从旅游行业的在线评论中提取功能请求

IF 0.6 4区综合性期刊 Q3 MULTIDISCIPLINARY SCIENCES

Acta Scientiarum-technology Pub Date : 2022-03-11 DOI:10.4025/actascitechnol.v44i1.58658

Superna Kumari, Z. Memon

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引用次数: 3

摘要

在产品开发之前，需求工程(RE)是了解客户对任何产品偏好的基本需求。传统上，可再生能源是通过几种方式进行的，特别是通过进行访谈，问卷调查，调查等，但这些方法提供的数据量有限。由于用户对任何类型的应用程序的偏好因国家而异，因此手动收集来自不同国家的用户需求是非常忙碌和耗时的。随着互联网的广泛使用，大量的客户评论可以在网上获得，无需人工操作即可获得对任何产品的需求。在线用户评论可以分为三种类型:用户体验、bug和功能请求。在这三种类型中，功能请求对于涉众(分析师/需求工程师)获取每个应用程序的需求非常有用。为此，提出了一种从旅游行业移动应用评论中提取特征请求的方法。本文从Google Play Store和Apple Store中提取了5个国家的4类旅游行业移动应用。对于每个类别，我们都考虑了来自5个不同移动应用程序的数据。由于来自不同国家的用户的评论是用他们各自的语言，这些评论被翻译成一种标准语言，即英语，然后从这些评论中提取功能请求。之后，从用户评论中检索特征，并对提取的特征执行主题建模，因为一个或多个特征可以在一个主题下建模。为了了解用户对任何特征请求的意见，还对特征请求句子进行了情感分析。这些特性请求也被分为功能性需求和非功能性需求，因为它对应用程序开发人员改进或维护产品以更好地为应用程序用户提供便利非常有用

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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Extracting feature requests from online reviews of travel industry

Before product development, Requirement Engineering (RE) is the fundamental need to know customer preferences for any product. Traditionally, RE is carried out in several ways, particularly by conducting interviews, questionnaires, surveys etc. but these methods provide limited amount of data. As user’s preferences vary from country to country for any type of application, it is very hectic and time consuming to collect user requirements from different countries manually. As the internet is widely used now a days, a large number of customer’s reviews are available online that can be used to obtain the requirements for any product without manual work. Online customer reviews can be divided into three types: user experience, bugs and feature requests. Among these 3 categories, feature requests can be very useful for stakeholders (analysts/ requirements engineers) to acquire the requirements of each application. So, the approach is proposed for feature requests extraction from mobile application reviews of travel industry. In this paper, 4 categories of mobile apps of travel industry belonging to 5 countries have been extracted from Google Play Store and Apple Store. For each category, data from 5 different mobile applications have been considered. Since, the review of users from different countries is in their respective language, those reviews are translated into a standard language i.e. English, and then feature requests from these reviews have been extracted. After that, features are retrieved from user reviews and topic modeling is performed on extracted features since one or more features can be modelled under one topic. To know the opinions of users for any feature request, sentiment analysis is also performed on feature request sentences. These feature requests are also classified as Functional and Non-functional Requirements since it is very useful for application developers to improve or maintain the product to better facilitate the application users

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来源期刊

Acta Scientiarum-technology 综合性期刊-综合性期刊

CiteScore

1.40

自引率

12.50%

发文量

审稿时长

6-12 weeks

期刊介绍： The journal publishes original articles in all areas of Technology, including: Engineerings, Physics, Chemistry, Mathematics, Statistics, Geosciences and Computation Sciences. To establish the public inscription of knowledge and its preservation; To publish results of research comprising ideas and new scientific suggestions; To publicize worldwide information and knowledge produced by the scientific community; To speech the process of scientific communication in Technology.