ThaiQCor 2.0:通过Soundex和Word逼近的泰语查询校正

Santipong Thaiprayoon, A. Kongthon, C. Haruechaiyasak
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引用次数: 3

摘要

如今,搜索引擎是使用户能够在互联网上搜索信息的重要工具。搜索中最重要的问题之一是由于排版和认知错误而导致的输入不准确。打字错误通常是由于键盘布局上相邻字母的输入错误造成的。认知错误是由于用户在查询词拼写方面缺乏知识造成的。为了解决这些问题,我们设计并开发了一个新版本的泰语查询纠正程序,称为ThaiQCor 2.0,它可以处理排版和认知错误。我们的程序包括两个主要的方法,词近似和soundex。单词逼近采用近似字符串检索技术,包括字符编辑距离计算。这种方法旨在解决印刷错误。Soundex应用字形到音素的转换,然后通过计算音素序列中加权音素的编辑距离来执行字符串匹配近似。这种方法的目的是处理认知错误。两种方法的所有候选词都会根据它们的分数进行排名,并推荐给用户。实验结果表明,ThaiQCor 2.0对地名和人名的识别准确率分别达到97.11%和89.76%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
ThaiQCor 2.0: Thai Query Correction via Soundex and Word Approximation
Nowadays, search engine is an important tool for enabling users to search for information on the Internet. One of the most important problems of searching is inaccurate typing due to typographical and cognitive errors. Typographical errors are normally resulting from typing mistakes from adjacent letters on a keyboard layout. Cognitive errors are due to the lack of user knowledge in query term spelling. To solve the problems, we designed and developed a new version of Thai query correction program called ThaiQCor 2.0 that can handle both typographical and cognitive errors. Our program consists of two main approaches, word approximation and soundex. Word approximation employs the approximate string retrieval technique including character edit distance calculation. This approach aims to solve the typographical errors. Soundex applies the grapheme-to-phoneme conversion and then performs string matching approximation by calculating the edit distance of weighted phonemes from phoneme sequences. The objective of this approach is to handle the cognitive errors. All candidate words from both approaches are ranked based on their scores and suggested to the user. The experimental results showed that ThaiQCor 2.0 achieves the accuracy of 97.11% and 89.76% for place names and person names, respectively.
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