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...
Semantic web researchers tend to assume that XML Schema and OWL-S are the correct means for representing the types, structure, and semantics of XML data used for documents and int...
Andruid Kerne, Zachary O. Toups, Blake Dworaczyk, ...
We study a novel problem of social context summarization for Web documents. Traditional summarization research has focused on extracting informative sentences from standard docume...
Zi Yang, Keke Cai, Jie Tang, Li Zhang, Zhong Su, J...
In this paper we present a novel framework for extracting the ratable aspects of objects from online user reviews. Extracting such aspects is an important challenge in automatical...
Crisis Management and Disaster Recovery have gained immense importance in the wake of recent man and nature inflicted calamities. A critical problem in a crisis situation is how t...
Li Zheng, Chao Shen, Liang Tang, Tao Li, Steven Lu...