An efficient voice based information retrieval using bag of words based indexing

Abstract

Data mining is one of the leading and drastically growing researches nowadays. One of the main areas in data mining is Information Retrieval (IR). Information retrieval is a broad job and it is finding information without any structured nature. Infor-mation retrieval retrieves the user required information from a large collection of data. The existing approaches yet to improve the accuracy in terms of relevant accuracy. In this paper, it is motivated to provide an Information Retrieval System (IRS) where it can retrieve information with high relevancy. The proposed IRS is specially designed for physically challenged people like blind people where the input and the output taken/given is voice. The functionality of proposed IRS consists of three stages such as: (i) Voice to Text input, (II). Pattern Matching, and (III). Text to Voice output.In order to improve the accuracy and relevancy the proposed IRS uses an indexing method called Bag of Words (BOW). BOW is like an index-table which can be referred to store, compare and retrieve the information speedily and accurately. Index-table utilization in IRS improves the accuracy with minimized computational complexity. The proposed IRS is simulated in DOTNET software and the results are compared with the existing system results in order to evaluate the performance.