The extraction of multiple word which are related to expressions that has been increasingly a special topic in the last few years. Relevant expressions are applicable in diverse areas such as Information Retrieval, document clustering, or classification and indexing of documents. However, relevant single-words, which represent much of the knowledge in texts, have been a relatively dormant field. In this paper we present a statistical language-independent approach to extract concepts formed by relevant single and multi-word units. By achieving promising precision/recall values, it can be an alternative both to language dependent approaches and to extractors that deal exclusively with multi-words. In this paper proposed method pattern Taxonomy Deploying method to apply to find a new and efficient pattern method by which research related document, research related documents are patterned and classification of different field are done and more than 80% percent of the documents are successfully identified and categorized.
Pattern Taxonomy Deploying, Support Vector Machine, Pattern Taxonomy method
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