Study of Indexing Techniques to Improve the Performance of Information Retrieval in Telugu Language

Information Retrieval Systems (IRS) are so popular through World Wide Web. Availability of Text Information related to all types of objects like Documents, Web Pages, Images, Videos and Audio files on web are increasing day by day in an exponential manner. When the text repository grows to the maximum extent of the memory size in the server, the methods used to find a particular text unit either word or document is tedious task. Representation of these objects, using text information gives summarized features to decide whether to access the identified unit or not in the first look. Instead of exact query match in the document a set of keywords will be used to find the relevance of the document. If a set of keywords represents a document, then it is easy to match the couple of keywords from the query against keywords of the document and decide the relevance. Finding keywords to represent a complete unit is called index. Keyword are your own designated units which can be used for easy location of the document using any search engines. A keyword maps all the documents containing this indexed word. This problem is addressed by identifying indexed words or phrases of a document. Indexing terms together represents whole document and act as ambassadors of the unit. In this paper we studied the effect of various indexing techniques , namely , manual , automatic and semi-automatic on 10,000 Telugu text documents. Statistical Indexing is taken as base line approach and compared the results with other techniques. We observed that, the results are better plotted while moving from statistical representations to semantic representations. Keywords—Keywords, Indexing Terms, Manual Indexing, Automatic Indexing, Statistical Indexing, Semantic based Indexing, Telugu Text Corpus, N-gram, Inverted File Structure.