{"title":"Instant Web Retrieval for Instance-Attribute Queries","authors":"Yi-Ting Chou, Shui-Lung Chuang, Xuanhui Wang","doi":"10.1109/WI.2007.67","DOIUrl":null,"url":null,"abstract":"As the Web becomes the major information source of our daily activities, tools for finding various information on it are indispensable. This paper addresses theWeb retrieval of instance-attribute information, e.g., the contact addresses and research interests (attributes) of faculty and students (instances). This kind of information need is very common but cannot be directly supported by current keywordmatching-based search engines. People commonly use a two-phase search: First, locate the candidate pages, e.g., a faculty page, and then search within them for the desired information, e.g., contact information. Based on the stimulation of such human search behavior, we design a retrieval engine, upon general search engines, to help find the instance-attribute information from the Web. The experiment on several faculty members has shown the feasibility of the approach.","PeriodicalId":192501,"journal":{"name":"IEEE/WIC/ACM International Conference on Web Intelligence (WI'07)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE/WIC/ACM International Conference on Web Intelligence (WI'07)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WI.2007.67","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
Abstract
As the Web becomes the major information source of our daily activities, tools for finding various information on it are indispensable. This paper addresses theWeb retrieval of instance-attribute information, e.g., the contact addresses and research interests (attributes) of faculty and students (instances). This kind of information need is very common but cannot be directly supported by current keywordmatching-based search engines. People commonly use a two-phase search: First, locate the candidate pages, e.g., a faculty page, and then search within them for the desired information, e.g., contact information. Based on the stimulation of such human search behavior, we design a retrieval engine, upon general search engines, to help find the instance-attribute information from the Web. The experiment on several faculty members has shown the feasibility of the approach.