Using Shared Rare Attributes for Interest-based Friends Recommendation in Social Matching Systems
| Autor: | Shen, Yi-Cong, 沈奕聰 |
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| Rok vydání: | 2016 |
| Druh dokumentu: | 學位論文 ; thesis |
| Popis: | 105 Friend recommendation is one of the important applications of socialization website. A friend referral system helps users find people they are interested in. However, when a buddy recommendation is made to a new user, there is no record of the user's existing friends and users, a personalized recommendation for a new user is recommended, and the user is satisfied with the recommendation result, and is willing to continue using the system. Must provide an efficient, effective process, to give new users to express their preferences and preferences. The traditional way of capturing user preferences is to allow users to rate a group of popular items. However, there are user research that, for the common characteristics of a small minority, like the kind of user is usually more interested. Based on the findings of this user study, we designed a system using a small minority hobby buddy recommended to do, want to verify, to the user to do a friend recommendation, attention to small hobbies, get the recommendation results will allow users more satisfied. In the experiment, the use of minority characteristics of the system, compared with the traditional way of the system, and achieved better results, higher user satisfaction, the experiment there are many interesting discoveries, you can recommend to the design of friends System of people to provide reference. Due to the limited number of subjects allowed to rate the movie, similar to the cold start scenario, a cold start related technique was applied. This buddy recommendation system can also be applied to cold start problems. |
| Databáze: | Networked Digital Library of Theses & Dissertations |
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