Skip to main content
Disciplines
Automotive Business IT + Informatics Construction + Real Estate Electrical Engineering + Electronics Energy + Sustainability Insurance + Risk Finance + Banking Management + Leadership Marketing + Sales Mechanical Engineering + Materials
Events
DE
EN
Books
Journals
Topic Page
Marketing
Start single access now
Access for companies
EXTENDED SEARCH
Log in
Top
Published in:
Introduction Read chapter Read first chapter

2019 | OriginalPaper | Chapter

11. Discourse-Level Dialogue Management

Author : Boris Galitsky

Published in: Developing Enterprise Chatbots

Publisher: Springer International Publishing

Log in

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

In this Chapter we learn how to manage a dialogue relying on discourse of its utterances. We first explain how to build an invariant discourse tree for a corpus of texts to arrange a chatbot-facilitated navigation through this corpus. We define extended discourse trees, introduce means to manipulate with them, and outline scenarios of multi-document navigation. We then show how a dialogue structure can be built from an initial utterance. After that, we introduce imaginary discourse tree to address a problem of involving background knowledge on demand, answering questions. Finally, an approach to dialogue management based on lattice walk is described.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

inform now
previous chapter Rhetorical Agreement: Maintaining Cohesive Conversations
next chapter A Social Promotion Chatbot
Literature
Agostaro F, Augello A, Pilato G, Vassallo G, Gaglio S (2005) A conversational agent based on a conceptual interpretation of a data driven semantic space, proceedings of AI*IA. LNAI 3673:381–392
Allan J (1996) Automatic hypertext link typing. In: Hypertext’96, The seventh ACM conference on Hypertext, pp 42–52
Amiridze N, Kutsia T (2018) Anti-unification and natural language processing. In: Fifth workshop on natural language and computer science, NLCS’18, EasyChair Preprint no. 203
Augello A, Gentile M, Dignum F (2017) An overview of open-source chatbots social skills. In: Diplaris S, Satsiou A, Følstad A, Vafopoulos M, Vilarinho T (eds) Internet science, Lecture notes in computer science, vol 10750, pp 236–248CrossRef
Barzilay R, Elhadad M (1997) Using lexical chains for text summarization. In: Proceedings of the ACL/EACL’97 workshop on intelligent scalable text summarization. Madrid, Spain, July 1997, pp 10–17.
Barzilay R, Lapata M (2008) Modeling local coherence: An entity-based approach. Comput Linguist 34(1):1–34CrossRef
Bordes A, Weston, J (2016) Learning end-to-end goal-oriented dialog. ICRL 2017
Burtsev M, Seliverstov A, Airapetyan R, Arkhipov M, Baymurzina D, Bushkov N, Gureenkova O, Khakhulin T, Kuratov Y, Kuznetsov D, Litinsky A, Logacheva V, Lymar A, Malykh V, Petrov M, Polulyakh V, Pugachev L, Sorokin A, Vikhreva M, Zaynutdinov M (2018) DeepPavlov: open-source library for dialogue systems. In: ACL-system demonstrations, pp 122–127
Chali Y, Joty SR, Hasan SA (2009) Complex question answering: unsupervised learning approaches and experiments. J Artif Int Res 35(1):1–47MathSciNetMATH
Clarke J, Lapata M (2010) Discourse constraints for document compression. Comput Linguist 36(3):411–441CrossRef
Codocedo V, Napoli A (2014) A proposition for combining pattern structures and relational concept analysis. In: Glodeanu CV, Kaytoue M, Sacarea C (eds) ICFCA 2014. LNCS (LNAI), vol 8478. Springer, Heidelberg, pp 96–111
Elsner M, Charniak E (2008) You talking to me? a corpus and algorithm for conversation disentanglement. In: Proceedings of the 46th annual Meeting of the ACL: HLT (ACL 2008), Columbus, USA, pp 834–842
Feng WV, Hirst G (2014) A linear-time bottom-up discourse parser with constraints and post-editing. In: Proceedings of the 52nd annual meeting of the Association for Computational Lin-guistics (ACL 2014), Baltimore, USA, June.
