{"title":"The Use of Support Vector Machines When Designing a User-Defined Niche Search Engine","authors":"M. Jakovljevic, Howard Sommerfeld, A. Coleman","doi":"10.31341/JIOS.42.1.5","DOIUrl":null,"url":null,"abstract":"This study presents the construction of a niche search engine, whose search topic domain is to be user-defined. The specific focus of this study is the investigation of the role that a Support Vector Machine plays when classifying textual data from web pages. Furthermore, the aim is to establish whether this niche search engine can return results that are more relevant to a user than when compared to those returned by a commercial search engine Through the conduction of various experiments across a number of appropriate datasets, the suitability of the SVM to classify web pages has been proven to meet the needs of a niche search engine. A subset of the most useful webpage-specific features has been discovered, with the best performing feature being a web pages’ Text & Title component. The user defined niche search engine was successfully designed and an experiment showed that it returned more relevant results than a commercial search engine.\n","PeriodicalId":43428,"journal":{"name":"Journal of Information and Organizational Sciences","volume":" ","pages":""},"PeriodicalIF":0.3000,"publicationDate":"2018-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Information and Organizational Sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.31341/JIOS.42.1.5","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0
Abstract
This study presents the construction of a niche search engine, whose search topic domain is to be user-defined. The specific focus of this study is the investigation of the role that a Support Vector Machine plays when classifying textual data from web pages. Furthermore, the aim is to establish whether this niche search engine can return results that are more relevant to a user than when compared to those returned by a commercial search engine Through the conduction of various experiments across a number of appropriate datasets, the suitability of the SVM to classify web pages has been proven to meet the needs of a niche search engine. A subset of the most useful webpage-specific features has been discovered, with the best performing feature being a web pages’ Text & Title component. The user defined niche search engine was successfully designed and an experiment showed that it returned more relevant results than a commercial search engine.