Text Document Clustering. A Hard and Soft Computing Approach

      Аннотация: This Book provides a thorough overview of the document clustering techniques used in Text mining. It focuses on the different phases of document clustering: Pre-processing, Feature extraction, Feature selection and Clustering. It narrates the different methodologies applied in clustering process. The book acquaints the research students with the different soft and hard computing approaches that are most commonly used while carrying out their researches in various areas. The text book also contains the data flow diagrams for document clustering, recall precision rates and Inter-relationship between Research Papers. It also includes MatLab code for document clustering process. This book clears the ideas about the fuzzy clustering technique and its applicability in the document clustering process.

Ключевые слова: Clustering, Data Mining, Information Retrieval, Information Extraction, soft computing, Hard Computing, fuzzy c-means, K-means, Recall and Precision, Similarity Measures