Using collaborative filtering to weave an information tapestry
Communications of the ACM - Special issue on information filtering
Learning in the presence of concept drift and hidden contexts
Machine Learning
Item-based collaborative filtering recommendation algorithms
Proceedings of the 10th international conference on World Wide Web
Amazon.com Recommendations: Item-to-Item Collaborative Filtering
IEEE Internet Computing
Dynamic Weighted Majority: A New Ensemble Method for Tracking Concept Drift
ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
Adaptive web search based on user profile constructed without any effort from users
Proceedings of the 13th international conference on World Wide Web
TiVo: making show recommendations using a distributed collaborative filtering architecture
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Time weight collaborative filtering
Proceedings of the 14th ACM international conference on Information and knowledge management
Major components of the gravity recommendation system
ACM SIGKDD Explorations Newsletter - Special issue on visual analytics
Factorization meets the neighborhood: a multifaceted collaborative filtering model
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Scalable Collaborative Filtering with Jointly Derived Neighborhood Interpolation Weights
ICDM '07 Proceedings of the 2007 Seventh IEEE International Conference on Data Mining
Proceedings of the 2008 ACM conference on Recommender systems
ACM Conference on Recommender Systems
Collaborative filtering with temporal dynamics
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Improved neighborhood-based algorithms for large-scale recommender systems
Proceedings of the 2nd KDD Workshop on Large-Scale Recommender Systems and the Netflix Prize Competition
Creating the experience economy in e-commerce
Communications of the ACM
Predicting most rated items in Weekly Recommendation with temporal regression
Proceedings of the Workshop on Context-Aware Movie Recommendation
ACACOS'11 Proceedings of the 10th WSEAS international conference on Applied computer and applied computational science
User reputation in a comment rating environment
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
A case study in a recommender system based on purchase data
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
Making use of associative classifiers in order to alleviate typical drawbacks in recommender systems
Expert Systems with Applications: An International Journal
Improving k-nearest neighbors algorithms: practical application of dataset analysis
Proceedings of the 20th ACM international conference on Information and knowledge management
Mining relational context-aware graph for rater identification
Proceedings of the 2nd Challenge on Context-Aware Movie Recommendation
Semi-sparse algorithm based on multi-layer optimization for recommendation system
Proceedings of the 2012 International Workshop on Programming Models and Applications for Multicores and Manycores
Pushing the boundaries of crowd-enabled databases with query-driven schema expansion
Proceedings of the VLDB Endowment
A literature review and classification of recommender systems research
Expert Systems with Applications: An International Journal
Collaborative Filtering Recommender Systems
Foundations and Trends in Human-Computer Interaction
A recommendation model for handling dynamics in user profile
ICDCIT'12 Proceedings of the 8th international conference on Distributed Computing and Internet Technology
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Product recommendation with temporal dynamics
Expert Systems with Applications: An International Journal
Context-aware prediction of user's first click
Proceedings of the 1st International Workshop on Context Discovery and Data Mining
Proceedings of the second international ACM workshop on Music information retrieval with user-centered and multimodal strategies
Top-N recommendation through belief propagation
Proceedings of the 21st ACM international conference on Information and knowledge management
A hybrid recommendation approach for a tourism system
Expert Systems with Applications: An International Journal
A hidden Markov model for collaborative filtering
MIS Quarterly
Scalable all-pairs similarity search in metric spaces
Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining
Measuring spontaneous devaluations in user preferences
Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining
Towards a robust modeling of temporal interest change patterns for behavioral targeting
Proceedings of the 22nd international conference on World Wide Web
From amateurs to connoisseurs: modeling the evolution of user expertise through online reviews
Proceedings of the 22nd international conference on World Wide Web
Understanding temporal dynamics of ratings in the book recommendation scenario
Proceedings of the 2013 International Conference on Information Systems and Design of Communication
Context-aware review helpfulness rating prediction
Proceedings of the 7th ACM conference on Recommender systems
A people-to-people content-based reciprocal recommender using hidden markov models
Proceedings of the 7th ACM conference on Recommender systems
Music recommendations for groups of users
Proceedings of the 2013 ACM international workshop on Immersive media experiences
A survey on concept drift adaptation
ACM Computing Surveys (CSUR)
Mining user interest and its evolution for recommendation on the micro-blogging system
WAIM'13 Proceedings of the 14th international conference on Web-Age Information Management
Efficient Time-Stamped Event Sequence Anonymization
ACM Transactions on the Web (TWEB)
Prediction of members' return visit rates using a time factor
Electronic Commerce Research and Applications
Taxonomy discovery for personalized recommendation
Proceedings of the 7th ACM international conference on Web search and data mining
Finding progression stages in time-evolving event sequences
Proceedings of the 23rd international conference on World wide web
Colbar: A collaborative location-based regularization framework for QoS prediction
Information Sciences: an International Journal
Semi-sparse algorithm based on multi-layer optimization for recommender system
The Journal of Supercomputing
| Hi-index | 48.24 |
Customer preferences for products are drifting over time. Product perception and popularity are constantly changing as new selection emerges. Similarly, customer inclinations are evolving, leading them to ever redefine their taste. Thus, modeling temporal dynamics is essential for designing recommender systems or general customer preference models. However, this raises unique challenges. Within the ecosystem intersecting multiple products and customers, many different characteristics are shifting simultaneously, while many of them influence each other and often those shifts are delicate and associated with a few data instances. This distinguishes the problem from concept drift explorations, where mostly a single concept is tracked. Classical time-window or instance decay approaches cannot work, as they lose too many signals when discarding data instances. A more sensitive approach is required, which can make better distinctions between transient effects and long-term patterns. We show how to model the time changing behavior throughout the life span of the data. Such a model allows us to exploit the relevant components of all data instances, while discarding only what is modeled as being irrelevant. Accordingly, we revamp two leading collaborative filtering recommendation approaches. Evaluation is made on a large movie-rating dataset underlying the Netflix Prize contest. Results are encouraging and better than those previously reported on this dataset. In particular, methods described in this paper play a significant role in the solution that won the Netflix contest.