Filtering and Sophisticated Data Processing for Web Information Gathering
RSEISP '07 Proceedings of the international conference on Rough Sets and Intelligent Systems Paradigms
A two-stage text mining model for information filtering
Proceedings of the 17th ACM conference on Information and knowledge management
Effective pattern taxonomy mining in text documents
Proceedings of the 17th ACM conference on Information and knowledge management
Pattern Taxonomy Mining for Information Filtering
AI '08 Proceedings of the 21st Australasian Joint Conference on Artificial Intelligence: Advances in Artificial Intelligence
Adaptive Information Filtering Based on PTM Model (APTM)
WI-IAT '08 Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 03
Two-Stage Model for Information Filtering
WI-IAT '08 Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 03
An Operable Email Based Intelligent Personal Assistant
World Wide Web
Mining Negative Relevance Feedback for Information Filtering
WI-IAT '09 Proceedings of the 2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology - Volume 01
An effective model of using negative relevance feedback for information filtering
Proceedings of the 18th ACM conference on Information and knowledge management
Concept-Based, Personalized Web Information Gathering: A Survey
KSEM '09 Proceedings of the 3rd International Conference on Knowledge Science, Engineering and Management
Granular Computing for Text Mining: New Research Challenges and Opportunities
RSFDGrC '09 Proceedings of the 12th International Conference on Rough Sets, Fuzzy Sets, Data Mining and Granular Computing
Ontology based web mining for information gathering
WImBI'06 Proceedings of the 1st WICI international conference on Web intelligence meets brain informatics
International Journal of Intelligent Information and Database Systems
Mining positive and negative patterns for relevance feature discovery
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
Selected new training documents to update user profile
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
Rough sets based reasoning and pattern mining for a two-stage information filtering system
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
A pattern mining approach for information filtering systems
Information Retrieval
Pattern mining for a two-stage information filtering system
PAKDD'11 Proceedings of the 15th Pacific-Asia conference on Advances in knowledge discovery and data mining - Volume Part I
A two-stage decision model for information filtering
Decision Support Systems
A pattern discovery model for effective text mining
MLDM'12 Proceedings of the 8th international conference on Machine Learning and Data Mining in Pattern Recognition
Discovering relevant features for effective query formulation
IRFC'12 Proceedings of the 5th conference on Multidisciplinary Information Retrieval
Adopting relevance feature to learn personalized ontologies
AI'12 Proceedings of the 25th Australasian joint conference on Advances in Artificial Intelligence
Scoring-Thresholding pattern based text classifier
ACIIDS'13 Proceedings of the 5th Asian conference on Intelligent Information and Database Systems - Volume Part I
Using Patterns Co-occurrence Matrix for Cleaning Closed Sequential Patterns for Text Mining
WI-IAT '12 Proceedings of the The 2012 IEEE/WIC/ACM International Joint Conferences on Web Intelligence and Intelligent Agent Technology - Volume 01
A pattern based two-stage text classifier
MLDM'13 Proceedings of the 9th international conference on Machine Learning and Data Mining in Pattern Recognition
Text mining in negative relevance feedback
Web Intelligence and Agent Systems
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Text mining is the technique that helps users find useful information from a large amount of digital text documents on the Web or databases. Instead of the keyword-based approach which is typically used in this field, the pattern-based model containing frequent sequential patterns is employed to perform the same concept of tasks. However, how to effectively use these discovered patterns is still a big challenge. In this study, we propose two approaches based on the use of pattern deploying strategies. The performance of the pattern deploying algorithms for text mining is investigated on the Reuters dataset RCV1 and the results show that the effectiveness is improved by using our proposed pattern refinement approaches.