Mental models: towards a cognitive science of language, inference, and consciousness
Mental models: towards a cognitive science of language, inference, and consciousness
Naive (Bayes) at Forty: The Independence Assumption in Information Retrieval
ECML '98 Proceedings of the 10th European Conference on Machine Learning
Scaling multi-class support vector machines using inter-class confusion
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Effect of term distributions on centroid-based text categorization
Information Sciences—Informatics and Computer Science: An International Journal - Special issue: Informatics and computer science intelligent systems applications
Data And Text Mining: A Business Application Approach
Data And Text Mining: A Business Application Approach
Cognitive Psychology: Connecting Mind, Research and Everyday Experience
Cognitive Psychology: Connecting Mind, Research and Everyday Experience
Virtual relevant documents in text categorization with support vector machines
Information Processing and Management: an International Journal
On the strength of hyperclique patterns for text categorization
Information Sciences: an International Journal
Expert Systems with Applications: An International Journal
Automatic recognition of German news focusing on future-directed beliefs and intentions
Computer Speech and Language
Review: Causal knowledge and reasoning by cognitive maps: Pursuing a holistic approach
Expert Systems with Applications: An International Journal
Text categorization via generalized discriminant analysis
Information Processing and Management: an International Journal
Construction of supervised and unsupervised learning systems for multilingual text categorization
Expert Systems with Applications: An International Journal
International Journal of Approximate Reasoning
An effective refinement strategy for KNN text classifier
Expert Systems with Applications: An International Journal
Computing with words for text processing: An approach to the text categorization
Information Sciences: an International Journal
Class normalization in centroid-based text categorization
Information Sciences: an International Journal
Information Sciences: an International Journal
User comments for news recommendation in forum-based social media
Information Sciences: an International Journal
Cognitive intentionality extraction from discourse with pragmatic-tree construction and analysis
Information Sciences: an International Journal
Combining relevancy and methodological quality into a single ranking for evidence-based medicine
Information Sciences: an International Journal
Feature annotation for text categorization
Proceedings of the CUBE International Information Technology Conference
Class-indexing-based term weighting for automatic text classification
Information Sciences: an International Journal
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Text categorization is an important research area of text mining. The original purpose of text categorization is to recognize, understand and organize different types of texts or documents. The general categorization approaches are treated as supervised learning, which infers similarity among a collection of categorized texts for training purposes. The existing categorization approaches are obviously not content-oriented and constrained at single word level. This paper introduces an innovative content-oriented text categorization approach named as CogCate. Inspired by cognitive situation models, CogCate exploits a human cognitive procedure in categorizing texts. In addition to traditional statistical analysis at word level, CogCate also applies lexical/semantical analysis, which ensures the accuracy of categorization. The evaluation experiments have testified the performance of CogCate. Meanwhile, CogCate remarkably reduces the time and effort spent on software training and maintenance of text collections. Our research work attests that interdisciplinary research efforts benefit text categorization.