Galitsky B (2014) Learning parse structure of paragraphs and its applications in search. Eng Appl Artif Intell 32:160–184CrossRef
Galitsky B (2016) Providing personalized recommendation for attending events based on individual interest profiles. AI Research 5(1), Sciedu Press
Galitsky B (2017) Discovering rhetorical agreement between a request and response. Dialogue Discourse 8(2):167–205
Galitsky B, Ilvovsky D (2017a) Chatbot with a discourse structure-driven dialogue management, EACL demo program
Galitsky B, Ilvovsky D (2017b) On a chat bot finding answers with optimal rhetoric representation. In: Proceedings of recent advances in natural language processing, Varna, Bulgaria, 4–6 September, pp 253–259
Galitsky B, Makowski G (2017) Document classifier for a data loss prevention system based on learning rhetoric relations. CICLing 2017, Budapest, Hungary, 17–23 April.
Galitsky B, McKenna EW (2017) Sentiment extraction from consumer reviews for providing product recommendations. US Patent 9646078B2
Galitsky B, Chen H, Du S (2009a) Inverting semantic structure of customer opinions expressed in forums and blogs. In: 17th international conference on conceptual structures, Suppl. Proc.
Galitsky B, González MP, Chesñevar CI (2009b) A novel approach for classifying customer complaints through graphs similarities in argumentative dialogue. Decis Support Syst 46(3):717–729CrossRef
Galitsky B, Dobrocsi G, de la Rosa JL (2012) Inferring the semantic properties of sentences by mining syntactic parse trees. Data Knowl Eng v81:21–45
Galitsky B, Kuznetsov SO, Usikov D (2013) Parse thicket representation for multi-sentence search. In: International conference on conceptual structures, pp 153–172
Galitsky B, Ilvovsky D, Kuznetsov SO, Strok F (2014) Finding maximal common sub-parse thickets for multi-sentence search. In: Graph structures for knowledge representation and reasoning, pp 39–57CrossRef
Galitsky B, Ilvovsky D, Kuznetsov SO (2015) Text classification into abstract classes based on discourse structure. In: Proceedings of recent advances in natural language processing, Hissar, Bulgaria, 7–9 September 2015, pp 200–207.
Galitsky B, Parnis A, Usikov D (2017) Exploring discourse structure of user-generated content. CICLing 2017, Budapest, Hungary, 17–23 April.
Ganter B, Kuznetsov SO (2001) Pattern structures and their projections. In: International conference on conceptual structures, pp 129–142
Grasso F (1999) Playing with RST: two algorithms for the automated manipulation of discourse trees. In: Matousek V, Mautner P, Ocelíková J, Sojka P (eds) Text, speech and dialogue. TSD 1999. Lecture notes in computer science, vol 1692. Springer, Berlin/Heidelberg
Grosz BJ, Sidner CL (1986) Attention, intention and the structure of discourse. Comput Linguist 12(3):175–204
Grosz B, Joshi AK, Weinstein S (1995) Centering: a framework for modeling the local coherence of discourse. Comput Linguist 21(2):203–225
Gundel JK, Hedberg N, Zacharski R (1993) Cognitive status and the form of referring expressions in discourse. Language 69(2):274–307CrossRef
Heerschop B, Goossen F, Hogenboom A, Frasincar F, Kaymak U, de Jong F (2011) Polarity analysis of texts using discourse structure. In: Proceedings of the 20th ACM international conference on information and knowledge management, CIKM ‘11, pp 1061–1070, New York, USA, ACM
Jansen P, Surdeanu M, Clark P (2014) Discourse comple-ments lexical semantics for nonfactoid answer reranking. ACL
Ji Y, Eisenstein J (2014) Representation learning for text-level discourse parsing. ACL 2014
Joty SR, Moschitti A (2014) Discriminative reranking of discourse parses using tree kernels. In: Proceedings of the 2014 conference on Empirical Methods in Natural Language Processing (EMNLP).?
