In this paper we propose a methodology to learn to extract domain-specific information from large repositories (e.g. the Web) with minimum user intervention. Learning is seeded b...
Fabio Ciravegna, Alexiei Dingli, David Guthrie, Yo...
Information Retrieval Systems aim at retrieving relevant documents according to the information needs which users express. Most Information Retrieval Systems focus on passage retr...
Named entity recognition is important for semantically oriented retrieval tasks, such as question answering, entity retrieval, biomedical retrieval, trend detection, and event and...
Valentin Jijkoun, Mahboob Alam Khalid, Maarten Mar...
— The University of California, Berkeley and the University of Liverpool in conjunction with the San Diego Supercomputer Center, are developing a framework for GridBased Digital ...
User modeling for information retrieval has mostly been studied to improve the effectiveness of information access in centralized repositories. In this paper we explore user model...