Research
String Matching Problems with Parallel Approaches An Evaluation for the Most Recent Studies
In recent years string matching plays a functional role in many application like information retrieval, gene analysis, pattern recognition, linguistics, bioinformatics etc. For understanding the functional requirements of string matching algorithms, we surveyed the real time parallel string matching patterns to handle the current trends. Primarily, in this paper, we focus on present developments of parallel string matching, and the central ideas of the algorithms and their complexities. We present the performance of the different algorithms and their effectiveness. Finally this analysis helps the researchers to develop the better techniques.
Parallel String Matching with Multi Core Processors-A Comparative Study for Gene Sequences
The increase in huge amount of data is seen clearly in present days because of requirement for storing more information. To extract certain data from this large database is a very difficult task, including text processing, information retrieval, text mining, pattern recognition and DNA sequencing. So we need concurrent events and high performance computing models for extracting the data. This will create a challenge to the researchers. One of the solutions is parallel algorithms for string matching on computing models. In this we implemented parallel string matching with JAVA Multi threading with multi core processing, and performed a comparative study on Knuth Morris Pratt, Boyer Moore and Brute force string matching algorithms. For testing our system we take a gene sequence which consists of lacks of records. From the test results it is shown that the multicore processing is better compared to lower versions. Finally this proposed parallel string matching with multicore processing is better compared to other sequential approaches.
