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All Journal Halal Research Journal
Miftahul Jannah
ITS
Religion Agriculture, Biological Sciences & Forestry Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Engineering

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Food Ingredients Similarity Based on Conceptual and Textual Similarity Nur Aini Rakhmawati; Miftahul Jannah
Halal Research Vol 1 No 2 (2021): Volume 1 No 2 July 2021
Publisher : Halal Center ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (399.177 KB) | DOI: 10.12962/j22759970.v1i2.107

Abstract

Open Food Facts provides a database of food products such as product names, compositions, and additives, where everyone can contribute to add the data or reuse the existing data. The open food facts data are dirty and needs to be processed before storing the data to our system. To reduce redundancy in food ingredients data, we measure the similarity of ingredient food using two similarities: the conceptual similarity and textual similarity. The conceptual similarity measures the similarity between the two datasets by its word meaning (synonym), while the textual similarity is based on fuzzy string matching, namely Levenshtein distance, Jaro-Winkler distance, and Jaccard distance. Based on our evaluation, the combination of similarity measurements using textual and Wordnet similarity (conceptual) was the most optimal similarity method in food ingredients.
Co-Authors Nur Aini Rakhmawati