Novel filing systems applicable to an automated office: a state-of-the-art study
Information Processing and Management: an International Journal
Implementing agglomerative hierarchic clustering algorithms for use in document retrieval
Information Processing and Management: an International Journal
Optimal determination of user-oriented clusters
SIGIR '87 Proceedings of the 10th annual international ACM SIGIR conference on Research and development in information retrieval
Diversity in the use of electronic mail: a preliminary inquiry
ACM Transactions on Information Systems (TOIS)
Self-organization and associative memory: 3rd edition
Self-organization and associative memory: 3rd edition
Scatter/Gather: a cluster-based approach to browsing large document collections
SIGIR '92 Proceedings of the 15th annual international ACM SIGIR conference on Research and development in information retrieval
GroupLens: an open architecture for collaborative filtering of netnews
CSCW '94 Proceedings of the 1994 ACM conference on Computer supported cooperative work
Some advances in transformation-based part of speech tagging
AAAI '94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 1)
Context as a factor in personal information management systems
Journal of the American Society for Information Science
Social information filtering: algorithms for automating “word of mouth”
CHI '95 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Fab: content-based, collaborative recommendation
Communications of the ACM
Siteseer: personalized navigation for the Web
Communications of the ACM
GroupLens: applying collaborative filtering to Usenet news
Communications of the ACM
Hierarchic document classification using Ward's clustering method
Proceedings of the 9th annual international ACM SIGIR conference on Research and development in information retrieval
User-oriented document clustering: a framework for learning in information retrieval
Proceedings of the 9th annual international ACM SIGIR conference on Research and development in information retrieval
SIGIR '85 Proceedings of the 8th annual international ACM SIGIR conference on Research and development in information retrieval
Self-organizing maps
Inductive learning algorithms and representations for text categorization
Proceedings of the seventh international conference on Information and knowledge management
Recommendation as classification: using social and content-based information in recommendation
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
Fast and effective text mining using linear-time document clustering
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
Document clustering for electronic meetings: an experimental comparison of two techniques
Decision Support Systems - From information retrieval to knowledge management: enabling technologies and best practices
Partitioning-based clustering for Web document categorization
Decision Support Systems - Special issue on WITS '97
Analysis of recommendation algorithms for e-commerce
Proceedings of the 2nd ACM conference on Electronic commerce
A semi-supervised document clustering technique for information organization
Proceedings of the ninth international conference on Information and knowledge management
Machine learning in automated text categorization
ACM Computing Surveys (CSUR)
A context vector model for information retrieval
Journal of the American Society for Information Science and Technology
An effective document clustering method using user-adaptable distance metrics
Proceedings of the 2002 ACM symposium on Applied computing
Document clustering with committees
SIGIR '02 Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval
Document organization using Kohonen's algorithm
Information Processing and Management: an International Journal
A Comparative Study on Feature Selection in Text Categorization
ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
Learning Collaborative Information Filters
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
A simple rule-based part of speech tagger
ANLC '92 Proceedings of the third conference on Applied natural language processing
Combining preference- and content-based approaches for improving document clustering effectiveness
Information Processing and Management: an International Journal
Verifying the proximity and size hypothesis for self-organizing maps
Journal of Management Information Systems - Special section: Exploring the outlands of the MIS discipline
Journal of Management Information Systems
Empirical analysis of predictive algorithms for collaborative filtering
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
Recommendation systems for decision support: An editorial introduction
Decision Support Systems
Multidimensional credibility model for neighbor selection in collaborative recommendation
Expert Systems with Applications: An International Journal
Preserving User Preferences in Automated Document-Category Management: An Evolution-Based Approach
Journal of Management Information Systems
Discovering event episodes from news corpora: a temporal-based approach
Proceedings of the 11th International Conference on Electronic Commerce
Density link-based methods for clustering web pages
Decision Support Systems
Information Systems Frontiers
A literature review and classification of recommender systems research
Expert Systems with Applications: An International Journal
Electronic Commerce Research and Applications
Hi-index | 0.00 |
Document clustering is an intentional act that reflects individual preferences with regard to the semantic coherency and relevant categorization of documents. Hence, effective document clustering must consider individual preferences and needs to support personalization in document categorization. Most existing document-clustering techniques, generally anchoring in pure content-based analysis, generate a single set of clusters for all individuals without tailoring to individuals' preferences and thus are unable to support personalization. The partial-clustering-based personalized document-clustering approach, incorporating a target individual's partial clustering into the document-clustering process, has been proposed to facilitate personalized document clustering. However, given a collection of documents to be clustered, the individual might have categorized only a small subset of the collection into his or her personal folders. In this case, the small partial clustering would degrade the effectiveness of the existing personalized document-clustering approach for this particular individual. In response, we extend this approach and propose the collaborative-filtering-based personalized document-clustering (CFC) technique that expands the size of an individual's partial clustering by considering those of other users with similar categorization preferences. Our empirical evaluation results suggest that when given a small-sized partial clustering established by an individual, the proposed CFC technique generally achieves better clustering effectiveness for the individual than does the partial-clustering-based personalized document-clustering technique.