Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Text categorization is an important research field within text mining. A document, actually, is often full of class-independent “general” words which many documents and classes share. These “general” words do harm to text categorization rather than contribute to the task. Inspired by human cognitive procedure in text classification task,  propose a novel approach called Class Core Extraction (CCE) method to extract“core” terms from each class. The “core” terms, which include not only the single-words but also the combinations of words just like a simple description of context, must be those terms with strong distinguishing por. In testing phase, a suitable algorithm what  called “lottery” algorithm is also proposed, which use ighted matching strategy to make final categorization decision. The comparative experimenton two datasets shows that the accuracy of our approach outperforms the k-nearest-neighbor (kNN)based classifier, as ll as outstanding efficiency compare with the Support Vector Machine (SVM)based classifier.
['Shicai Yu', 'Jianxing Zhang']
I am writing a research paper on a idea A Class Core Extraction Method for Text Categorization
[{"from": "human", "value": "I am writing a research paper on a idea A Class Core Extraction Method for Text Categorization"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Text categorization is an important research field within text mining. A document, actually, is often full of class-independent \u201cgeneral\u201d words which many documents and classes share. These \u201cgeneral\u201d words do harm to text categorization rather than contribute to the task. Inspired by human cognitive procedure in text classification task,  propose a novel approach called Class Core Extraction (CCE) method to extract\u201ccore\u201d terms from each class. The \u201ccore\u201d terms, which include not only the single-words but also the combinations of words just like a simple description of context, must be those terms with strong distinguishing por. In testing phase, a suitable algorithm what  called \u201clottery\u201d algorithm is also proposed, which use ighted matching strategy to make final categorization decision. The comparative experimenton two datasets shows that the accuracy of our approach outperforms the k-nearest-neighbor (kNN)based classifier, as ll as outstanding efficiency compare with the Support Vector Machine (SVM)based classifier."}]