Abstract
The modern commercial search methods have proved the efficiency of information retrieval (IR) technologies and made knowledge dissemination simpler where as finding the relevant text documents, given a query, is becoming much more complex day after day. Almost all information retrieval systems struggle to retrieve relevant entries on the top of ranked list of documents. Users are interested to retrieve the content satisfying their information needs rather than just retrieving the documents having the query terms supplied by them. For this task, traditional information retrieval methods hardly yield the results having higher-order relations between the given query and the documents in the collection. So, it becomes necessary to find and encode the higher-order feature associations present in text documents. This paper discusses the use of a distributed representation, namely random indexing for an effective retrieval of relevant text documents. This type of distributed representation would be scalable with modern computing facilities and flexible to develop knowledge-based applications, which may require the process of identifying implicit semantic relations though higher-order term associations.http://dx.doi.org/10.14429/djlit.31.4.1104
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: DESIDOC Journal of Library & Information Technology
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
