Automatic Document Clustering: Amharic News Items


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  • Product Description

Document clustering has a vital role in information storage and retrieval. In order to retrieve set of documents, it would be easy if the collection was clustered. This research is an investigation to the development of a prototype system that can automatically cluster a collection of Amharic news items. There are different techniques to automatic document clustering. The variants of hierarchical and partitional techniques are the most widely used methods. This research followed partitional clustering methodology specifically k-means and find optimum cluster of documents using statistical approach. Both internal and external qualities of clusters were evaluated using news items from Ethiopian News Agency (ENA). Overall average pair- wise similarity and overall purity were used to measure the internal quality of clusters. The values of these parameters were found to be 0.0797 and 0.7840 respectively. External quality was also measured using f-measure and its value was found to be 0.7705

Product Specifications
SKU :COC39255
AuthorSemahegne Ayalew
Number of Pages88
Publishing Year2010-12-01T00:00:00.000
Edition83 st
Book TypeComputing & information technology
Country of ManufactureIndia
Product BrandVDM Verlag Dr. Müller
Product Packaging InfoBox
In The Box1 Piece
Product First Available On ClickOnCare.com2015-01-08 00:00:00
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