Pattern Based Frequent Term Retrieval Search Using Text Clustering
R.Krithika 1 , G.Sathish Kumar2
Section:Research Paper, Product Type: Journal Paper
Volume-4 ,
Issue-4 , Page no. 292-297, Apr-2016
Online published on Apr 27, 2016
Copyright © R.Krithika, G.Sathish Kumar . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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IEEE Style Citation: R.Krithika, G.Sathish Kumar, “Pattern Based Frequent Term Retrieval Search Using Text Clustering,” International Journal of Computer Sciences and Engineering, Vol.4, Issue.4, pp.292-297, 2016.
MLA Style Citation: R.Krithika, G.Sathish Kumar "Pattern Based Frequent Term Retrieval Search Using Text Clustering." International Journal of Computer Sciences and Engineering 4.4 (2016): 292-297.
APA Style Citation: R.Krithika, G.Sathish Kumar, (2016). Pattern Based Frequent Term Retrieval Search Using Text Clustering. International Journal of Computer Sciences and Engineering, 4(4), 292-297.
BibTex Style Citation:
@article{Kumar_2016,
author = {R.Krithika, G.Sathish Kumar},
title = {Pattern Based Frequent Term Retrieval Search Using Text Clustering},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {4 2016},
volume = {4},
Issue = {4},
month = {4},
year = {2016},
issn = {2347-2693},
pages = {292-297},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=935},
publisher = {IJCSE, Indore, INDIA},
}
RIS Style Citation:
TY - JOUR
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=935
TI - Pattern Based Frequent Term Retrieval Search Using Text Clustering
T2 - International Journal of Computer Sciences and Engineering
AU - R.Krithika, G.Sathish Kumar
PY - 2016
DA - 2016/04/27
PB - IJCSE, Indore, INDIA
SP - 292-297
IS - 4
VL - 4
SN - 2347-2693
ER -
VIEWS | XML | |
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Abstract
Clients are known to experience troubles in dealing with information retrieval look outputs, particularly if those yields are above a certain size. It has been contended by several analysts that look yield Clustering can help clients in their collaboration with IR frameworks in some retrieval situations, providing them with an review of their results by abusing the topicality information that resides in the yield but has not been used at the retrieval stage. This review might enable them to find applicable records more effortlessly by focused on the most promising clusters, or to use the Groups as a starting-point for question refinement or expansion. In this paper, the results of tests carried out to assess the viability of Clustering as a look yield presentation technique are reported and discussed.
Key-Words / Index Term
Content Clustering, Pattern Mining, Content Retrieval, Clustering Algorithm
References
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