Artificial intelligence: a modern approach
Artificial intelligence: a modern approach
Social information filtering: algorithms for automating “word of mouth”
CHI '95 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
GroupLens: applying collaborative filtering to Usenet news
Communications of the ACM
Adaptive Web sites: automatically synthesizing Web pages
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
Probabilistic latent semantic indexing
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
An algorithmic framework for performing collaborative filtering
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
Unsupervised learning by probabilistic latent semantic analysis
Machine Learning
A tree projection algorithm for generation of frequent item sets
Journal of Parallel and Distributed Computing - Special issue on high-performance data mining
Measuring similarity of interests for clustering web-users
ADC '01 Proceedings of the 12th Australasian database conference
Discovery and Evaluation of Aggregate Usage Profiles for Web Personalization
Data Mining and Knowledge Discovery
ICDE '95 Proceedings of the Eleventh International Conference on Data Engineering
Learning to Probabilistically Identify Authoritative Documents
ICML '00 Proceedings of the Seventeenth International Conference on Machine Learning
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Knowledge discovery from users Web-page navigation
RIDE '97 Proceedings of the 7th International Workshop on Research Issues in Data Engineering (RIDE '97) High Performance Database Management for Large-Scale Applications
Evaluating collaborative filtering recommender systems
ACM Transactions on Information Systems (TOIS)
Latent semantic models for collaborative filtering
ACM Transactions on Information Systems (TOIS)
Discovering user access pattern based on probabilistic latent factor model
ADC '05 Proceedings of the 16th Australasian database conference - Volume 39
Using Probabilistic Latent Semantic Analysis for Web Page Grouping
RIDE '05 Proceedings of the 15th International Workshop on Research Issues in Data Engineering: Stream Data Mining and Applications
Letizia: an agent that assists web browsing
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
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Web transaction data usually convey user task-oriented behaviour pattern. Web usage mining technique is able to capture such informative knowledge about user task pattern from usage data. With the discovered usage pattern information, it is possible to recommend Web user more preferred content or customized presentation according to the derived task preference. In this paper, we propose a Web recommendation framework based on discovering task-oriented usage pattern with Probabilistic Latent Semantic Analysis (PLSA) model. The user intended tasks are characterized by the latent factors through probabilistic inference, to represent the user navigational interests. Moreover, the active user's intuitive task-oriented preference is quantized by the probabilities, by which pages visited in current user session are associated with various tasks as well. Combining the identified task preference of current user with the discovered usage-based Web page categories, we can present user more potentially interested or preferred Web content. The preliminary experiments performed on real world data sets demonstrate the usability and effectiveness of the proposed approach.