2018, Hohhot, China, August 26–30, 2018, Proceedings
M Zhang, V Ng, D Zhao, S Li, H Zan – 2018 – books.google.com
Page 1. Min Zhang· Vincent Ng· Dongyan Zhao Sujian Li· Hongying Zan (Eds.) Natural Language Processing and Chinese Computing 7th CCF International Conference, NLPCC 2018 Hohhot, China, August 26–30, 2018 Proceedings, Part I 123 Page 2 …
Maximum Entropy Models for Sequences: Scaling up from Tagging to Translation
P Lehnen – www-i6.informatik.rwth-aachen.de
… 13]. Here, all components of the spoken dialog system, the automatic speech recognition, the spoken language understanding, the dialog manager, the text generation, and the final text to speech, work in an incremental way …
Generating Animated Videos of Human Activities from Natural Language Descriptions
AS Lin, L Wu, R Corona, K Tai, Q Huang, RJ Mooney – Learning, 2018 – cs.utexas.edu
… Further, we demonstrate how the dialog conversations can be leveraged for continuous improvement of the dialog system … Natural language understanding and dialog management are two integral components of interactive dialog systems …
Recurrent Neural Networks
CC Aggarwal – Neural Networks and Deep Learning, 2018 – Springer
“Democracy is the recurrent suspicion that more than half the people are right more than half the time.”— The New Yorker, July 3, 1944.