T. Kawada, Tetsuji Nakagawa, Kentaro Inui, S. Kurohashi
{"title":"Topic relatedness in evaluative information extraction","authors":"T. Kawada, Tetsuji Nakagawa, Kentaro Inui, S. Kurohashi","doi":"10.1145/1667780.1667804","DOIUrl":null,"url":null,"abstract":"The task of extracting opinions/evaluations related to a given topic from a large number of documents such as Web documents is crucial for developing an automatic evaluation finding system, which can handle a wide variety of topics as input. In this paper, we discuss the topic relatedness of extracted evaluation through analysis of a corpus we developed. We suggest here that the semantic relationship between the target of each extracted evaluation and a given topic helps in judging topic relatedness. In addition, we point out other factors that are beyond the analysis of topic-target relations for judging the topic relatedness of evaluation.","PeriodicalId":103128,"journal":{"name":"Proceedings of the 3rd International Universal Communication Symposium","volume":"19 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 3rd International Universal Communication Symposium","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/1667780.1667804","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
The task of extracting opinions/evaluations related to a given topic from a large number of documents such as Web documents is crucial for developing an automatic evaluation finding system, which can handle a wide variety of topics as input. In this paper, we discuss the topic relatedness of extracted evaluation through analysis of a corpus we developed. We suggest here that the semantic relationship between the target of each extracted evaluation and a given topic helps in judging topic relatedness. In addition, we point out other factors that are beyond the analysis of topic-target relations for judging the topic relatedness of evaluation.