臺灣博碩士論文加值系統

現有的收尋引擎幾乎都是使用關鍵字比對（Keyword-Matching）的技術，作為檢索的方式。傳統的關鍵字比對技術只是單純利用字彙在語法上的比對，而忽略其在語意上的比對，也就是使用者必須使用相同的字詞，才能找到所需的資訊。但隨著資訊源的快速成長，其檢索的結果會產生較低的精準度。在此我們應用詞彙集（Thesaurus）及本體論（Ontology）所表達的特定領域知識與略圖（Schema），來提供使用者查詢的方式，幫助系統了解使用者提出的查詢問題，並且希望能針對使用者的問題，有精確的答案產生。
這篇論文提出一個系統以歷史領域的詞彙表及本體論為基礎的查詢問題機制，並且提供較關鍵詞比對好的機制。我們利用本體論來表示領域知識，讓使用者藉由查詢略圖（Query Schema）的幫助之下，能夠提出簡單的歷史問題。系統中利用詞彙集中所表達的知識來幫助系統了解使用者的查詢中的語意。根據查詢問題，系統可以從特定的資訊源取出資訊，並且提供給使用者一個精確的答案。
我們也利用RDF/RDFS的架構來表達本體論中所內含的領域知識與關係，希望讓其他的研究人員可以更容易地了解已建構的知識結構，因此達到本體論能夠被共享與重複使用的目的。

Contents
摘要
Chapter 1 Introduction
1.1 Background
1.2 Problem Description
1.3 Organization of Thesis
Chapter 2 Related Works
Chapter 3 The System Overview
3.1 Ontology Reusing Cycle
3.2 The Ontology-based Answer Extraction System
3.2.1 Overall Scenario
3.2.2 Why Using RDF/RDFS
3.2.3 Event Ontology
3.2.3.1 Event Structure
3.2.3.2 Time and Location Structure
3.2.4 The Chinese Synonym Thesaurus
3.2.5 The Pattern Rules
Chapter 4 The Answer Extraction Based on Event Ontolog
4.1 Representation of Sentence
4.1.1 Simple Sentence
4.1.2 Linguistic Analysis of Sentences
4.2 Query over Ontology
4.2.1 Query Schema
4.2.2 Extract Answers with Query Schema
4.2.3 Examples
Chapter 5 The Implementation and Experiments
5.1 The Implementation
5.1.1 Word Segmentation
5.1.2 Query Interface
5.2 Experiments
5.2.1 Experiment of Architecture
5.2.2 Results and Discussions
5.2.2.1 The Advantages of the Systems
5.2.2.2 The Weaknesses of the Systems
Chapter 6 Conclusion and Future Work
References
Appendix A
A.1 Event Ontology in RDF/RDFS
A.2 Pattern Schemas
A.3 Simple Questions
A.4 A Chinese Historical Tagged Text
A.5 A Chinese Historical Text

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