臺灣博碩士論文加值系統

隨著近年來網路快速的發展，我們經由網路可以接觸到的網路資源也隨之越來越多，但問題卻也伴隨而來，例如：缺乏有效尋找到有用資源的辦法。雖然對這個問題已經有很多有效的解決辦法，而眾多解決辦法之中以搜尋引擎及其相關的技術在此領域最為蓬勃發展，但仍然有一部分的問題尚需解決，如本篇論文中會提到的（一）對於一個短查詢來說，搜尋引擎不容易了解使用者的目的，難以提供給使用者真正想取得資源位置。（二）搜尋引擎如同就像無邊境的圖書館，雖然網頁被索引起來，但是當索引的數量過於龐大的話，仍需一套好的分群的辦法將大量的結果根據描述主題分群，來提高搜尋引擎能給使用者的便利性。因此，本篇論文的重心在於延續前人的對於分群的研究，以對於搜尋結果的分析，找出可運用的新特徵及一套可使用於中文搜尋環境下的分群方法，不僅預先替使用者產生易讀的群名，提高使用者使用搜尋引擎的便利性。另外，本篇論文亦會對一個查詢，適不適合作分群的處理作研究，目的在於避免不必要的處理，造成使用者多餘的閱讀負擔。

As the rapid development of the network environment in recent years, we could get more and more Web resources, however some problems happened as followed, e.g., Lacking of the effective method of finding the Web resources. This problem is solved as the birth of the search engines, but there are some other problems and issues needed to be resolved.
For some examples that will be mentioned in this paper: (1) for a short query, it is difficult for search engines to understand what users’ goal of the Web search. As a result, search engines are difficult to provide Web resources that are related to users’ search goal. (2) Without the effective method for helping the users, finds their information need among search engines’ enormous indexes. Therefore, this paper will focus on continuing and improving the previous work about clustering, and also try to study the suitability of pre-deciding that whether the query should be clustered or not, in order to avoid additional overheads both the search engines and users.

中文摘要 I
ABSTRACT II
誌謝 III
TABLE LISTING VI
FIGURE LISTING VII
1. INTRODUCTION 1
2. MOTIVATION 5
3. ISSUES IN THIS PROBLEM 9
　3.1 THE CLUSTER NAME 9
　3.2 THE EVALUATION METHOD 9
　3.3 USING DIVERSE RESULTS OF DIFFERENT SEARCH ENGINES 9
　3.4 CHINESE SEARCHING RESULTS 10
4. RELATED WORK 10
　4.1 OVERALL DESCRIPTION 10
　4.2 DESCRIPTION OF THE PRESENT WEB SEARCH ENVIRONMENT 12
　4.3 OVERALL INTRODUCTION OF PREVIOUS METHODS 13
　　4.3.1 Traditional methods 13
　　4.3.2 Extended version of traditional methods 13
　　4.3.3 Suffix Tree Clustering (STC) 13
　　4.3.4 Clustering under the network environment or present search engine: 14
　4.4 DESCRIPTION OF ZHENG’S METHOD [16] 14
　　4.4.1 Search Result Fetching 15
　　4.4.2 Document Parsing and Phrase Property Calculation 15
　　4.4.3 SVR brief description 18
5. EXPERIMENT 19
　5.1 PRE-CLUSTERING ANALYSIS 19
　　5.1.1 Method description 20
　　5.1.2 Real Cases: 22
　5.2 OUR PROPOSED METHOD 27
　　5.2.1 Description 27
　　5.2.2 Data set 27
　　5.2.3 Description of experiment’s property 29
　　5.2.4 URL structure 30
　　5.2.5 About filtering method of Chinese search 33
　　5.2.6 Combing Results of Multiple Search Engines 33
　　5.2.7 Experiment Result and Discussion 34
　5.3 OUR RESEARCH ON HIERARCHICAL CLUSTER 37
　　5.3.1 Description 37
　　5.3.2 Dataset and Algorithm 37
　　5.3.3 Evaluation 39
6. CONCLUSION AND FUTURE WORK 40
7. REFERENCE: 41

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