Product Recommendation with Hot Queries and Hidden Events

論文翻譯標題: 利用熱門搜索及其隱含事件推薦商品
  • 洪 千越

學生論文: Master's Thesis


In recent years with the rapid development and increasing popularity of the Internet the web has become part of people’s lives Since the convenience of web more and more people tend to make online purchases At the same time the competition among online stores has gradually increased In such a competitive situation online retailers usually offer various consumption discounts for customers to attract people to visit their online shopping malls In addition to catching people’s eyes by offering the best price to customers the ad service from search engines is another great way for online shopping malls to meet the people with certain needs However we have noticed that when a user search a hot query they may need some products Surprisingly search engines may not offer any product recommendation ads This situation causes the loss of profit to both search engines and online retailers In this work we find out the hidden event behind the hot query Then we inference the products which users might be interested in and recommend them to users Our Query-Event-based Hot Product Recommendation (QEHPR) model contains three stages The model first find out the hidden event behind a hot query Since not all events are proper in recommending products such as the event “cabinet reshuffle” we identify events that are suitable for our model to recommend products Second we discover different kinds of event needs from the consumption events we have collected Finally we recommend products based on the event needs for the given hot query
獎項日期2016 八月 9
監督員Wen-Hsiang Lu (Supervisor)