String matching algorithms for reteriving information from desktop — Comparative analysis

Information retrieval is the method of retrieving the knowledge relevant to an issue of curiosity. It locates the relevant documents, on the premise of user's question which includes keywords or example files. Probably the most acquainted application of information retrieval system is search engine corresponding to Web search, Desktop search, Federated search, Mobile search, Enterprise search and Social search. This research work mainly focused on the desktop search. Desktop search is the specified variant of enterprise search, where the information foundations are the files stored on a personal computer, together with email and websites established on content analysis. Content Analysis is a group of manual or computer based approaches for contextualized explanations of documents. To analyze the content the different text pattern matching algorithms are used and it is used to discover all the existences of a limited set of patterns inside an input document. Commonly these algorithms are used in several applications that include information security bio-informatics, plagiarism detection, text mining and document matching. String matching is essential for finding text patterns that are in online and offline. String matching algorithm is used to matches the pattern precisely or about in the input document. The main objective of this research work is to analyze the performance of existing string matching algorithms. For this comparison there are four algorithms are used namely, Two way algorithm, Colussi algorithm, Optimal mismatch algorithm and Maximal shift algorithm. From this analysis it is observed that the Colussi string matching algorithm gives the better result.