Web Recommendation System Analysis the recommendation system will never recommend anything to you

don’t think you can sneak up on Taobao to see erotic things. Everything you do on the web can’t escape the eyes of the system. In order to guess your thoughts, your recommendation algorithm might need as much data acquisition, so as to determine what you really love. Of course, it’s still to win your trust and make online retailers make more money.


source: yoochoose.com

(A. Konstan & John /Joseph; Riedl) finished the recommendation algorithm is how to "guess you love", now, for you every time when shopping online online retailers is how to look at you, and try to put your preferences and other matching have a basic concept.

recommendation system and two other characteristics, also to you finally see the recommended results have significant effects: first, the clear similarity to you and other shoppers are high before the recommendation system must first understand what you really love; second, according to a group of business recommender system operation rules to ensure that the recommended results not only make you feel useful, also make the business profitable.

recommendation algorithm is how to win your trust, but also allow businesses to earn money,


collects your online data

, for example, look at Amazon’s art shop. When we went to see it last time, there were about 9000000 volumes of printed matter and posters on sale. Amazon’s art store has several ways to evaluate your preferences. It will allow you to a piece of art scoring 1 to 5 stars level, it will record your view, click to enlarge the picture which you draw which repeatedly read many times, what you put into the list, and you actually bought what orders. It also tracks what paintings are displayed on every page you’ve browsed. Online retailers use the path you visit on your website (the page you browsed and click on the link to the product) to recommend the related items to you. In addition, it combines your purchase record with your scoring information to create a profile of your long-term purchase preference.

, a company like Amazon, collects a large amount of such data about its customers. During your login period, almost every action you have on its website will be written down for future use. Thanks to browser cookie, businesses can maintain online records of anonymous shoppers, and eventually the data will be linked to customer profiles when anonymous shoppers create accounts or log on. This explosion of data acquisition is not unique to online merchants, and WAL-MART is known for its deep mining of cash receipts. But online stores are in a better position to view and record, not just what consumers buy, but also packs


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