【摘要】：“以用戶為中心”是電子商務網站取得成功的前提,而電子商務網站中有80%的用戶傾向于使用分類目錄,分類目錄已經成為用戶進行信息獲取的重要途徑之一。此外考慮到用戶需求、興趣等個性化的差異,大量的電子商務網站都引入了“個性化推薦”的功能,其實質為將最符合用戶知識結構的分類目錄推薦給用戶�？梢姺诸惸夸浭请娮由虅站W站的重要組成部分,因此從目錄體系的設計到基于目錄的個性化推薦都應做到“以用戶為中心”,這就需要解決以下三個問題：如何獲取用戶關于網站分類目錄的認知、如何在網站分類目錄設計中體現(xiàn)用戶認知、如何結合分類目錄基于用戶認知實施個性化推薦。 本研究針對這三個關鍵問題,探索新的用戶研究方法,直接利用客觀體現(xiàn)用戶心智模型的網站日志數據,從中提取用戶關于網站分類目錄的認知,從用戶心智模型概念相似性出發(fā),基于聚類分析與路徑搜索法,分析用戶內心期望的分類目錄體系與網站分類目錄體系間的關系,進而為構建更符合用戶心智模型的網站分類目錄體系提供決策支持；從用戶心智模型概念空間性出發(fā),借鑒協(xié)同過濾和基于內容推薦算法的思想,應用聚類分析與多維尺度法,基于網絡日志分類用戶,挖掘三級目錄之間的相關性以給用戶個性化推薦相關產品主題(即最相關的三級目錄),嘗試給用戶帶來良好的個性化推薦使用體驗,從而為電子商務網站留住更多的用戶。
[Abstract]:"User centered" is the prerequisite for the success of e-commerce websites, and 80% of users in e-commerce websites tend to use classified catalogues. Classified catalogues have become one of the most important ways for users to obtain information. In addition, a large number of e-commerce websites have been introduced into account of user needs, interest and other personalized differences. The function of "personalized recommendation" is actually to recommend the classified catalogues that are most consistent with the user's knowledge structure. It is obvious that the classified catalogue is an important part of the e-commerce website. Therefore, from the design of the directory system to the personalized recommendation based on the directory, it should be "centered on the user", which needs to solve the following three questions. Question: how to obtain the user's cognition about the classified catalogue of the website, how to embody the user's cognition in the design of the website cataloging, and how to implement the personalized recommendation based on the user cognition in the classified catalogue.
This study aims at these three key problems, exploring new user research methods, using the web log data that objectively embodies the mental model of the user, extracting the users' cognition on the classified catalogue of the web site, starting with the similarity of the mental model of the user, based on the clustering analysis and the path search method, to analyze the classification of the users' inner expectations. The relationship between the catalog system and the web classified catalog system, and then to provide decision support for building a web catalog system that is more consistent with the user mental model. Based on the concept of user mental model, the ideas of collaborative filtering and content based recommendation algorithm are used for reference, and the clustering analysis and multidimensional scale method are applied to the network log classification. Class users, mining the correlation between the three levels of directory to personalize the users to recommend related product topics (the most relevant three levels of directory), and try to give users a good personalized recommendation and use experience, so as to retain more users for e-commerce sites.
【學位授予單位】：南京理工大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：TP393.092

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