Social information filtering
Социальная фильтрация информации
1995-01-01
SCID: 54.1/vgna9geb
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Ringomusic recommendationpersonalized recommendationssocial information filteringuser interest profiles
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Abstract (AI)
This paper describes a technique for making personalized recommendations from any type of database to a user based on similarities between the interest profile of that user and those of other users.In particular, we discuss the implementation of a networked system called Ringo, which makes personalized recommendations for music albums and artists.Ringo's database of users and artists grows dynamically as more people use the system and enter more information.Four different algorithms for making recommendations by using social information filtering were tested and compared.We present quantitative and qualitative results obtained from the use of Ringo by more than 2000 people.
Key Findings
1
Four social-information-filtering recommendation algorithms were tested and compared.
2
Quantitative and qualitative results were collected from Ringo’s use by more than 2,000 people.
3
Ringo implements this approach for personalized recommendations of music albums and artists in a networked system.
4
Ringo’s user and artist database expands dynamically as participants join and contribute information.
5
The paper introduces social information filtering, recommending database items by matching a user’s interest profile with those of similar users.
Research Object
Ringo networked system for personalized music recommendations, including its dynamically growing database of users, music albums, and artists
Research Subject
Personalized recommendation performance based on similarities between users’ interest profiles, including comparison of four social information filtering algorithms
Publication Details
Publication Date
1995-01-01
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