EasyChoose: A Continuous Feature Extraction and Review Highlighting Scheme on Hadoop YARN

2018 IEEE 32nd International Conference on Advanced Information Networking and Applications (AINA) Pub Date : 2018-05-16 DOI:10.1109/AINA.2018.00145

Ming-Chang Lee, Jia-Chun Lin, Olaf Owe

{"title":"EasyChoose: A Continuous Feature Extraction and Review Highlighting Scheme on Hadoop YARN","authors":"Ming-Chang Lee, Jia-Chun Lin, Olaf Owe","doi":"10.1109/AINA.2018.00145","DOIUrl":null,"url":null,"abstract":"Today the Internet offers a massive amount of reviews and user experiences about a variety of products from different manufacturers, ranging from smartphones, automobiles, and home appliances to Internet services such as hotel booking and airplane booking. For a careful customer it is time-consuming to make good purchasing decisions due to a variety of similar products, lots of reviews for each product, and distributed reviews on the Internet. To alleviate this situation, this paper proposes EasyChoose, which is a distributed scheme based on Hadoop YARN to continuously collect product reviews from the Internet, extract representative product features based on previous customers' reviews, and highlight the main point of the reviews. In this paper, we use online hotel booking as an example to demonstrate the effectiveness of EasyChoose. The results show that EasyChoose is able to automatically extract representative product features and highlight reviews without losing the original meanings. Furthermore, EasyChoose is able to continuously provide such service to keep up with changes in recent customers' reviews.","PeriodicalId":239730,"journal":{"name":"2018 IEEE 32nd International Conference on Advanced Information Networking and Applications (AINA)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE 32nd International Conference on Advanced Information Networking and Applications (AINA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AINA.2018.00145","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 0

Abstract

Today the Internet offers a massive amount of reviews and user experiences about a variety of products from different manufacturers, ranging from smartphones, automobiles, and home appliances to Internet services such as hotel booking and airplane booking. For a careful customer it is time-consuming to make good purchasing decisions due to a variety of similar products, lots of reviews for each product, and distributed reviews on the Internet. To alleviate this situation, this paper proposes EasyChoose, which is a distributed scheme based on Hadoop YARN to continuously collect product reviews from the Internet, extract representative product features based on previous customers' reviews, and highlight the main point of the reviews. In this paper, we use online hotel booking as an example to demonstrate the effectiveness of EasyChoose. The results show that EasyChoose is able to automatically extract representative product features and highlight reviews without losing the original meanings. Furthermore, EasyChoose is able to continuously provide such service to keep up with changes in recent customers' reviews.

查看原文本刊更多论文

EasyChoose: Hadoop YARN上的连续特征提取和回顾突出显示方案

今天，互联网提供了大量关于不同制造商的各种产品的评论和用户体验，从智能手机、汽车、家用电器到酒店预订和飞机预订等互联网服务。对于一个细心的顾客来说，由于各种相似的产品，每个产品的大量评论，以及互联网上的分布式评论，要做出正确的购买决定是非常耗时的。为了缓解这种情况，本文提出了EasyChoose，这是一种基于Hadoop YARN的分布式方案，从互联网上持续收集产品评论，根据以往客户的评论提取有代表性的产品特征，并突出评论的要点。本文以在线酒店预订为例，对EasyChoose的有效性进行了验证。结果表明，EasyChoose能够在不丢失原始含义的情况下自动提取具有代表性的产品特征并突出显示评论。此外，EasyChoose能够持续提供此类服务，以跟上最近客户评论的变化。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

2018 IEEE 32nd International Conference on Advanced Information Networking and Applications (AINA)

自引率

0.00%

发文量