WordNet: a lexical database for English
Communications of the ACM
A re-examination of text categorization methods
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
Machine learning in automated text categorization
ACM Computing Surveys (CSUR)
Feature selection on hierarchy of web documents
Decision Support Systems - Web retrieval and mining
Text Categorization with Suport Vector Machines: Learning with Many Relevant Features
ECML '98 Proceedings of the 10th European Conference on Machine Learning
A Comparative Study on Feature Selection in Text Categorization
ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
Supervised term weighting for automated text categorization
Proceedings of the 2003 ACM symposium on Applied computing
Web-page classification through summarization
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
Semantic cores for representing documents in IR
Proceedings of the 2005 ACM symposium on Applied computing
A Semantic Web Primer, 2nd Edition (Cooperative Information Systems)
A Semantic Web Primer, 2nd Edition (Cooperative Information Systems)
Effective and efficient classification on a search-engine model
Knowledge and Information Systems
Supervised and Traditional Term Weighting Methods for Automatic Text Categorization
IEEE Transactions on Pattern Analysis and Machine Intelligence
Beyond TFIDF weighting for text categorization in the vector space model
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
An ontology-based information retrieval model
ESWC'05 Proceedings of the Second European conference on The Semantic Web: research and Applications
Using ontology to generate test cases for GUI testing
International Journal of Computer Applications in Technology
International Journal of Computer Applications in Technology
Addressing security compatibility for multi-tenant cloud services
International Journal of Computer Applications in Technology
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From the cognitive point of view, web documents consist of a list of concepts instead of terms (words or phrases). Therefore, identifying concepts will provide better results in retrieving useful information from the web. However, web documents are composed of text containing terms and concepts are included implicitly. In order to 'find' concepts in a text, we need their definitions and a method for their recognition. In this paper, we propose a novel adaptive assignment of term importance (AATI) schema. This schema is an ontology-based approach for defining and identifying concepts. It includes definitions of relations between terms and concepts, and an iterative algorithm for determining importance of terms. AATI continuously updates importance of terms with 'unknown' web documents, which makes it appropriate for web applications.