【摘要】：深度萬(wàn)維網(wǎng)蘊(yùn)藏著海量的信息,由于其隱藏性,現(xiàn)有的搜索引擎很難搜索到其中的內(nèi)容。目前還沒(méi)有研究出很好的方法和模型來(lái)捕獲其內(nèi)容,很大程度上制約了人們獲取更多、更有價(jià)值的信息,因此如何充分的獲取深度萬(wàn)維網(wǎng)中的信息成為了一個(gè)難題。 本文提出了基于關(guān)鍵詞的深度萬(wàn)維網(wǎng)的數(shù)據(jù)庫(kù)的查詢方法,該方法在考慮了深度萬(wàn)維網(wǎng)自身特點(diǎn)的基礎(chǔ)上,又借鑒了傳統(tǒng)的搜索引擎思想。文章比較了各種分類算法,最終采用樸素貝葉斯算法對(duì)關(guān)鍵詞進(jìn)行分類,找到其所屬的領(lǐng)域,該算法適合深度萬(wàn)維網(wǎng)查詢模型,簡(jiǎn)單明了,準(zhǔn)確性也很高。關(guān)鍵詞與屬性關(guān)聯(lián)引入了本體的概念,利用WordNet詞典生成的概念層次樹(shù),提出了基于本體的語(yǔ)義相似度計(jì)算方法。該方法擺脫了人們的主觀意識(shí),簡(jiǎn)單而直觀,代價(jià)也不是很大。確定了查詢關(guān)鍵詞所屬的領(lǐng)域和其所對(duì)應(yīng)的關(guān)系表中的屬性后,最終生成查詢的SQL語(yǔ)句,把查詢的頁(yè)面信息反饋給用戶。 實(shí)驗(yàn)部分也舉例驗(yàn)證和測(cè)試了所提出的方法的可行性與準(zhǔn)確性,不僅解決了深度萬(wàn)維網(wǎng)多領(lǐng)域的數(shù)據(jù)庫(kù)查詢,而且能夠與現(xiàn)有的搜索引擎進(jìn)行整合,幫助用戶快速有效的查詢。
[Abstract]:The deep World wide Web contains a great deal of information. Because of its concealment, it is difficult for the existing search engines to search for the contents. At present, there is no good method and model to capture its content, which restricts people to obtain more and more valuable information, so how to obtain the information in the depth of the World wide Web has become a difficult problem. In this paper, a query method of the database based on the keyword depth World wide Web is proposed. This method not only takes into account the characteristics of the depth World wide Web, but also draws lessons from the traditional search engine idea. This paper compares various classification algorithms, and finally classifies keywords by naive Bayes algorithm, and finds its domain. The algorithm is suitable for deep World wide Web query model, simple and clear, and has high accuracy. The concept of ontology is introduced by associating keywords with attributes, and the semantic similarity calculation method based on ontology is proposed by using the concept hierarchy tree generated by WordNet dictionary. This method gets rid of people's subjective consciousness, simple and intuitionistic, and the cost is not very big. After determining the domain to which the query keywords belong and the attributes in the corresponding relational table, the SQL statement of the query is generated, and the page information of the query is fed back to the user. The experiment also verifies and tests the feasibility and accuracy of the proposed method, which not only solves the database query of deep World wide Web, but also integrates with the existing search engine to help users to query quickly and effectively.
【學(xué)位授予單位】：上海師范大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2013
【分類號(hào)】：TP391.1;TP311.13

【參考文獻(xiàn)】

相關(guān)期刊論文 前9條

1 姚全珠;彭程;宋志理;李薇;;基于關(guān)聯(lián)規(guī)則的搜索引擎方法[J];計(jì)算機(jī)工程與應(yīng)用;2011年09期

2 劉偉;孟小峰;孟衛(wèi)一;;Deep Web數(shù)據(jù)集成研究綜述[J];計(jì)算機(jī)學(xué)報(bào);2007年09期

3 劉玉奎;周立柱;范舉;;中文深度萬(wàn)維網(wǎng)數(shù)據(jù)庫(kù)的現(xiàn)狀研究[J];計(jì)算機(jī)學(xué)報(bào);2011年02期

4 范舉;周立柱;;基于關(guān)鍵詞的深度萬(wàn)維網(wǎng)數(shù)據(jù)庫(kù)選擇[J];計(jì)算機(jī)學(xué)報(bào);2011年10期

5 姜芳艽;孟小峰;;Deep Web數(shù)據(jù)集成中查詢處理的研究與進(jìn)展[J];計(jì)算機(jī)科學(xué)與探索;2009年02期

6 林玲;周立柱;;基于簡(jiǎn)單查詢接口的Web數(shù)據(jù)庫(kù)模式識(shí)別[J];清華大學(xué)學(xué)報(bào)(自然科學(xué)版);2010年04期

7 田萱;杜小勇;李海華;;語(yǔ)義查詢擴(kuò)展中詞語(yǔ)-概念相關(guān)度的計(jì)算[J];軟件學(xué)報(bào);2008年08期

8 趙志宏;黃蕾;劉峰;陳振宇;;Deep Web搜索技術(shù)進(jìn)展綜述[J];山東大學(xué)學(xué)報(bào)(工學(xué)版);2009年02期

9 趙朋朋;崔志明;高嶺;仲華;;關(guān)于中國(guó)Deep Web的規(guī)模、分布和結(jié)構(gòu)[J];小型微型計(jì)算機(jī)系統(tǒng);2007年10期

，

本文編號(hào)：2168489