New Search Techniques for Automatic Information Classification

Abstract

Information categorization has become one of the primary tasks of the text retrieval systems. The main objective of this research work is to classify the information which is available in tables. In this work, two new searching techniques, normal search and indexed search are proposed for categorizing the table information. The synthetic data set is created by using the information available in the Annexure II journal list dataset. The performance factors used here are classification accuracy, search time and outliers. From the experimental results it is observed that indexed search technique has produced better results in classification accuracy and outliers. For search time performance factor, the normal search technique required minimum time compared to index search.

Authors and Affiliations

Dr. S. Vijayarani, Ms. N. Nithya

Keywords

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  • EP ID EP20033
  • DOI -
  • Views 315
  • Downloads 4

How To Cite

Dr. S. Vijayarani, Ms. N. Nithya (2015). New Search Techniques for Automatic Information Classification. International Journal for Research in Applied Science and Engineering Technology (IJRASET), 3(3), -. https://www.europub.co.uk/articles/-A-20033