RnR:从在线评论和评级中提取基本原理

2010 IEEE International Conference on Data Mining Workshops Pub Date : 2010-12-13 DOI:10.1109/ICDMW.2010.167

Dwi A. P. Rahayu, S. Krishnaswamy, O. Alahakoon, C. Labbé

{"title":"RnR:从在线评论和评级中提取基本原理","authors":"Dwi A. P. Rahayu, S. Krishnaswamy, O. Alahakoon, C. Labbé","doi":"10.1109/ICDMW.2010.167","DOIUrl":null,"url":null,"abstract":"Review mining is a part of web mining which focuses on getting main information from user review. State of the art review mining systems focus on identifying semantic orientation of reviews and providing sentences or feature scores. There has been little focus on understanding the rationale for the ratings that are provided. This paper presents our proposed RnR system for extracting rationale from online reviews and ratings. We have implemented the system for evaluation on online reviews for hotels from TripAdvisor.com and present extensive experimental evaluation that demonstrates the improved computational performance of our approach and the accuracy in terms of identifying the rationale. This RnR system is available for testing from http://rnrsystem.com/RnRSystem","PeriodicalId":170201,"journal":{"name":"2010 IEEE International Conference on Data Mining Workshops","volume":"193 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"RnR: Extracting Rationale from Online Reviews and Ratings\",\"authors\":\"Dwi A. P. Rahayu, S. Krishnaswamy, O. Alahakoon, C. Labbé\",\"doi\":\"10.1109/ICDMW.2010.167\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Review mining is a part of web mining which focuses on getting main information from user review. State of the art review mining systems focus on identifying semantic orientation of reviews and providing sentences or feature scores. There has been little focus on understanding the rationale for the ratings that are provided. This paper presents our proposed RnR system for extracting rationale from online reviews and ratings. We have implemented the system for evaluation on online reviews for hotels from TripAdvisor.com and present extensive experimental evaluation that demonstrates the improved computational performance of our approach and the accuracy in terms of identifying the rationale. This RnR system is available for testing from http://rnrsystem.com/RnRSystem\",\"PeriodicalId\":170201,\"journal\":{\"name\":\"2010 IEEE International Conference on Data Mining Workshops\",\"volume\":\"193 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-12-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 IEEE International Conference on Data Mining Workshops\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICDMW.2010.167\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 IEEE International Conference on Data Mining Workshops","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDMW.2010.167","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 9

摘要

评论挖掘是web挖掘的一部分，侧重于从用户评论中获取主要信息。目前最先进的评论挖掘系统集中在识别评论的语义方向和提供句子或特征分数上。人们很少关注于理解所提供评级的基本原理。本文提出了我们提出的RnR系统，用于从在线评论和评级中提取基本原理。我们已经对TripAdvisor.com上的酒店在线评论进行了评估，并进行了广泛的实验评估，证明了我们的方法在计算性能上的改进，以及在识别基本原理方面的准确性。该RnR系统可从http://rnrsystem.com/RnRSystem进行测试

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

RnR: Extracting Rationale from Online Reviews and Ratings

Review mining is a part of web mining which focuses on getting main information from user review. State of the art review mining systems focus on identifying semantic orientation of reviews and providing sentences or feature scores. There has been little focus on understanding the rationale for the ratings that are provided. This paper presents our proposed RnR system for extracting rationale from online reviews and ratings. We have implemented the system for evaluation on online reviews for hotels from TripAdvisor.com and present extensive experimental evaluation that demonstrates the improved computational performance of our approach and the accuracy in terms of identifying the rationale. This RnR system is available for testing from http://rnrsystem.com/RnRSystem

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

2010 IEEE International Conference on Data Mining Workshops

自引率

0.00%

发文量