Publication Type : Conference Proceedings
Publisher : Ambient Communications and Computer Systems, Advances in Intelligent Systems and Computing
Source : Ambient Communications and Computer Systems, Advances in Intelligent Systems and Computing, Springer Singapore, Volume 904, Singapore (2019)
Url : https://link.springer.com/chapter/10.1007/978-981-13-5934-7_34
ISBN : 9789811359347
Keywords : Linear search, Meta-search engine, Optimization, Semantic
Campus : Amritapuri
School : Department of Computer Science and Engineering, School of Engineering
Center : Algorithms and Computing Systems
Department : Computer Science
Verified : No
Year : 2019
Abstract : Search engines are turning out to be the greatest tools for gaining valuable data from the internet. Search engines return the search result to the user query which can be an important result or non-important result. Because, the users naturally look only at the first few pages of search results, and search engine ranking can introduce significant bias to their understanding of the internet and their information gain. When a search query is delivered to several search engines, each individual returns a list of pages based on the ranking. Scientists have confirmed that merging search results in a meta-search engine makes a substantial progress in a search result. Current meta-search engines use several search engines for fetching the results but do not emphasize on the semantic relation of the query for finding the best result. In order tod overcome this limitation, a new approach is proposed. The proposed approach can optimize meta-search results using the combination of linear search and semantic search.
Cite this Research Publication : Siji Rani S. and Goutham, S., “A Novel Approach for Meta-Search Engine Optimization”, Ambient Communications and Computer Systems, Advances in Intelligent Systems and Computing, vol. 904. Springer Singapore, Singapore, 2019