Title :
Using a Matrix Decomposition for Clustering Data
Author :
Abdulla, Hussam Dahwa ; Polovincak, Martin ; Snasel, Vaclav
Author_Institution :
Dept. of Comput. Sci., VSB-Tech. Univ. of Ostrava, Ostrava, Czech Republic
Abstract :
There are many search engines in the web and when asked, they return a long list of search results, ranked by their relevancies to the given query. Web users have to go through the list and examine the titles and (short) snippets sequentially to identify their required results. In this paper we present how usage of Matrix Decomposition (Singular Value Decomposition (SVD) and Nonnegative Matrix Factorization (NMF)) can be good solution for the search results clustering.
Keywords :
Web services; singular value decomposition; Nonnegative Matrix Factorization; clustering data; matrix decomposition; nonnegative matrix factorizationquery; search engines; singular value decomposition; Computational linguistics; Computer networks; Computer science; Data mining; Information retrieval; Machine learning; Matrix decomposition; Search engines; Singular value decomposition; Social network services; Data clustering; Nonnegative Matrix Factorization (NMF); Search results clustering; Singular Value Decomposition;
Conference_Titel :
Computational Aspects of Social Networks, 2009. CASON '09. International Conference on
Conference_Location :
Fontainbleu
Print_ISBN :
978-1-4244-4613-1
DOI :
10.1109/CASoN.2009.11
