In this paper, we propose a semi-supervised learning approach for classifying program (bot) generated web search traffic from that of genuine human users. The work is motivated by...
Hongwen Kang, Kuansan Wang, David Soukal, Fritz Be...
In this paper, we propose to model the blended search problem by assuming conditional dependencies among queries, VSEs and search results. The probability distributions of this mo...
This paper aims to propose solutions to the issue of ontology visualization, by presenting intuitive and userfriendly ontology editing and visualization environments mainly orient...
Nadia Catenazzi, Lorenzo Sommaruga, Riccardo Mazza
Abstract. The rapid increase on the circulation of data over the web has highlighted the need for distributed storage of Internet-accessible information due to the rapid increase o...
As the number of non-English resources available on the Web is increasing rapidly, developing information retrieval techniques for non-English languages is becoming an urgent and ...