Joty SR, Carenini G, Ng RT, Mehdad Y (2013) Combining intra-and multi- sentential rhetorical parsing for document-level discourse analysis. In: ACL, vol. 1, pp 486–496
Kaytoue M, Codocedo V, Buzmakov A, Baixeries J, Kuznetsov SO, Napoli A (2015) Pattern structures and concept lattices for data mining and knowledge processing. Joint european conference on machine learning and knowledge discovery in databases. Springer, Cham, pp 227–231
Kelley JF (1984) An iterative design methodology for user-friendly natural language office information applications. ACM Trans Inf Syst 2(1):26–41CrossRef
Kerly A, Hall P, Bull S (2007) Bringing chatbots into education: towards natural language negotiation of open learner models. Knowl-Based Syst 20(2):177–185CrossRef
Kim SN, Wang LI, Baldwin T (2010) Tagging and linking web forum posts. In: Proceedings of the 14th conference on Computational Natural Language Learning (CoNLL-2010), Uppsala, Sweden, pp 192–202
Kovalerchuk B, Kovalerchuk M (2017) Toward virtual data scientist with visual means. In: IJCNN.
Kuyten P, Bollegala D, Hollerit B, Prendinger H, Aizawa K (2015) A discourse search engine based on rhetorical structure theory. In: Hanbury A, Kazai G, Rauber A, Fuhr N (eds) Advances in information retrieval. ECIR 2015, Lecture notes in computer science, vol 9022. Springer, Cham
LeThanh H, Abeysinghe G, Huyck C (2004) Generating discourse structures for written texts. In: Proceedings of the 20th international conference on computational linguistics, COLING ‘04, Geneva, Switzerland. Association for Computational Linguistics
Lioma C, Larsen B, Lu W (2012). Rhetorical relations for information retrieval. SIGIR. Portland, Oregon, USA, 12–16 August 2012
Louis A, Joshi AK, Nenkova A (2010) Discourse indicators for content selection in summarization. In Fernandez R, Katagiri Y, Komatani K, Lemon O, Nakano M (eds) SIGDIAL conference, The Association for Computer Linguistics, pp 147–156
Lowe RIV, Noseworthy M, Charlin L, Pineau J (2016) On the evaluation of dialogue systems with next utterance classification. In: Special interest group on discourse and dialogue
Marcu D (2000) The rhetorical parsing of unrestricted texts: a surface-based approach. Comput Linguist 26:395–448CrossRef
Marcu D, Echihabi A (2002) An unsupervised approach to recognizing discourse relations. In: Proceedings of the 40th annual meeting on Association for Computational Linguistics, ACL’02, pp 368–375
Marir F, Haouam K (2004) Rhetorical structure theory for content-based indexing and retrieval of Web documents, ITRE 2004. In: 2nd international conference information technology: research and education, pp 160–164
Morato J, Llorens J, Genova G, Moreiro JA (2003) Experiments in discourse analysis impact on information classification and retrieval algorithms. Info Process Manag 39:825–851CrossRef
Nagarajan V, Chandrasekar P (2014) Pivotal sentiment tree classifier. IJSTR V.3, I, 11 November.
Nguyen DT, Joty S (2017) A neural local coherence model. ACL 1:1320–1330
Poesio M, Stevenson R, Di Eugenio B, Hitzeman J (2004) Centering: A parametric theory and its instantiations. Comput Linguist 30(3):309–363CrossRef
Radev DR (2000) A common theory of information fusion from multiple text sources step one: cross-document structure. In: Proceedings of the 1st SIGDIAL workshop on discourse and dialogue (SIGDIAL) ‘00, pp 74–83
Rose CP, Di Eugenio B, Levin LS, Van Ess-Dykema C (1995) Discourse processing of dialogues with multiple threads. In: Proceedings of the 33rd annual meeting of the association for computational linguistics, Cambridge, USA, pp 31–38
Sakai T (2007) Alternatives to Bpref. In: Proceedings of the 30th annual international ACM SIGIR conference on research and development in information retrieval. Amsterdam, The Netherlands, ACM, pp 71–78
Seo JW, Croft B, Smith DA (2009) Online community search using thread structure. In: Proceedings of the 18th ACM Conference on Information and Knowledge Management (CIKM 2009), Hong Kong, China, pp 1907–1910.
