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ReserarchID
CSTNWS5A413
As the number of electronic data collections available on the internet increases, so does the difficulty of finding the right collection for a given query. Often the first time user will be overwhelmed by the array of options available, and will waste time hunting through pages of collection names, followed by time reading results pages after doing an adhoc search. Collection selection using optimal weight methods try to solve this problem by suggesting the best subset of collections to search based on a query. This is of importance to fields containing large number of electronic collections which undergo frequent change, and collections that cannot be fully indexed using traditional methods such as spiders. This paper presents a solution to these problems of selecting the best collections and reducing the number of collections needing to be searched.
K. S. Niraja. 2016. \u201cA New Modified Collection Selection Algorithm using Optimal Term Weight for Web based Applications\u201d. Global Journal of Computer Science and Technology - E: Network, Web & Security GJCST-E Volume 16 (GJCST Volume 16 Issue E2): .
Crossref Journal DOI 10.17406/gjcst
Print ISSN 0975-4350
e-ISSN 0975-4172
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Total Score: 103
Country: India
Subject: Global Journal of Computer Science and Technology - E: Network, Web & Security
Authors: K. S. Niraja, B. Ramana Reddy, K. B. K. S. Durga (PhD/Dr. count: 0)
View Count (all-time): 249
Total Views (Real + Logic): 7338
Total Downloads (simulated): 1947
Publish Date: 2016 04, Mon
Monthly Totals (Real + Logic):
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As the number of electronic data collections available on the internet increases, so does the difficulty of finding the right collection for a given query. Often the first time user will be overwhelmed by the array of options available, and will waste time hunting through pages of collection names, followed by time reading results pages after doing an adhoc search. Collection selection using optimal weight methods try to solve this problem by suggesting the best subset of collections to search based on a query. This is of importance to fields containing large number of electronic collections which undergo frequent change, and collections that cannot be fully indexed using traditional methods such as spiders. This paper presents a solution to these problems of selecting the best collections and reducing the number of collections needing to be searched.
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