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Social Media Recommender System (Social Media Domains (Digital Library (e…
Social Media
Recommender System
Recommendation Approaches
Content-based Filtering (CB)
Collaborative Filtering (CF)
User-based
Item-based
Memory-based
Model-based
Hybrid-based Filtering (HB)
Knowledge-based Filtering (KB)
Social Media Domains
Digital Library
e.g. Google Scholars
Research paper recommendation
Relevance between research paper with search query and interest
Forums
e.g. Stack Overflow
Expert and post recommendation
E-Commerce
e.g. Amazon
Product recommendation
Real-time recommendations, where user's preference continue to change
Entertaiment
e.g. Netflix
Movie recommendation
Blog/Microblog
e.g. Twitter
Similar blog recommendation
Geo Location
e.g. Foursquare
Social Review
e.g. Epinions
Social Networks
e.g. Facebook
Friend / Connection recommendation
Dataset
Social Review
Epinions Dataset
Entertaiment
MovieLens
IMDB
Forum
Stackoverflow Dataset
Data Mining Technique
CB
Bayesian Network
Logistic Regression
CF
*Clustering
*KNN
*Matrix Factorization
Link Analysis
Decision Tree
Association Rule
HB
Clustering
KNN
Matrix Factorization
Fuzzy
Social data extractor
User activities
User information
Recommendation Type
Classical
Item-User
User-User
*User-Item
Implicit
Explicit
User-Tag
Contextual
User-Tag-Item
User-Item-Tag
Performance Metrics
Precision
Recall
Accuracy
MAE
Time and Space
Requirement
Based on 61 Research Paper
(2011 - 2015)