Sidorov G, Velasquez F, Stamatatos E, Gelbukh A, Chanona-Hernández L (2012) Syntactic Dependency-based N-grams as Classification Features. LNAI 7630:1–11
Singh Ospina N, Phillips KA, Rodriguez-Gutierrez R, Castaneda-Guarderas A, Gionfriddo MR, Branda ME, Montori VM (2019) Eliciting the patient’s agenda- secondary analysis of recorded clinical encounters. J Gen Intern Med 34(1):36–40CrossRef
Somasundaran S, Namata G, Wiebe J, Getoor L (2009) Supervised and unsupervised methods in employing discourse relations for improving opinion polarity classification. In: EMNLP, ACL, pp 170–179.
Soricut R, Marcu D (2003) Sentence level discourse parsing using syntactic and lexical information. In: HLT-NAACL.
Sporleder C, Lascarides A (2004) Combining hierarchical clustering and machine learning to predict high-level discourse structure. In: Proceedings of the 20th international conference on Computational Linguistics, COLING’04, Geneva, Switzerland
Sun M, Chai JY (2007) Discourse processing for context question answering based on linguistic knowledge. Know Based Syst 20:511–526CrossRef
Surdeanu M, Hicks T, Valenzuela-Escarcega MA (2015) Two practical rhetorical structure theory parsers. In: Proceedings of the conference of the North American Chapter of the Association for Computational Linguistics – Human Language Technologies: Software Demonstrations (NAACL HLT).
Suwandaratna N, Perera U (2010). Discourse marker based topic identification and search results refining. In: Information and automation for sustainability (ICIAFs), 2010 5th International conference on, pp 119–125
Teufel S, Moens M (2002) Summarizing scientific articles: experiments with relevance and rhetorical status. Comput Linguist 28(4):409–445, 2002CrossRef
Trigg R, Weiser M (1987) TEXTNET: A network-based approach to text handling. ACM Trans Off Inf Sys 4(1):1–23
Wanas N, El-Saban M, Ashour H, Ammar W (2008) Automatic scoring of online discussion posts. In: Proceeding of the 2nd ACM workshop on Information credibility on the web (WICOW’08), Napa Valley, USA, pp 19–26.
Wang Z, Lemon O (2013) A simple and generic belief tracking mechanism for the dialog state tracking challenge: on the believability of observed information. In: Proceedings of the SIGDIAL
Wang DY, Luk RWP, Wong KF, Kwok KL. (2006) An information retrieval approach based on discourse type. In: Kop C, Fliedl G, Mayr HC, M’etais E (eds), NLDB, volume 3999 of Lecture notes in computer science, Springer, pp 197–202.
Wang W, Su J, Tan CL (2010) Kernel based discourse relation recognition with temporal ordering information. ACL
Wang L, Lui M, Kim SN, Nivre J, Baldwin T (2011) Predicting thread discourse structure over technical web forums. In: Proceedings of the 2011 conference on empirical methods in natural language processing, Edinburgh, UK, pp 13–25
Wilks YA (ed) (1999) Machine conversations. Kluwer, Boston
Wolf F, Gibson E (2005) Representing discourse coherence: A corpus-based study. Comput Linguist 31(2):249–287CrossRef
Young S, Gasic M, Thomson B, Williams J (2013) POMDP-based statistical spoken dialogue systems: a review. In: Proceedings of IEEE, vol 99, pp 1–20
Zeldes A (2016) rstWeb – a browser-based annotation Interface for rhetorical structure theory and discourse relations. In: Proceedings of NAACL-HLT 2016 (demonstrations). San Diego, California, June 12–17, 2016, pp 1–5
Zhao J, Chevalier F, Collins C, Balakrishnan R (2012) Facilitating discourse analysis with interactive visualization. IEEE Trans Vis Comput Graph 18(12):2639–2648CrossRef
Metadata
Title
Discourse-Level Dialogue Management
Author
Boris Galitsky
Copyright Year
2019
Book
Developing Enterprise Chatbots

Print ISBN: 978-3-030-04298-1

Electronic ISBN: 978-3-030-04299-8

Copyright Year: 2019

DOI
https://doi.org/10.1007/978-3-030-04299-8_11

Premium Partner

    Image Credits