Iitd-ibmirl system for question answering using pattern matching, semantic type and semantic category recognition. In Proceedings of The Sixteenth.[r]
(1)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
bản
Content
Table of Contents
1 Introduction
1.1 A Semantic Approach for Question Analysis
1.2 A Vietnamese Text-based Conversational Agent
(2)2 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 12
3 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
4 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
5 Evaluation and Discussion………29
5.1 Experimental results for Vietnamese text-based conversational agent 29
5.2 Question Analysis for English 31
5.3 Discussion 33
6 Conclusion 34
A Scripting patterns
for English question analysis 36
B Definitions of question-class types 38
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