基於全球資訊網之協同式搜尋

身處於資訊爆炸的時代，想要在浩瀚的網海中搜尋到真正所需的資料，變得越來越不容易，在如此大量的資料海中，使用者往往會因為自己的知識領域偏狹於某個部分，搜尋時會遺漏掉某些自己想要但不熟悉的資料，亦或是對某個領域認知不足，不知道如何開始進行搜尋該領域的資料，此時，如果能夠在搜尋的過程中，請過去有搜尋過相關領域的經驗者協助，似乎會有助於我們解決所面臨到的問題。　　於是，我們想建立一個基於全球資訊網路上的協同式搜尋系統，架構於現有的網路搜尋引擎上，將每個使用者查詢結果的snippet斷詞後，當作為自己的query profile，當使用者搜尋某個關鍵字時，系統依照重要性、相關性及新穎性，會自動推薦與其相似的query profile內之關鍵字當作query，期望能夠幫助使用者加強在全球資訊網上的搜尋效能。最後我們設計三個實驗，分別針對查詢的效能、推薦字的新穎性及推薦字的相關性來進行驗證及比較，並討論我們方法的優點及未來可精進之處。

關鍵字

協同式搜尋；查詢推薦；搜尋

並列摘要

In the era of information explosion,it becomes more and more difficult to find out the information meeting users’ real needs on the internet.On account of their own limited domain knowledge,users may often overlook the information that they are not familiar with,but need.Users,as a result of insufficient knowledge of some field,may not have any idea how to start searching information,too.Such problems might be solved more easily,as those who have had already experience if searching information in the internet could help users. 　　A collaborative search system based on the internet would be designed.This collaborative search system,working together with the present search engine,will segment the snippet of search results and take the segmentation for its own query prefile.When users query,the system will also automatically suggest the terms of similar query profile as queries,according to importance,relevance and novelty.The efficiency of searching on the internet could hopefully become better in this way. 　　Finally,there are three experiments designed to examine and evaluate query precision,the novelty and relevance of recommended terms.The strong points and possible improvement of this method will be discussed,too.

並列關鍵字

IR ； Collaborative search ； query suggestion

參考文獻

[3] SHAHABI, C. AND CHEN, Y. S. 2003. Web information personalization: Challenges and approaches.In Proceedings of Databases in Networked Information Systems. 5–15.

[7] Kalervo Jarvelin, Jaana Kekalainen: Cumulated gain-based evaluation of IR techniques. ACM Transactions on Information Systems 20(4), 422–446 (2002).

[8] Barry Smyth, Evelyn Balfe, Peter Briggs, Maurice Coyle, Jill Freyne (2003), "Collaborative Web Search", IJCAI: 1417–1419.

[9] D. Goldberg, D. Nichols, B. M. Oki, and D. Terry, “Using collaborative filtering to weave an information tapestry,” Communications of ACM, vol. 35, no. 12, pp. 61–70, 1992.

[12] Huizhi Liang;Yue Xu;Yuefeng Li;Nayak, R.: Collaborative Filtering Recommender Systems Using Tag Information.Web Intelligence and Intelligent Agent Technology IEEE 2008

國際替代計量

基於全球資訊網之協同式搜尋

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