1、隨著Internet的不斷發(fā)展,網(wǎng)上的信息極度膨脹,網(wǎng)絡(luò)用戶越來(lái)越難以從信息海洋中快速有效的查找到所需要的信息.為了解決這一難題,要求人們?cè)贗nternet這樣一個(gè)動(dòng)態(tài)變化的環(huán)境下對(duì)信息進(jìn)行收集、分析、分類、評(píng)價(jià)以提供有效的信息服務(wù).本文以網(wǎng)頁(yè)文本信息為研究對(duì)象,針對(duì)網(wǎng)頁(yè)信息內(nèi)容多樣、結(jié)構(gòu)復(fù)雜的特點(diǎn),從理論和應(yīng)用兩個(gè)角度對(duì)網(wǎng)頁(yè)文本信息的分類方法和自動(dòng)摘要做了深入研究.運(yùn)用正向最大和逆向最大分詞算法對(duì)網(wǎng)頁(yè)提取的文本信息進(jìn)行分詞,使用K-m
2、eans聚類算法,Bayers分類算法對(duì)信息進(jìn)行分類,設(shè)計(jì)并實(shí)現(xiàn)了適合于新聞網(wǎng)頁(yè)信息的自動(dòng)分類器.詳細(xì)分析了主題詞的結(jié)構(gòu)成分,并對(duì)所有超文本標(biāo)記進(jìn)行分析,將
等九個(gè)重要的標(biāo)記在進(jìn)行主題詞評(píng)價(jià)的時(shí)候被分配更大的權(quán)重,設(shè)計(jì)了主題詞權(quán)重系數(shù)公式,結(jié)合句子位置信息計(jì)算句子得分、根據(jù)句子得分利用LUHN和LSA算法進(jìn)行摘要提取,最終設(shè)計(jì)并實(shí)現(xiàn)了一套Web自動(dòng)文本摘要原型系統(tǒng).經(jīng)實(shí)驗(yàn)表明,改進(jìn)了主題詞評(píng)價(jià)標(biāo)準(zhǔn)后,利用LUHN、LSA算法</p> </div> </div> <div id="vrlthxf" class="main-nav"> <a href="/" title="眾賞文庫(kù)" class="themeHoverColor0">眾賞文庫(kù)</a><span id="vpnnbzp" class="arrow">></span> <a href="/c-0.html" title="全部分類" class="themeHoverColor0">全部分類</a><span id="xtxfxth" class="arrow">></span> <a href="/c-00001000100000100001.html" title="畢業(yè)設(shè)計(jì)" class="themeHoverColor0 ">畢業(yè)設(shè)計(jì)</a> </div> <div id="znhrvjh" class="intro-wrap"> <h4>溫馨提示</h4> <ul> <li>1. 本站所有資源如無(wú)特殊說(shuō)明，都需要本地電腦安裝OFFICE2007和PDF閱讀器。圖紙軟件為CAD,CAXA,PROE,UG,SolidWorks等.壓縮文件請(qǐng)下載最新的WinRAR軟件解壓。</li> <li>2. 本站的文檔不包含任何第三方提供的附件圖紙等，如果需要附件，請(qǐng)聯(lián)系上傳者。文件的所有權(quán)益歸上傳用戶所有。</li> <li>3. 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