@article{10.11648/j.ajcst.20230601.14,
  author = {Feng Kai and Tuyatsetseg Badarch},
  title = {Research and Implementation of Word Detection System Based on Improved DFA in China},
  journal = {American Journal of Computer Science and Technology},
  volume = {6},
  number = {1},
  pages = {25-32},
  doi = {10.11648/j.ajcst.20230601.14},
  url = {https://doi.org/10.11648/j.ajcst.20230601.14},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajcst.20230601.14},
  abstract = {Since the second half of the last century, the intensive usage of digital texts and textual databases produced the need for efficient search methods and data structures. Even though there are many traditional pattern matching algorithms such as regular matching, AC algorithm, and WM algorithm, in this paper, we use on a word detection method based on an improved DFA algorithm. We focus on the implementation of content matching technology using an improved DFA algorithm. We used the approach that can retrieve the emoticon icon, half corner character, repeated word based on ConcurrentSkipListMap to construct the tree of the word filtering system. We introduce the architecture of the system that mainly depends on the middleware, database, and data processing parts. The algorithm performs functions including filtering the word to match multiple pattern strings, to share a common prefix of a string that can reduce repeated lookups and save memory space. We use the pre-trained word vector model to achieve good results for the expansion and improvement of the sensitive lexicon. The system realizes the functions of word matching, including initializing, changing, matching, and highlighting of the word database, various processes that are tested and analyzed. We did a simulation to capture relevant word data and import it into MySQL database for storage. The method for message sensitive word recognition effectively improves the speed and accuracy of the algorithm recognition, the efficiency of word matching. We emphasize the DFA algorithm is the best approach compared to AC algorithm and other algorithms. Through function test, system test, and performance test, some valuable results are obtained. As a result of the tests, valuable results are founded from functional tests, system tests, performance tests. The system realizes the characteristics of large thesaurus and high matching efficiency of long text. It can meet the requirement of network real-time transmission, so it can be applied in the network. This paper proposes an improved multi-mode matching algorithm for word detection based on DFA. The algorithm maximizes the speed of problem detection and response efficiency and purifies the network space by optimizing the algorithm for the characters of the text content, the number of basic words and the detection efficiency. As a result of our research, we have shown the data from different sources of the system can be reused to reduce repeated construction costs.},
 year = {2023}
}

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TY  - JOUR
T1  - Research and Implementation of Word Detection System Based on Improved DFA in China
AU  - Feng Kai
AU  - Tuyatsetseg Badarch
Y1  - 2023/03/04
PY  - 2023
N1  - https://doi.org/10.11648/j.ajcst.20230601.14
DO  - 10.11648/j.ajcst.20230601.14
T2  - American Journal of Computer Science and Technology
JF  - American Journal of Computer Science and Technology
JO  - American Journal of Computer Science and Technology
SP  - 25
EP  - 32
PB  - Science Publishing Group
SN  - 2640-012X
UR  - https://doi.org/10.11648/j.ajcst.20230601.14
AB  - Since the second half of the last century, the intensive usage of digital texts and textual databases produced the need for efficient search methods and data structures. Even though there are many traditional pattern matching algorithms such as regular matching, AC algorithm, and WM algorithm, in this paper, we use on a word detection method based on an improved DFA algorithm. We focus on the implementation of content matching technology using an improved DFA algorithm. We used the approach that can retrieve the emoticon icon, half corner character, repeated word based on ConcurrentSkipListMap to construct the tree of the word filtering system. We introduce the architecture of the system that mainly depends on the middleware, database, and data processing parts. The algorithm performs functions including filtering the word to match multiple pattern strings, to share a common prefix of a string that can reduce repeated lookups and save memory space. We use the pre-trained word vector model to achieve good results for the expansion and improvement of the sensitive lexicon. The system realizes the functions of word matching, including initializing, changing, matching, and highlighting of the word database, various processes that are tested and analyzed. We did a simulation to capture relevant word data and import it into MySQL database for storage. The method for message sensitive word recognition effectively improves the speed and accuracy of the algorithm recognition, the efficiency of word matching. We emphasize the DFA algorithm is the best approach compared to AC algorithm and other algorithms. Through function test, system test, and performance test, some valuable results are obtained. As a result of the tests, valuable results are founded from functional tests, system tests, performance tests. The system realizes the characteristics of large thesaurus and high matching efficiency of long text. It can meet the requirement of network real-time transmission, so it can be applied in the network. This paper proposes an improved multi-mode matching algorithm for word detection based on DFA. The algorithm maximizes the speed of problem detection and response efficiency and purifies the network space by optimizing the algorithm for the characters of the text content, the number of basic words and the detection efficiency. As a result of our research, we have shown the data from different sources of the system can be reused to reduce repeated construction costs.
VL  - 6
IS  - 1
ER  - 

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