IR-Tree Implementation using Index Document Search Method
Deepak B. Kanthale1, R.P.Mahajan2
1Deepak B. Kanthale, Computer Engg., L.K.C.T, Indore ,R.G.P.V., Bhopal, India.
2R.P. Mahajan, Computer Engg., L.K.C.T, Indore, R.G.P.V., Bhopal India.
Manuscript received on June 05, 2014. | Revised Manuscript received on June 11, 2014. | Manuscript published on June 15, 2014. | PP: 11-15 | Volume-2 Issue-7, June 2014. | Retrieval Number: G0685062714/2014©BEIESP
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©The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Given a geographic question that’s composed of question keywords and a location, a geographic programmed retrieves documents that area unit the foremost textually and spatially relevant to the question keywords and therefore the location, severally, and ranks the retrieved documents consistent with their joint matter and spacial relevances to the question. the shortage of Associate in Nursing economical index that may at the same time handle each the matter and spacial aspects of the documents makes existing geographic search engines inefficient in respondent geographic queries. during this paper, we have a tendency to propose Associate in Nursing economical index, referred to as IR-tree, that in conjunction with a top-k document search algorithm facilitates four major tasks in document searches, namely, 1) spacial filtering, 2) matter filtering, 3) connexion computation, and 4) document ranking in an exceedingly absolutely integrated manner. additionally, IR-tree permits searches to adopt totally different weights on matter and spacial connexion of documents at the runtime and therefore caters for a good kind of applications. a group of comprehensive experiments over a good vary of eventualities has been conducted and therefore the experiment results demonstrate that IR-tree outperforms the state-of-the art approaches for geographic document searches.
Keywords: Spacial filtering) matter filtering, connexion computation, and document ranking.