Intelligent text searching tool for E-book collection

Abstract

Nowadays digital data is available all over the world. Digital data storages growing day by day, 2009 Librarian E-book survey conducted by Stanford University which represents responses of 138 librarians and 13 countries, state the rapid growth of digital data clearly. As quantity of digital data increases, fetch required piece of data out of digital library become difficult and challenging. As a solution different kind of information extracting techniques and tools has been invented. Search engines, web spiders, database searching techniques and Library Catalogs are commonly available for information extraction. Most of these tools based on Information retrieval (IR), which is a great feature to have in search tool but because of the semantic disconnect between query and documents, IR is liable to return a lot of junk. So in most cases only IR is not enough for an effective text extraction. Once user require to find exact pieces of data, normal scenario is user will get huge list of results set from search tool and user has to manually analyze the result set to figure out most relevant result. This is both time and energy consuming. Considering all these facts this research is towards to discover an effective text searching tool. In order to achieve this goal some intelligence need to be added for the text searching tools. Intelligence is for extracting correct set of results and to order them according to the user requirements. The scope of this project is restricted to search on collection of E-books/ E-book library. The reason behind the focus on E-book collection is high accessibility of web searching tools and limited searching facility available on digital document collection. In this research work I argue that extracting most effective result or set of results out of collection of digital documents is no more impossible. I propose a way to pre-process digital document and the user query before start search function. Preprocessing increases the effectiveness and efficiency of search functionality. Then go through search function and collect all the available search results. Finally search result optimization function will discover the relevancy order of result set vs. user inquiry.