基於產品比較紀錄的汽車資訊行動APP推薦系統之研究

A Study of Car Information Mobile APP Recommender System based on Product Comparing Records

10.6495/CIMBM.2015.003

吳芳綾(Fang-Lin Wu)；劉秀雯(Hsiu-Wen Liu)

推薦系統 ； 資料探勘 ； 關聯規則 ； Recommendation system ； Data Mining ； Association Rules

科際整合管理研討會

2015第18屆（2015 / 06 / 07）

40 - 49

繁體中文

隨著行動裝置及應用程式使用率的增加，使得人們的生活習慣也有所改變。為了因應市場趨勢，許多企業紛紛加入開發應用程式的行列。目前市面上已經有許多產品資訊搜尋的應用程式已經被開發出來（例如：飯店、旅遊、汽車等等）。儘管這類型的應用程式可提供消費者豐富的產品訊息，但是若缺乏一套好的關聯性產品推薦系統，使用者還是很難從APP的使用中獲得最大的益處。本研究即以此為出發點，透過使用者將產品兩兩比較的瀏覽記錄，透過關聯規則分析，建立一套針對汽車產品資訊的行動APP推薦系統。

People's life and habits have changed with the increasing usage of mobile devices and applications. In response to this market trends, many companies have joined the development of apps. Several apps have been developed that allow users to search product information. This kind of apps can improve user's experience if they can provide recommendations. In this study, we use the behavior information of product comparing records from a car app to create car recommendation system. The association rule analysis was adopted as the miming method. Through the empirical analysis, we develop recommendation rules for car information app. The conclusions and managerial implications will also be discussed.