A Robust Multi-Keyword Text Content Retrieval by Utilizing Hash Indexing

Abstract

Digital content on servers increase the  storage and fetching issues. So, researcher works in this  field to organize content for fast retrieval with data security.  This paper has worked on text digital content retrieval  available in form of documents, files. User can search a  desired file by test query and relevant list of files get  appeared. Keywords were fetched from the text content by  removing noisy data during pre-processing. Pre-processed  keywords are identified by the number known as term ID.  As per the term-ID each text content got a Hash Index  which was termed as key numbers in document index. Each  term or word has its own identification number known as  term Id , so privacy of comparing content terms and user  query maintain by hash based searching. As document  identification done by hash index key, so storage of text  content was done in encrypted numbers once document  select for reading then decryption of document applied for a  particular user. Experiment was done on real and artificial  text content dataset files on different topics. It was obtained  that proposed model of Hash indexing and tem based  retrieval has improved the privacy with relevancy of as per  query.