本文選題：個性化查詢詞補全 + 時間敏感分析�。� 參考：《北京林業(yè)大學》2015年碩士論文

【摘要】：當今互聯(lián)網(wǎng)信息紛繁復(fù)雜,搜索引擎為互聯(lián)網(wǎng)用戶提供了良好的信息搜索體驗。而搜索引擎的查詢詞補全技術(shù)又進一步提高了搜索引擎質(zhì)量,為用戶提供了更優(yōu)質(zhì)的搜索服務(wù)。目前查詢詞補全技術(shù)廣泛應(yīng)用于各搜索引擎,但大多依賴群體智慧策略。針對用戶檢索需求隨時間變化而不同這一問題,時間敏感查詢詞自動補全技術(shù)越來越成為研究熱點。時間敏感查詢詞補全在生成查詢詞補全候選列表時擬合多種時間因素,呈現(xiàn)出與傳統(tǒng)查詢詞補全不同的特點。本文針對查詢詞自動補全技術(shù)非個性化及時間敏感化的問題,提出了一個方法“個性化時間敏感查詢詞補全”來推薦時間敏感的個性化查詢。首先,將用戶所有桌面操作行為數(shù)據(jù)組織建立索引,并存儲于用戶個人計算機中；其次,用貝葉斯公式描述用戶需求和時間的關(guān)聯(lián),并應(yīng)用時間序列預(yù)測模型計算時間敏感值；最后,根據(jù)時間敏感權(quán)值對所有補全候選詞進行排序。通過最終的在真實數(shù)據(jù)集上的實驗結(jié)果對比證明,論文模型可以用于加強信息檢索,特別是查詢詞補全推薦相關(guān)領(lǐng)域算法。
[Abstract]:Nowadays, Internet information is complicated, search engine provides good information search experience for Internet users. Search engine query word complement technology further improves the search engine quality and provides users with better search services. At present, query word complement technology is widely used in various search engines, but mostly rely on group intelligence strategy. In order to solve the problem that users' retrieval requirements vary with time, the automatic completion of time-sensitive query terms has become a hot research topic. Time-sensitive query word complement is different from traditional query word complement because of fitting various time factors when generating query word complement candidate list. Aiming at the problem of non-personalization and time sensitivity of automatic completion of query words, this paper proposes a method of "personalized time-sensitive query word complement" to recommend time-sensitive personalized query. First of all, the data of user's desktop operation behavior are organized and indexed, and stored in the user's personal computer. Secondly, Bayesian formula is used to describe the relationship between user's demand and time, and time sensitive value is calculated by using time series prediction model. Finally, all the complement candidate words are sorted according to the time sensitive weights. The experimental results on the real data set show that the model can be used to enhance information retrieval, especially the algorithm of complete recommendation of query words.
【學位授予單位】：北京林業(yè)大學
【學位級別】：碩士
【學位授予年份】：2015
【分類號】：TP391.3

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相關(guān)碩士學位論文 前1條

1 張驍;基于時間敏感的個性化查詢詞補全算法研究[D];北京林業(yè)大學;2015年

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本文編號：1944089