Quranic Latin Query Correction as a Search Suggestion

Satriady, Wildhan; Bijaksana, Moch Arif; Lhaksmana, Kemas Muslim

doi:10.1016/j.procs.2019.08.156

Cited by 2 publications

(6 citation statements)

References 9 publications

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“…This is one of the ways we can decide that something has a good overlap with the query term and it is a good candidate to suggest as a spelling correction. The retrieval process for plausible definitions of multiple n-grams in common, according to [8], is simply a single scan of the postings for the n-grams in the query term Q. In order to generate the set of bigrams for both Q and T, we designed an algorithm as shown in algorithm.…”

Section: Bigram Overlap Using Jcmentioning

confidence: 99%

“…It is a commonly used measure of n-gram overlap. Satriady et al [8] demonstrated how the linear scan intersection might be adapted when the measure of bigram overlap is the J.C for measuring the bigram overlap between two groups Q and T. It is given by (1):…”

Section: Bigram Overlap Using Jcmentioning

confidence: 99%

“…Query spelling correction is to automatically detect misspelt queries and find alternative forms in order to correct them [8]. The capability to automatically correct misspelt queries has become crucial in today's search engines.…”

Section: Introductionmentioning

confidence: 99%

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Automatic spelling error detection and correction for Tigrigna information retrieval: a hybrid approach

Desta

Lehal²

2023

Bulletin EEI

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This paper proposes a hybrid approach to design and implement query spelling error detection and correction (SEDC) for Tigrigna information retrieval (IR). Our approach, which is the main contribution to this work, is fast and robust to achieve better performance and also helps the users to easily insert their corrected queries to retrieve relevant information from the IR. This is achieved by combining the normalized measure of bigram overlap using the Jaccard coefficient (J.C) technique, a dynamic programming algorithm for edit distance, and probability of occurrence, which were used to make suggestions for the misspelt words. Our approach was evaluated on the SEDC subtasks separately. It achieved an F-measure of 98.85% on the spelling error detection subtask and an accuracy of 95.36% on the spelling error correction subtask. Thus, a comparison was conducted between our approach and the existing Tigrigna spell checker. It is found that our approach outperformed the existing spell checker and shows a 5.36% improvement in accuracy. This is by far the most promising result with regard to correcting the misspelt users’ queries and improving the overall performance of the IR.

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Section: Bigram Overlap Using Jcmentioning

confidence: 99%

Section: Bigram Overlap Using Jcmentioning

confidence: 99%

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Automatic spelling error detection and correction for Tigrigna information retrieval: a hybrid approach

Desta

Lehal²

2023

Bulletin EEI

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“…The second research is the development of Lafzi. Lafzi+ [5] is the development of the Lafzi system, which is to improve the function of the system. In this case, the addition of functions and improvement of existing systems.…”

Section: Related Workmentioning

confidence: 99%

“…Previous research has been conducted on the Quranic Latin Query Correction as a Search Suggestion [5], but the research is still less variation in the type of typing errors, only able to handle the types of typo namely substitution, deletion, and insertion. Whereas in typing errors, there are four types of typos, namely typo substitution, deletion, insertion, and transposition.…”

Section: Introductionmentioning

confidence: 99%

Typo handling in searching of Quran verse based on phonetic similarities

Purwita

Bijaksana

Lhaksmana

et al. 2020

regist. j. ilm. teknol. sist. inf.

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The Quran search system is a search system that was built to make it easier for Indonesians to find a verse with text by Indonesian pronunciation, this is a solution for users who have difficulty writing or typing Arabic characters. Quran search system with phonetic similarity can make it easier for Indonesian Muslims to find a particular verse. Lafzi was one of the systems that developed the search, then Lafzi was further developed under the name Lafzi+. The Lafzi+ system can handle searches with typo queries but there are still fewer variations regarding typing error types. In this research Lafzi++, an improvement from previous development to handle typographical error types was carried out by applying typo correction using the autocomplete method to correct incorrect queries and Damerau Levenshtein distance to calculate the edit distance, so that the system can provide query suggestions when a user mistypes a search, either in the form of substitution, insertion, deletion, or transposition. Users can also search easily because they use Latin characters according to pronunciation in Indonesian. Based on the evaluation results it is known that the system can be better developed, this can be seen from the accuracy value in each query that is tested can surpass the accuracy of the previous system, by getting the highest recall of 96.20% and the highest Mean Average Precision (MAP) reaching 90.69%. The Lafzi++ system can improve the previous system.

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Quranic Latin Query Correction as a Search Suggestion

Cited by 2 publications

References 9 publications

Automatic spelling error detection and correction for Tigrigna information retrieval: a hybrid approach

Automatic spelling error detection and correction for Tigrigna information retrieval: a hybrid approach

Typo handling in searching of Quran verse based on phonetic similarities

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