Accuracy of Textual Document Clustering With Semantic Approach | Natural Language Processing with Semantic by the help of WordNet. The accuracy of Clustering is assured by F-Measure

S. K. Ahammad Fahad

ISBN 10: 6133991720 / ISBN 13: 9786133991729

Published by LAP LAMBERT Academic Publishing, 2018

About this Item

Accuracy of Textual Document Clustering With Semantic Approach | Natural Language Processing with Semantic by the help of WordNet. The accuracy of Clustering is assured by F-Measure | S. K. Ahammad Fahad | Taschenbuch | 144 S. | Englisch | 2018 | LAP LAMBERT Academic Publishing | EAN 9786133991729 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu.

Seller Inventory # 110944266

Bibliographic Details

• Title: Accuracy of Textual Document Clustering With Semantic Approach | Natural Language Processing with Semantic by the help of WordNet. The accuracy of Clustering is assured by F-Measure
• Publisher: LAP LAMBERT Academic Publishing
• Publication Date: 2018
• Language: English
• ISBN 10: 6133991720
• ISBN 13: 9786133991729
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 220W x 150H x 10D millimeters 220 millimeters width by 150 millimeters height by 10 millimeters depth
• Weight: 233 grams
• Seller catalogs:
  • Bücher

About this title

Synopsis

Now the age of information technology, textual document is spontaneously increasing over the internet, e-mail, web pages, offline & online reports, journals, articles and those are stored in the electronic database format. Millions of new text file created in a day, for the lackings of classification, people miss vast information those are useful to several challenges. To maintain and access those documents are very difficult without adequate rating and when there has classification without any information provide call clustering. To overcome such difficulties K-means and others old clustering algorithms are unfit to impart as may be expected on Natural languages. Because of high-dimensional about texts, the presence of logical structure clues within the texts and novel segmentation techniques have taken advantage of advances in generative topic modeling algorithms, specifically designed to spot questions at intervals text to cipher word topic distributions. So considering the limitation, COBWEB conceptual clustering algorithm applied to the preprocessed data. For ensuring the accuracy of clusters, the f-measure accuracy measuring methods selected for evaluating the clusters.

About the Author

Mr. SK Ahammad Fahad achieves his Master’s from Al-Madinah International University (Malaysia). He earned a Bachelor's degree at IBAIS University (Bangladesh). Currently, he is working in Natural Language Processing with semantics and lexicon database on different Languages.