Implementation of Rabin Karp Algorithm in E-Commerce Search Box Feature (Case Study: Sinar Baja Store)

Yazeed Qholili Arifin, Ade Ismail, V. Firdaus
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引用次数: 0

Abstract

Inside any e-commerce platform, search features are a key factor in an online business. In order to look for the desired item name, users need to type a pattern into the search feature. Inside the typing process users may make some mistypes. Based on the problem, the writer tried to create a search box as the search feature inside an e-commerce system with a capability to look for item names, even if there are some accidental mistypes inside the user's typing process. The main purpose is to reduce the possibility of empty results after a searching process due to the user’s accidental mistypes. This research utilizes Rabin Karp Algorithm in order to look for the item names. Result of this research is that the Rabin Karp Algorithm can be implemented in a website-based e-commerce, but this method is slower than SQL as a method to search item names inside the same system. It happens because Rabin Karp requires a longer process than SQL to get the similarity percentage from each comparison. This research shows that k-gram value inside the algorithm affects the overall results with a condition where greater the value.
Rabin-Karp算法在电子商务搜索框特征中的实现(案例研究:新浪巴哈店)
在任何电子商务平台中,搜索功能都是在线业务的关键因素。为了查找所需的项目名称,用户需要在搜索功能中键入一个模式。在键入过程中,用户可能会输入一些错误的类型。基于这个问题,作者尝试在电子商务系统中创建一个搜索框作为搜索功能,该功能具有查找商品名称的功能,即使在用户键入过程中出现一些偶然的错误输入。其主要目的是减少由于用户偶然输入错误而导致搜索过程后出现空结果的可能性。本研究利用Rabin Karp算法来寻找商品名称。本研究的结果是,Rabin Karp算法可以在基于网站的电子商务中实现,但作为在同一系统内搜索商品名称的方法,该方法比SQL慢。这是因为Rabin Karp需要比SQL更长的过程才能从每个比较中获得相似度百分比。本研究表明,算法内部的k-gram值在值越大的情况下会影响整体结果。
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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