The Use of Support Vector Machines When Designing a User-Defined Niche Search Engine

  • Maria Jakovljevic University of South Africa (UNISA)
  • Howard Sommerfeld Software developer, entrepreneur
  • Alfred Coleman University of South Africa, Florida Campus
Keywords: Support vector machine, search engine, text classification and processing, information retrieval


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.

Author Biographies

Maria Jakovljevic, University of South Africa (UNISA)

School of Computing, College of Science, Engineering and Technology (CSET), UNISA, Academic Associate


Howard Sommerfeld, Software developer, entrepreneur
BSc honours, Compute Science, University of the Witwatersrand, Johannesburg, South Africa
Alfred Coleman, University of South Africa, Florida Campus
Associate Professor, School of Computing, College of Science, Engineering and Technology (CSET), University of South Africa