NDLI: A comparitive analysis of single pattern matching algorithms in text mining

Content Provider	IEEE Xplore Digital Library
Author	Sheshasayee, A. Thailambal, G.
Copyright Year	2015
Description	Author affiliation: Quaid-e-Millath Gov. Coll. for Women, Chennai, India (Sheshasayee, A.) \|\| SCSVMV Univ., Kancheepuram, India (Thailambal, G.)
Abstract	Text Mining is an emerging area of research where the necessary information of user needs to be provided from large amount of information. The user wants to find a text P in the search box from the group of text information T. A match needs to be found in the information then only the search is successful. Many String matching algorithms available for this search. This paper discusses three algorithms in unique pattern searching in which only one occurrence of the pattern is searched. Knuth Morris Pratt, Naive and Boyer Moore algorithms implemented in Python and compared their execution time for different Text length and Pattern length. This paper also gives you a brief idea about time Complexity, Characteristics given by other authors. The paper is concluded with the best algorithm for increase in text length and pattern length.
Starting Page	720
Ending Page	725
File Size	158955
Page Count	6
File Format	PDF
e-ISBN	9781467379106
DOI	10.1109/ICGCIoT.2015.7380557
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-10-08
Publisher Place	India
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Algorithm design and analysis Text mining Pattern Matching Preprocessing Green computing Internet of things Knuth Morris Pratt Automata Boyer Moore Time complexity Naive Pattern matching Python
Content Type	Text
Resource Type	Article

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