Performance and Scalability Testing Methodology for a Semantic Personalized Search Engine.
Leyla Zhuhadar, Olfa Nasraoui · IKE · 2010
The Internet Systems Consortium1 (ISC) shows, in its latest Internet global statistics, that the number of hosts advertised in the DNS is equal to 732,740,444 (January, 2010); whereas, the number of Internet Users is around 1,802 Million and there are, approximately 4.2 Billion Mobile Users and 1.3 Billion PC Users2 (December, 2009). This proliferation of data, users, and mobile devices pushed the Information Retrieval (IR) community harder to find solutions to relate, organize, and control this information in a more efficient way. The work presented in this paper describes an evaluation of the performance of a hybrid recommender retrieval model that can filter information based on a user’s needs. We evaluate the scalability of the HyperManyMedia search engine by evaluating the crawling speed, more specifically, the time needed for the crawler to crawl the server.