Keywords can be used as attributes for mining rules or a basis measuring the similarity of new (unclassified) documents with existing (classified) ones. The focus is on problem extracting keywords from document collection in order to use them classification. Document classification hot topic machine learning. Typical approaches extract “features,” generally words, document, and feature vectors ...

This paper addresses the problem of Near Duplicate document. Propose a new method to detect near duplicate document from a large collection of document set. This method is classified into three steps. Feature selection, similarity measures and discriminant function. Feature selection performs pre-processing; calculate the weight of each terms and heavily weighted term is selected as a features ...

Document structure weighting is a technique whereby different parts of a document (title, abstract, etc.) contribute unevenly to the overall document weight during ranking. Near optimal weights can be learned with a GA. Doing so shows a statistically significant 5% relative improvement in MAP for vector space inner product and Croft’s probabilistic ranking, but no improvement for BM25. Two appl...

Documents clustering become an essential technology with the popularity of the Internet. That also means that fast and high-quality document clustering technique play core topics. Text clustering or shortly clustering is about discovering semantically related groups in an unstructured collection of documents. Clustering has been very popular for a long time because it provides unique ways of di...