博碩士論文 945202033 完整後設資料紀錄

DC 欄位 語言
DC.contributor資訊工程學系zh_TW
DC.creator施宗昆zh_TW
DC.creatorTsung-Kun Shihen_US
dc.date.accessioned2007-10-11T07:39:07Z
dc.date.available2007-10-11T07:39:07Z
dc.date.issued2007
dc.identifier.urihttp://ir.lib.ncu.edu.tw:88/thesis/view_etd.asp?URN=945202033
dc.contributor.department資訊工程學系zh_TW
DC.description國立中央大學zh_TW
DC.descriptionNational Central Universityen_US
dc.description.abstract現今在網路上最主要的活動就是資訊的搜尋,雖然目前的搜尋引擎已經相當的好用了,但是它們仍然有些缺點需要去改進。很多人們的資訊需求是很難用關鍵字為基礎的查詢,就能得到正確的回傳結果,所以在本篇論文裡,我們建立一個名為隱藏式的馬可夫模型,來預測最有可能的網頁路徑,進而達到蒐集特定資訊的目的,而在實驗結果方面也顯示了我們的系統改善了一些搜尋引擎所面臨的一些缺點。zh_TW
dc.description.abstractInformation search is the key activity for many users on the Web. Although search engines are very useful and powerful nowadays, there are also many drawbacks faced by them. Moreover, many information needs are hard to express using keyword-based queries. In this paper, we apply a method to solve composite information needs by building a Hidden Markov Model (HMM) for predicting the most likely path to the target information. We want to use the concept of the focused crawling to trace down a Web site for specific information. The experiment shows that the results is good for the admission information and the accepted papers.en_US
DC.subject馬可夫鏈zh_TW
DC.subject資訊蒐集zh_TW
DC.subjectHMMen_US
DC.subjectInformation Gatheringen_US
DC.title使用隱藏式馬可夫模型之特定網頁資訊抓取蒐集zh_TW
dc.language.isozh-TWzh-TW
DC.titleFocused Crawling for Information Gathering Using Hidden Markov Modelen_US
DC.type博碩士論文zh_TW
DC.typethesisen_US
DC.publisherNational Central Universityen_US

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