Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: , the problem of skewness in text corpora for effective classification is addressed. A method of converting an imbalanced text corpus into a more or less balanced one is presented through an application of a classwise clustering algorithm. Further, to avoid curse of dimensionality, the chi-squared feature selection is employed. Nevertheless, each cluster of documents has been given a single vector representation by the use of a vector of interval-valued data which accomplishes a compact representation of text data thereby requiring a less memory for storage. A suitable symbolic classifier is used to match a query document against stored interval valued vectors. The superiority of the model has been demonstrated by conducting series of experiments on two benchmarking imbalanced corpora viz., Reuters-21578 and TDT2. In addition, a comparative analysis of the results of the proposal model versus that of the state of the art models on Reuters 21578 dataset indicates that the proposed model outperforms several contemporary models.
['Mahamad Suhil', 'D. S. Guru', 'Lavanya Narayana Raju', 'Harsha S. Gowda']
I am writing a research paper on a idea Simple yet effective classification model for skewed text categorization
[{"from": "human", "value": "I am writing a research paper on a idea Simple yet effective classification model for skewed 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: , the problem of skewness in text corpora for effective classification is addressed. A method of converting an imbalanced text corpus into a more or less balanced one is presented through an application of a classwise clustering algorithm. Further, to avoid curse of dimensionality, the chi-squared feature selection is employed. Nevertheless, each cluster of documents has been given a single vector representation by the use of a vector of interval-valued data which accomplishes a compact representation of text data thereby requiring a less memory for storage. A suitable symbolic classifier is used to match a query document against stored interval valued vectors. The superiority of the model has been demonstrated by conducting series of experiments on two benchmarking imbalanced corpora viz., Reuters-21578 and TDT2. In addition, a comparative analysis of the results of the proposal model versus that of the state of the art models on Reuters 21578 dataset indicates that the proposed model outperforms several contemporary models."}]