Pattern matching is a very important topic in computer science. It has been used in various applications such as information retrieval, virus scanning, DNA sequence analysis, data mining, machine learning, network sec...Pattern matching is a very important topic in computer science. It has been used in various applications such as information retrieval, virus scanning, DNA sequence analysis, data mining, machine learning, network security and pattern recognition. This paper has presented a new pattern matching algorithm—Enhanced ERS-A, which is an improvement over ERS-S algorithm. In ERS-A, two sliding windows are used to scan the text from the left and the right simultaneously. The proposed algorithm also scans the text from the left and the right simultaneously as well as making comparisons with the pattern from both sides simultaneously. The comparisons done between the text and the pattern are done from both sides in parallel. The shift technique used in the Enhanced ERS-A is the four consecutive characters in the text immediately following the pattern window. The experimental results show that the Enhanced ERS-A has enhanced the process of pattern matching by reducing the number of comparisons performed.展开更多
Pattern matching is a very important algorithm used in many applications such as search engine and DNA analysis. They are aiming to find a pattern in a text. This paper proposes a Pattern Matching Algorithm Using Chan...Pattern matching is a very important algorithm used in many applications such as search engine and DNA analysis. They are aiming to find a pattern in a text. This paper proposes a Pattern Matching Algorithm Using Changing Consecutive Characters (PMCCC) to make the searching pro- cess of the algorithm faster. PMCCC enhances the shift process that determines how the pattern moves in case of the occurrence of the mismatch between the pattern and the text. It enhances the Berry Ravindran (BR) shift function by using m consecutive characters where m is the pattern length. The formal basis and the algorithms are presented. The experimental results show that PMCCC made enhancements in searching process by reducing the number of comparisons and the number of attempts. Comparing the results of PMCCC with other related algorithms has shown significant enhancements in average number of comparisons and average number of attempts.展开更多
This paper presents an efficient pattern matching algorithm (FSW). FSW improves the searching process for a pattern in a text. It scans the text with the help of four sliding windows. The windows are equal to the leng...This paper presents an efficient pattern matching algorithm (FSW). FSW improves the searching process for a pattern in a text. It scans the text with the help of four sliding windows. The windows are equal to the length of the pattern, allowing multiple alignments in the searching process. The text is divided into two parts;each part is scanned from both sides simultaneously using two sliding windows. The four windows slide in parallel in both parts of the text. The comparisons done between the text and the pattern are done from both of the pattern sides in parallel. The conducted experiments show that FSW achieves the best overall results in the number of attempts and the number of character comparisons compared to the pattern matching algorithms: Two Sliding Windows (TSW), Enhanced Two Sliding Windows algorithm (ETSW) and Berry-Ravindran algorithm (BR). The best time case is calculated and found to be??while the average case time complexity is??.展开更多
文摘Pattern matching is a very important topic in computer science. It has been used in various applications such as information retrieval, virus scanning, DNA sequence analysis, data mining, machine learning, network security and pattern recognition. This paper has presented a new pattern matching algorithm—Enhanced ERS-A, which is an improvement over ERS-S algorithm. In ERS-A, two sliding windows are used to scan the text from the left and the right simultaneously. The proposed algorithm also scans the text from the left and the right simultaneously as well as making comparisons with the pattern from both sides simultaneously. The comparisons done between the text and the pattern are done from both sides in parallel. The shift technique used in the Enhanced ERS-A is the four consecutive characters in the text immediately following the pattern window. The experimental results show that the Enhanced ERS-A has enhanced the process of pattern matching by reducing the number of comparisons performed.
文摘Pattern matching is a very important algorithm used in many applications such as search engine and DNA analysis. They are aiming to find a pattern in a text. This paper proposes a Pattern Matching Algorithm Using Changing Consecutive Characters (PMCCC) to make the searching pro- cess of the algorithm faster. PMCCC enhances the shift process that determines how the pattern moves in case of the occurrence of the mismatch between the pattern and the text. It enhances the Berry Ravindran (BR) shift function by using m consecutive characters where m is the pattern length. The formal basis and the algorithms are presented. The experimental results show that PMCCC made enhancements in searching process by reducing the number of comparisons and the number of attempts. Comparing the results of PMCCC with other related algorithms has shown significant enhancements in average number of comparisons and average number of attempts.
文摘This paper presents an efficient pattern matching algorithm (FSW). FSW improves the searching process for a pattern in a text. It scans the text with the help of four sliding windows. The windows are equal to the length of the pattern, allowing multiple alignments in the searching process. The text is divided into two parts;each part is scanned from both sides simultaneously using two sliding windows. The four windows slide in parallel in both parts of the text. The comparisons done between the text and the pattern are done from both of the pattern sides in parallel. The conducted experiments show that FSW achieves the best overall results in the number of attempts and the number of character comparisons compared to the pattern matching algorithms: Two Sliding Windows (TSW), Enhanced Two Sliding Windows algorithm (ETSW) and Berry-Ravindran algorithm (BR). The best time case is calculated and found to be??while the average case time complexity is??.
