利用關聯規則建構查詢關鍵字之網站推薦

Using Association Rules to Construct Website Recommendations of Query Keywords

網站搜尋引擎是電子商務經營模式中最受歡迎的服務之一，本研究以搜尋引擎中查詢關鍵字與點選網站做為探勘的資料來源，利用關聯規則(association rules)從以下兩方面找出查詢關鍵字適性化的網站推薦：一是提出一個快速探勘查詢關鍵字，與點選網站之間關聯規則的演算法；二是以某查詢關鍵字為探勘目標，文中修改前面的演算法，探勘前置項目組為此查詢關鍵字之關聯規則。藉由以上關聯規則所顯示出的點選傾向特徵，當搜尋引擎中輸入關鍵字搜尋網站時，可依據以上關聯規則的信賴度，提供其適性化的網站推薦及排名順序。文中根據所提出的兩個演算法，設計與建置一個查詢關鍵字適性化的網站推薦系統，並實驗評估所提出之演算法的執行效能。

The website search engine is one of the most popular services in electronic commerce business models. This paper uses browsing data as the source data of mining， and a browsing data contains query keywords and browse websites in search engine. The association rule is used to find the adaptive website recommendations of query keywords from two aspects. One is to propose a fast algorithm to mine association rules betweenquery keywords and browse websites. The other is to use some query keywords as the target of mining， and to modify the previous algorithm to mine association rules as those antecedents are the query keywords. The adaptive website recommendations with rank by the confidence of the association rules can be provided for the query keywords in searchengine. A mining system for adaptive website recommendations of query keywords is designed and constructed according to both algorithms， and the performances of both algorithms are evaluated.