IMPLEMENTASI SPELLING CORRECTOR UNTUK MENGATASI TYPOGRAPHICAL ERROR PADA FITUR PENCARIAN APLIKASI KAMUS ISTILAH INFORMATIKA

Cahyo Prianto, Dian Markuci, Syafrial Fachri Pane
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Abstract

Information needs can arise because of a knowledge gap in a person with the necessary information needs, one of which is knowledge in the field of computers and informatics, especially related to terms in the computer field. Therefore we need a system that makes it easy for users to meet the information needs needed by building a digital dictionary application related to computer terms and informatics by utilizing the search engine features in it. Search activities are carried out daily to meet information needs. However, an error that is often unavoidable in performing a search is a typing error in the query. As a result, the information sought is not as expected. Based on this, we need a system that can identify typographical errors in the search text. So in this research, a website-based dictionary of computer and informatics terms will be developed by applying Peter Norvig's spelling corrector using the Python language with the flask framework. The implementation results show that Peter Norvig's spelling corrector method can be applied to computer and informatics term dictionary applications. This can be seen at the level of accuracy reaching 89% in correcting 180 word variations that contain typographical errors based on the highest probability of each possible word in the corpus. However, there is a lack of this spelling corrector method, it is still difficult to overcome typos in spelling abbreviations and typographical errors that exceed 1 letter
信息需求的产生可能是由于一个人在必要的信息需求方面存在知识差距,其中之一是计算机和信息学领域的知识,特别是与计算机领域的术语相关的知识。因此,我们需要一个系统,利用搜索引擎的特点,建立一个与计算机术语和信息学相关的数字词典应用程序,方便用户满足信息需求。为了满足信息需求,我们每天都进行搜索活动。然而,在执行搜索时经常不可避免的一个错误是查询中的输入错误。结果,所寻求的信息并不如预期的那样。基于此,我们需要一个能够识别搜索文本中的印刷错误的系统。因此,在这项研究中,一个基于网站的计算机和信息学术语词典将通过使用Python语言和flask框架应用Peter Norvig的拼写校正器来开发。实现结果表明,Peter Norvig的拼写校正方法可以应用于计算机和信息学术语词典。我们可以看到,基于语料库中每个可能单词的最高概率,在纠正180个包含排版错误的单词变体时,准确率达到89%。但是,由于缺乏这种拼写纠错方法,拼写缩略语中的拼写错误和超过1个字母的排版错误仍然难以克服
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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