Using collaborative filtering to weave an information tapestry
Communications of the ACM - Special issue on information filtering
GroupLens: an open architecture for collaborative filtering of netnews
CSCW '94 Proceedings of the 1994 ACM conference on Computer supported cooperative work
Recommending and evaluating choices in a virtual community of use
CHI '95 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Social information filtering: algorithms for automating “word of mouth”
CHI '95 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
PHOAKS: a system for sharing recommendations
Communications of the ACM
Fab: content-based, collaborative recommendation
Communications of the ACM
Horting hatches an egg: a new graph-theoretic approach to collaborative filtering
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
An algorithmic framework for performing collaborative filtering
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
Authoritative sources in a hyperlinked environment
Proceedings of the ninth annual ACM-SIAM symposium on Discrete algorithms
Combining collaborative filtering with personal agents for better recommendations
AAAI '99/IAAI '99 Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence
Item-based collaborative filtering recommendation algorithms
Proceedings of the 10th international conference on World Wide Web
Proceedings of the 11th international conference on World Wide Web
Eigentaste: A Constant Time Collaborative Filtering Algorithm
Information Retrieval
Learning Collaborative Information Filters
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
Latent Class Models for Collaborative Filtering
IJCAI '99 Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence
Collaborative Filtering by Personality Diagnosis: A Hybrid Memory and Model-Based Approach
UAI '00 Proceedings of the 16th Conference on Uncertainty in Artificial Intelligence
UAI '01 Proceedings of the 17th Conference in Uncertainty in Artificial Intelligence
Content-boosted collaborative filtering for improved recommendations
Eighteenth national conference on Artificial intelligence
ACM Transactions on Information Systems (TOIS)
Item-based top-N recommendation algorithms
ACM Transactions on Information Systems (TOIS)
Unifying collaborative and content-based filtering
ICML '04 Proceedings of the twenty-first international conference on Machine learning
Fast maximum margin matrix factorization for collaborative prediction
ICML '05 Proceedings of the 22nd international conference on Machine learning
Collaborative prediction using ensembles of Maximum Margin Matrix Factorizations
ICML '06 Proceedings of the 23rd international conference on Machine learning
Naïve filterbots for robust cold-start recommendations
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Empirical analysis of predictive algorithms for collaborative filtering
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
Efficient computation of personal aggregate queries on blogs
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Non-linear matrix factorization with Gaussian processes
ICML '09 Proceedings of the 26th Annual International Conference on Machine Learning
Query Recommendations for Interactive Database Exploration
SSDBM 2009 Proceedings of the 21st International Conference on Scientific and Statistical Database Management
Time-Dependent Models in Collaborative Filtering Based Recommender System
WI-IAT '09 Proceedings of the 2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology - Volume 01
Factor in the neighbors: Scalable and accurate collaborative filtering
ACM Transactions on Knowledge Discovery from Data (TKDD)
Prediction of social bookmarking based on a behavior transition model
Proceedings of the 2010 ACM Symposium on Applied Computing
A multimedia recommender integrating object features and user behavior
Multimedia Tools and Applications
From netflix to heart attacks: collaborative filtering in medical datasets
Proceedings of the 1st ACM International Health Informatics Symposium
The decreasing marginal value of evaluation network size
ACM SIGCAS Computers and Society
Kernel-Mapping Recommender system algorithms
Information Sciences: an International Journal
PeerSec: towards peer production and crowdsourcing for enhanced security
HotSec'12 Proceedings of the 7th USENIX conference on Hot Topics in Security
Scalable collaborative filtering using incremental update and local link prediction
Proceedings of the 21st ACM international conference on Information and knowledge management
A probability-based unified framework for semantic search and recommendation
Journal of Information Science
Proceedings of the 23rd international conference on World wide web
| Hi-index | 0.00 |
We propose a new ranking method, which combines recommender systems with information search tools for better search and browsing. Our method uses a collaborative filtering algorithm to generate personal item authorities for each user and combines them with item proximities for better ranking. To demonstrate our approach, we build a prototype movie search and browsing engine called MAD6 (Movies, Actors and Directors; 6 degrees of separation). We conduct offline and online tests of our ranking algorithm. For offline testing, we use Yahoo! Search queries that resulted in a click on a Yahoo! Movies or Internet Movie Database (IMDB) movie URL. Our online test involved 44 Yahoo! employees providing subjective assessments of results quality. In both tests, our ranking methods show significantly better recall and quality than IMDB search and Yahoo! Movies current search.