DSpace at VNU: A Vietnamese Text-based Conversational Agent

A Vietnamese Text-based Conversational Agent Nguyễn Quốc Đại Trường Đại học Công nghệ Luận văn Thạc sĩ ngành: Khoa học máy tính; Mã số: 60 48 01 Người hướng dẫn: TS Phạm Bảo Sơn Năm bảo vệ: 2011 Abstract The first step that a question answering system must perform is to transform an input question into an intermediate representation Most published works so far use rule-based approaches to realize this transformation in question answering systems Nevertheless, in existing rule-based approaches, manually creating the rules is error-prone and expensive in time and effort In this thesis, we focus on introducing a rule-based approach that offers an intuitive way to create compact rules for extracting intermediate representation of input questions Experimental results are promising where our system achieves reasonable performance and demonstrate that it is straightforward to adapt to new domains and languages More importantly, this thesis introduces a Vietnamese text-based conversational agent architecture on specific knowledge domain which is integrated in a question answering system When the question answering system fails to provide answers to user input, our conversational agent can step in to interact with users to provide answers to users Experimental results are promising where our Vietnamese text-based conversational agent achieves positive feedback in a study conducted in the university academic regulation domain Keywords Trí tuệ nhân tạo; Đàm thoại; Ngơn ngữ máy tính; Tiếng Việt; Văn Content Table of Contents Introduction 1.1 A Semantic Approach for Question Analysis 1.2 A Vietnamese Text-based Conversational Agent 1.3 Thesis Organisation 1 Literature review 2.1 Text-based conversational agents 2.1.1 Using keywords for pattern matching 2.1.2 Using the sentence similarity measure for pattern matching 2.2 FrameScript Scripting Language 2.3 Question answering systems 4 12 Our Question Answering System Architecture 15 3.1 Vietnamese Question Answering System 15 3.1.1 Natural language question analysis component 16 3.1.1.1 Intermediate representation ofan input question 16 3.1.1.2 Question analysis 17 3.1.2 Answer retrieval component 18 3.2 Using FrameScript for question analysis 19 3.2.1 Preprocessing module 19 3.2.2 Syntactic analysis module 20 3.2.3 Semantic analysis module 22 Text-based Conversational Agent for Vietnamese 24 4.1 Overview of architecture 24 4.2 Determining separate contexts 25 4.3 Identifying hierarchical contexts 27 Evaluation and Discussion………………………………………………………29 5.1 Experimental results for Vietnamese text-based conversational agent 29 5.2 5.3 Question Analysis for English 31 Discussion 33 Conclusion 34 A Scripting patterns for English question analysis 36 B 38 Definitions of question-class types C Definitions of question-structures 40 References Ion Androutsopoulos, Graeme Ritchie, and Peter Thanisch Natural language interfaces to databases — an introduction Natural Language Engineering, 1:29-81, 1995 William W Cohen, Pradeep Ravikumar, and Stephen E Fienberg A comparison of string distance metrics for name-matching tasks In Proceedings of IJCAI-03 Workshop on Information Integration, pages 73-78, 2003 Hammish Cunningham, Diana Maynard, Kalina Bontcheva, and Valentin Tablan GATE: A Framework and Graphical Development Environment for Robust NLP Tools and Applications In Proceedings of the 40th Anniversary Meeting of the Association for Computational Linguistics, pages 168-175, 2002 Danica Damljanovic, Valentin Tablan, and Kalina Bontcheva A text-based query interface to owl ontologies In Proceedings of 6th Language Resources and Evaluation Conference, 2008 Christiane D Fellbaum WordNet: An Electronic Lexical Database MIT Press, 1998 A Galea Open-domain surface-based question answering system In Proceedings of the Computer Science Annual Workshop (CSAW), 2003 Arthur C Graesser, Shulan Lu, George Tanner Jackson, Heather Hite Mitchell, Mathew Ventura, Andrew Olney, and Max M Louwerse AutoTutor: A Tutor with Dialogue in Natural Language Behavioral Research Methods, Instruments, and Computers, Vol 36:180-192, 2004 L Hirschman and R Gaizauskas Natural Language Question Answering: The View from here Natural Language Engineering, Vol 7:275-300, 2001 Boris Katz Annotating the world wide web using natural language In Proceedings of the 5th RIAO Conference on Computer Assisted Information Searching on the Internet - 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