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Research on Uyghur Pattern Matching Based on Syllable Features

School of Information Science and Engineering, Xinjiang University, Urumqi 830046, China
Key Laboratory of Multilingual Information Technology in Xinjiang Uygur Autonomous Region, Urumqi 830046, China
Author to whom correspondence should be addressed.
Information 2020, 11(5), 248;
Received: 27 March 2020 / Revised: 30 April 2020 / Accepted: 1 May 2020 / Published: 2 May 2020
(This article belongs to the Section Information Processes)
Pattern matching is widely used in various fields such as information retrieval, natural language processing (NLP), data mining and network security. In Uyghur (a typical agglutinative, low-resource language with complex morphology, spoken by the ethnic Uyghur group in Xinjiang, China), research on pattern matching is also ongoing. Due to the language characteristics, the pattern matching using characters and words as basic units has insufficient performance. There are two problems for pattern matching: (1) vowel weakening and (2) morphological changes caused by suffixes. In view of the above problems, this paper proposes a Boyer–Moore-U (BM-U) algorithm and a retrievable syllable coding format based on the syllable features of the Uyghur language and the improvement of the Boyer–Moore (BM) algorithm. This algorithm uses syllable features to perform pattern matching, which effectively solves the problem of weakening vowels, and it can better match words with stem shape changes. Finally, in the pattern matching experiments based on character-encoded text and syllable-encoded text for vowel-weakened words, the BM-U algorithm precision, recall, F1-measure and accuracy are improved by 4%, 55%, 33%, 25% and 10%, 52%, 38%, 38% compared to the BM algorithm. View Full-Text
Keywords: pattern matching; text search; Uyghur; syllable; Boyer–Moore; BM-U pattern matching; text search; Uyghur; syllable; Boyer–Moore; BM-U
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Abliz, W.; Maimaiti, M.; Wu, H.; Wushouer, J.; Abiderexiti, K.; Yibulayin, T.; Wumaier, A. Research on Uyghur Pattern Matching Based on Syllable Features. Information 2020, 11, 248.

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