Research Paper | Computer Science & Engineering | India | Volume 3 Issue 5, May 2014
Improving Text Search Process using Text Document Clustering Approach
Ruchika Mavis Daniel, Arun Kumar Shukla
Knowledge discovery and data mining is a process of retrieving the meaningful knowledge from the raw data; using different techniques. Therefore; text mining is a sub domain of knowledge discovery from the text data. This paper provides a different way of understanding the text mining and their applications in different real time applications. This paper also includes the design of a hybrid text document clustering approach by which the document organization becomes easier for text search process. That includes the concept of fuzzy calculation; text summarization and traditional k-means clustering for cluster analysis of data. The implementation of the proposed methodology is summarized using a new kind of document clustering algorithm; and implemented using visual studio environment. After implementation of the proposed methodology the performance of the designed system is evaluated using the N-cross validation process. According to the obtained results the proposed system outperformed for text categorization with small amount of resources consumption. So; the proposed methodology is efficient and adoptable for different real time application.
Keywords: text search, text clustering, text classification and categorization
Edition: Volume 3 Issue 5, May 2014
Pages: 1424 - 1428
How to Cite this Article?
Ruchika Mavis Daniel, Arun Kumar Shukla, "Improving Text Search Process using Text Document Clustering Approach", International Journal of Science and Research (IJSR), https://www.ijsr.net/search_index_results_paperid.php?id=20132185, Volume 3 Issue 5, May 2014, 1424 - 1428