GroupLens: an open architecture for collaborative filtering of netnews
CSCW '94 Proceedings of the 1994 ACM conference on Computer supported cooperative work
A personal news agent that talks, learns and explains
Proceedings of the third annual conference on Autonomous Agents
Recommender systems in e-commerce
Proceedings of the 1st ACM conference on Electronic commerce
Proceedings of the 11th international conference on World Wide Web
Learning implicit user interest hierarchy for context in personalization
Proceedings of the 8th international conference on Intelligent user interfaces
The Journal of Machine Learning Research
Latent semantic models for collaborative filtering
ACM Transactions on Information Systems (TOIS)
Newsjunkie: providing personalized newsfeeds via analysis of information novelty
Proceedings of the 13th international conference on World Wide Web
Time weight collaborative filtering
Proceedings of the 14th ACM international conference on Information and knowledge management
Google news personalization: scalable online collaborative filtering
Proceedings of the 16th international conference on World Wide Web
Research Paper Recommender Systems: A Random-Walk Based Approach
WI '06 Proceedings of the 2006 IEEE/WIC/ACM International Conference on Web Intelligence
A framework for projected clustering of high dimensional data streams
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
EigenRank: a ranking-oriented approach to collaborative filtering
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Introducing Serendipity in a Content-Based Recommender System
HIS '08 Proceedings of the 2008 8th International Conference on Hybrid Intelligent Systems
CARD: a decision-guidance framework and application for recommending composite alternatives
Proceedings of the 2008 ACM conference on Recommender systems
A random walk method for alleviating the sparsity problem in collaborative filtering
Proceedings of the 2008 ACM conference on Recommender systems
Context-aware recommender systems
Proceedings of the 2008 ACM conference on Recommender systems
A random walk on the red carpet: rating movies with user reviews and pagerank
Proceedings of the 17th ACM conference on Information and knowledge management
Ontology-Based Personalised and Context-Aware Recommendations of News Items
WI-IAT '08 Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 01
Personalized recommendation on dynamic content using predictive bilinear models
Proceedings of the 18th international conference on World wide web
TrustWalker: a random walk model for combining trust-based and item-based recommendation
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Collaborative filtering with temporal dynamics
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
TANGENT: a novel, 'Surprise me', recommendation algorithm
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Grocery shopping recommendations based on basket-sensitive random walk
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Personalized news recommendation based on click behavior
Proceedings of the 15th international conference on Intelligent user interfaces
A contextual-bandit approach to personalized news article recommendation
Proceedings of the 19th international conference on World wide web
Metrics for evaluating the serendipity of recommendation lists
JSAI'07 Proceedings of the 2007 conference on New frontiers in artificial intelligence
Temporal diversity in recommender systems
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
Temporal recommendation on graphs via long- and short-term preference fusion
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
A multimedia recommender integrating object features and user behavior
Multimedia Tools and Applications
Towards context-aware personalization and a broad perspective on the semantics of news articles
Proceedings of the fourth ACM conference on Recommender systems
Integrating Document Clustering and Multidocument Summarization
ACM Transactions on Knowledge Discovery from Data (TKDD)
SCENE: a scalable two-stage personalized news recommendation system
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
LOGO: a long-short user interest integration in personalized news recommendation
Proceedings of the fifth ACM conference on Recommender systems
Collaborative filtering by personality diagnosis: a hybrid memory- and model-based approach
UAI'00 Proceedings of the Sixteenth conference on Uncertainty in artificial intelligence
Hybrid systems for personalized recommendations
ITWP'03 Proceedings of the 2003 international conference on Intelligent Techniques for Web Personalization
Semantics-based news recommendation
Proceedings of the 2nd International Conference on Web Intelligence, Mining and Semantics
A location-based news article recommendation with explicit localized semantic analysis
Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval
Towards a journalist-based news recommendation system: The Wesomender approach
Expert Systems with Applications: An International Journal
Personalized news recommendation using ontologies harvested from the web
WAIM'13 Proceedings of the 14th international conference on Web-Age Information Management
CONCERT: a concept-centric web news recommendation system
WAIM'13 Proceedings of the 14th international conference on Web-Age Information Management
Personalized news recommendation via implicit social experts
Information Sciences: an International Journal
| Hi-index | 12.05 |
User profiling is an important step for solving the problem of personalized news recommendation. Traditional user profiling techniques often construct profiles of users based on static historical data accessed by users. However, due to the frequent updating of news repository, it is possible that a user's fine-grained reading preference would evolve over time while his/her long-term interest remains stable. Therefore, it is imperative to reason on such preference evaluation for user profiling in news recommenders. Besides, in content-based news recommenders, a user's preference tends to be stable due to the mechanism of selecting similar content-wise news articles with respect to the user's profile. To activate users' reading motivations, a successful recommender needs to introduce ''somewhat novel'' articles to users. In this paper, we initially provide an experimental study on the evolution of user interests in real-world news recommender systems, and then propose a novel recommendation approach, in which the long-term and short-term reading preferences of users are seamlessly integrated when recommending news items. Given a hierarchy of newly-published news articles, news groups that a user might prefer are differentiated using the long-term profile, and then in each selected news group, a list of news items are chosen as the recommended candidates based on the short-term user profile. We further propose to select news items from the user-item affinity graph using absorbing random walk model to increase the diversity of the recommended news list. Extensive empirical experiments on a collection of news data obtained from various popular news websites demonstrate the effectiveness of our method.