整合信任網路與回饋機制之個人化餐廳推薦系統

A Personalized Restaurant Recommender System with the Integration of Trust Network and Feedback Mechanism

本研究建置一個以整合信任網路與回饋機制之個人化餐廳推薦系統，改善推薦結果的正確性。在信任網路機制中，透過信任推演和節點配適的輔助，增加搜尋到符合使用者需求資訊的機率。回饋機制則利用使用者瀏覽行為作為回饋機制的基礎，用以輔助評價結果的精確度及協助修正信任網路。本研究以美食餐廳推薦為例，透過使用者個人的信任網路和瀏覽行為，去推演符合使用者喜好的美食餐廳，讓推薦結果可以更符合個人化，幫助使用者找尋符合需求的美食餐廳。

In this paper, a recommender system was built for a personalized restaurant recommendation by the integration of trust networks and feedback mechanisms to improve the correctness of the recommended results. In trust network mechanisms, with the support of the trust deductions and the node matching, the system can greatly increase the chances of the search result to meet users' needs. In Feedback mechanisms, with the basis of user browsing behavior for a feedback mechanism, the accuracy of the recommendation results can be improved and the precision of the trust network value can be adjusted for users' preferences. A restaurant recommender system has been implemented to support the personalized restaurant recommendation in this study. With the support of personal trust networks and users' browsing behavior, the recommended results can match personalized demands and help users find the more appropriate restaurant for the needs.