{"title":"A framework for extraction of journal information from scientific publishers web site","authors":"Umamageswari Kumaresan, K. Ramanujam","doi":"10.1109/ISCO.2016.7726937","DOIUrl":null,"url":null,"abstract":"World Wide Web is a huge repository of information and the information is presented in the disparate formats which make automated processing a cumbersome task. Search engines are used to query the WWW. Students and scholars find it difficult to determine the appropriate journals for the research article publication since performing a keyword search using search engines like Google, Yahoo etc. presents them with a list of publication site where the user need to click through a series of link to reach the journal web site and go through the details of the journals like Impact Factor, SNIP etc. manually. Suppose if a publication web site is linked to hundreds of journal web sites matching the user's topic of interest, it poses a serious problem on part of the user to manually determine the most reputed journal for the publication of his/her research article. This paper proposes a framework for extraction of Journal information in a single interaction with the system.","PeriodicalId":320699,"journal":{"name":"2016 10th International Conference on Intelligent Systems and Control (ISCO)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 10th International Conference on Intelligent Systems and Control (ISCO)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISCO.2016.7726937","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
World Wide Web is a huge repository of information and the information is presented in the disparate formats which make automated processing a cumbersome task. Search engines are used to query the WWW. Students and scholars find it difficult to determine the appropriate journals for the research article publication since performing a keyword search using search engines like Google, Yahoo etc. presents them with a list of publication site where the user need to click through a series of link to reach the journal web site and go through the details of the journals like Impact Factor, SNIP etc. manually. Suppose if a publication web site is linked to hundreds of journal web sites matching the user's topic of interest, it poses a serious problem on part of the user to manually determine the most reputed journal for the publication of his/her research article. This paper proposes a framework for extraction of Journal information in a single interaction with the system.