Narrow-domain Short Texts Clustering Algorithm

Please use this identifier to cite or link to this item: http://elar.urfu.ru/handle/10995/3709

Title:	Narrow-domain Short Texts Clustering Algorithm
Authors:	Popova, S. V. Khodyrev, I. A.
Issue Date:	2011
Publisher:	St. Petersburg University Press
Citation:	Popova S. V. Narrow-domain Short Texts Clustering Algorithm / S. V. Popova, I. A. Khodyrev // Web of Data: The joint RuSSIR/EDBT 2011 Summer School, August 15–19, 2011, Proceedings of the Fifth Russian Young Scientists Conference in Information Retrieval / B. Novikov, P. Braslavsky (Eds.). — St. Petersburg, 2011 — P. 30-39.
Abstract:	In this paper, we describe the algorithm of narrow-domain short texts clustering, which is based on terms’ selection and modification of k-means algorithm. Our approach was tested on collections: CICling–2002 and SEPLIN-CICling. Results of tests and conclusions are presented.
Keywords:	INFORMATION RETRIEVAL TEXTS CLUSTERING NARROW-DOMAIN SHORT TEXTS CLUSTERING K-MEANS GENETIC ALGORITHM
URI:	http://elar.urfu.ru/handle/10995/3709
Conference name:	V Russian Summer School in Information Retrieval (RuSSIR’2011) V Российская летняя школа по информационному поиску (RuSSIR’2011) EDBT Summer Schools
Conference date:	15.08.2011–19.08.2011
ISBN:	978-5-288-05225-5
Origin:	RuSSIR/EDBT2011
Appears in Collections:	Информационный поиск

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