Research Article
Semantic Sense Annotation from User Query by using Web Search Techniques
@ARTICLE{10.4108/eai.13-7-2018.156005, author={Sunita Mahajan and Dr. Vijay Rana}, title={Semantic Sense Annotation from User Query by using Web Search Techniques}, journal={EAI Endorsed Transactions on Future Internet: Online First}, volume={}, number={}, publisher={EAI}, journal_a={UE}, year={2018}, month={12}, keywords={User Query, Information Retrieval, Web Search}, doi={10.4108/eai.13-7-2018.156005} }
- Sunita Mahajan
Dr. Vijay Rana
Year: 2018
Semantic Sense Annotation from User Query by using Web Search Techniques
UE
EAI
DOI: 10.4108/eai.13-7-2018.156005
Abstract
These days, individuals as often as possible use search engines keeping in mind the end goal to discover the information they must on the web. Be that as it may, as a rule, web information retrieval appear rear to most often searched web pages in a worldwide positioning makes difficulties to the clients to pursue distinctive themes fixed the outcome set and in this way making it tough to discover rapidly the coveted webpages. The requirements for uncommon calculation process of the frameworks that will discover knowledge in this web-based searching comes about giving the client the likelihood to pursue diverse themes controlled to given outcome set. The proposed model consists of phases, primarily used to reduce execution time in URL fetch. The first phase includes preprocessing that handle the error in words of the input query, the second phase is a unique keyword segmentation that extracts synonyms corresponding keywords. The keywords segmentation process is used most probable clustering mechanism to reduce overall execution time by grouping the similar keywords so that server doesn’t involve again and again, the third phase includes the sense segmentation. This phase fetches the URL corresponding to synonyms fetched in the second phase. In the results section, the results in terms of execution time indicate improvement by and a number of a fetched result.
Copyright © 2018 Sunita Mahajan et al., licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.