The use of support vector machines when designing a user-defined niche search engine /Maria Jakovljevic, Howard Sommerfeld, Alfred Coleman.
Sažetak

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.