Discourse analysis of asynchronous conversations
department or school: Science, Faculty of
department or school: Computer Science, Department of
data provider: DSpace
degree campus: UBCV
creator: Joty, Shafiq Rayhan
issued: 2014-01-02T16:12:31Z
issued: 2013
related degree: Doctor of Philosophy - PhD
degree grantor: University of British Columbia
description: A well-written text is not merely a sequence of independent and isolated sentences, but instead a sequence of structured and related sentences. It addresses a particular topic, often covering multiple subtopics, and is organized in a coherent way that enables the reader to process the information. Discourse analysis seeks to uncover such underlying structures, which can support many applications including text summarization and information extraction. This thesis focuses on building novel computational models of different discourse analysis tasks in asynchronous conversations; i.e., conversations where participants communicate with each other at different times (e.g., emails, blogs). Effective processing of these conversations can be of great strategic value for both organizations and individuals. We propose novel computational models for topic segmentation and labeling, rhetorical parsing and dialog act recognition in asynchronous conversation. Our approaches rely on two related computational methodologies: graph theory and probabilistic graphical models. The topic segmentation and labeling models find the high-level discourse structure; i.e., the global topical structure of an asynchronous conversation. Our graph-based approach extends state-of-the-art methods by integrating a fine-grained conversational structure with other conversational features. On the other hand, the rhetorical parser captures the coherence structure, a finer discourse structure, by identifying coherence relations between the discourse units within each comment of the conversation. Our parser applies an optimal parsing algorithm to probabilities inferred from a discriminative graphical model which allows us to represent the structure and the label of a discourse tree constituent jointly, and to capture the sequential and hierarchical dependencies between the constituents. Finally, the dialog act model allows us to uncover the underlying dialog structure of the conversation. We present unsuper…
aggregated CHO: https://circle.library.ubc.ca/rest/handle/2429/45674
note: Discourse Analysis of Asynchronous ConversationsbyShafiq Rayhan JotyB. Sc., Islamic University of Technology, 2005M. Sc., University of Lethbridge, 2008A THESIS SUBMITTED IN PARTIAL FULFILLMENTOF THE REQUIREMENTS FOR THE DEGREE OFDoctor of PhilosophyinTHE FACULTY OF GRADUATE AND POSTDOCTORALSTUDIES(Computer Science)The University Of British Columbia(Vancouver)December 2013c? Shafiq Rayhan Joty, 2013AbstractA well-written text is not merely a sequence of independent and isolated sentences,but instead a sequence of structured and related sentences. It addresses a particulartopic, often covering multiple subtopics, and is organized in a coherent way thatenables the reader to process the information. Discourse analysis seeks to uncoversuch underlying structures, which can support many applications including textsummarization and information extraction.This thesis focuses on building novel computational models of different dis-course analysis tasks in asynchronous conversations; i.e., conversations where par-ticipants communicate with each other at different times (e.g., emails, blogs). Ef-fective processing of these conversations can be of great strategic value for bothorganizations and individuals. We propose novel computational models for topicsegmentation and labeling, rhetorical parsing and dialog act recognition in asyn-chronous conversation. Our approaches rely on two related computational method-ologies: graph theory and probabilistic graphical models.The topic segmentation and labeling models find the high-level discourse struc-ture; i.e., the global topical structure of an asynchronous conversation. Our graph-based approach extends state-of-the-art methods by integrating a fine-grained con-versational structure with other conversational features.On the other hand, the rhetorical parser captures the coherence structure, a finerdiscourse structure, by identifying coherence relations between the discourse unitswithin each comment of the conversation. Our parser ap…
has type: Thesis/Dissertation
date issued: 2014-05
is shown at: 10.14288/1.0165726
language: eng
degree discipline: Computer Science
provider: Vancouver : University of British Columbia Library
publisher: University of British Columbia
rights: Attribution-NonCommercial-NoDerivatives 4.0 International
rights URI: http://creativecommons.org/licenses/by-nc-nd/4.0/
scholar level: Graduate
type: Text
identifier URI: http://hdl.handle.net/2429/45674