Comparative Study on Text Pattern Matching for Heterogeneous System

Abstract

Pattern-matching has been routinely used in various computer applications, for example, in editors, retrieval of information either textual, image, or sound and searching nucleotide or amino acid sequence patterns in genome and protein sequence databases. Pattern-matching algorithm matches the pattern exactly or approximately within the text. This paper presents the comparative analysis of various multiple pattern Text matching algorithms. The highly efficient algorithms like Brute Force algorithm, Knuth Morris Pratt algorithm, Finite Auto Mata algorithm, Bayer Moore algorithm for exact and approximate multi-object and multi-pattern matching on heterogeneous systems. After performing a detailed study on the above mentioned algorithms, the best algorithm having least complexity is chosen. Consequently, the comparison result proves that Bayer Moore Pattern matching algorithm is the most efficient One to apply on heterogeneous system for pattern matching.

Authors and Affiliations

Priya jain , Shikha Pandey

Keywords

Related Articles

HCI and Eye Tracking : Emotion Recognition Using Hidden Markov Model

Recognition of Emotion can be identified using Eye Tracking methods which may be non-intrusive. SVD and HMM are used for eye tracking to recognize emotions, which classifies six different emotions with less correlation c...

SURVEY ON BIG DATA MINING PLATFORMS, ALGORITHMS AND CHALLENGES

“Big data” is coined to address massive volumes of data sets usually huge, sparse, incomplete, uncertain, complex or dynamic, which are mainly coming from multiple and autonomous sources. The primary sources for big data...

Refined Markov clustering Algorithm for Mycobacterium Tuberculosis Protein Sequence analysis

Clustering of proteins is an essential as it helps to infer biological function of a new sequence. In this paper, the protein sequences of Mycobacterium Tuberculosis have been clustered based on its space group using Ref...

An Effective Approach for Web Document Classification using FP-Growth and Naïve Bayes Techniques

Exponential growth of the web increased the importance of web documents classification and data mining. To get the exact information, in the form of knowing what classes a web document belongs to, is expensive. Automatic...

Dynamic Time Quantum in Shortest Job First Scheduling Algorithm (DTQSJF) for Unpredictable Burst Time of Processes

In multitasking and time sharing operating system the performance of the CPU depends on waiting time, response time, turnaround time, context switches from the process mainly depends on the scheduling algorithm. Shortest...

Download PDF file
  • EP ID EP119895
  • DOI -
  • Views 97
  • Downloads 0

How To Cite

Priya jain, Shikha Pandey (2012). Comparative Study on Text Pattern Matching for Heterogeneous System. International Journal of Computer Science & Engineering Technology, 3(11), 537-543. https://europub.co.uk/articles/-A-119895