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Mining typical preferences of collaborative user groups
Su Jeong Ko,
Jiawei Han
Information Trust Institute
Carl R. Woese Institute for Genomic Biology
Siebel School of Computing and Data Science
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Keyphrases
User Groups
100%
User Preference
100%
Collaborative Users
100%
Association Word
100%
Sparsity
66%
Feature Extraction Methods
66%
Correlation Degree
66%
Typical User
66%
Similar Users
66%
Collaborative Filtering Systems
66%
Feature Space
33%
Learning Algorithm
33%
Modeling Algorithm
33%
Customer Preference
33%
Noun Phrase
33%
Mining Method
33%
Automatically Generate
33%
System Issues
33%
Vector Space Model
33%
Preference Rating
33%
Data User
33%
Single-dimension
33%
Text Collection
33%
Apriori Algorithm
33%
K-means Algorithm
33%
Unique Word
33%
Weighted Words
33%
Computer Science
User Preference
100%
Word Association
100%
Sparsity
66%
Feature Extraction
66%
collaborative filtering algorithm
66%
Feature Space
33%
User Data
33%
Customer Preference
33%
Learning Algorithm
33%
Vector Space Models
33%
Text Collection
33%
apriori algorithm
33%