Title
Semantically Enriched Recommender Engine: A Novel Collaborative Filtering Approach Using "User-to-User Fast Xor Bit Operation"
Abstract
In this paper, we focus on Collaborative Filtering to provide recommendations to users that fit their profiles. We employed two methods: (1) K-Nearest Neighbors classifier, and (2) a fast implementation of Collaborative Filtering approach: “user-to-user fast XOR bit operation”. Both techniques serve the same objective, which is modifying the user's ontology profile (semantic profile). Technically, Collaborative Filtering extends the user's ontology profile based on the interests of a community of similar users. Also, we describe the implementation of the recommender system on a real platform, known as Hyper Many Media at Western Kentucky University. Finally, we evaluate the system based on Top-n-Recall and Top-n-Precision. The results show an improvement in Recall and Precsion using Collaborative Filtering.
Year
DOI
Venue
2010
10.1109/ICSC.2010.80
ICSC
Keywords
Field
DocType
groupware,information filtering,ontologies (artificial intelligence),recommender systems,K-nearest neighbor classifier,Top-n-Precision,Top-n-Recall,collaborative filtering,recommender engine,user-to-user fast XOR bit operation,Collaborative Filtering,Information Retrieval,Recommender Search Engine,Semantic Web
Recommender system,Ontology,Data mining,Collaborative filtering,Information retrieval,Bitwise operation,Collaborative software,Computer science,Semantic Web,Boosting (machine learning),Information filtering system
Conference
ISSN
Citations 
PageRank 
2325-6516
2
0.53
References 
Authors
9
3
Name
Order
Citations
PageRank
Leyla Zhuhadar114617.53
Olfa Nasraoui21515164.53
Robert Wyatt3101.20