In this paper we study the problem of entity retrieval for news applications and the importance of the news trail history (i.e. past related articles) to determine the relevant en...
Gianluca Demartini, Malik Muhammad Saad Missen, Ro...
Retrieving entities instead of just documents has become an important task for search engines. In this paper we study entity retrieval for news applications, and in particular the...
Gianluca Demartini, Malik Muhammad Saad Missen, Ro...
Statistical language models can learn relationships between topics discussed in a document collection and persons, organizations and places mentioned in each document. We present a...
David Newman, Chaitanya Chemudugunta, Padhraic Smy...
† In this paper, we compare two methods for article summarization. The first method is mainly based on term-frequency, while the second method is based on ontology. We build an o...
The primary purpose of news articles is to convey information about who, what, when and where. But learning and summarizing these relationships for collections of thousands to mil...
David Newman, Chaitanya Chemudugunta, Padhraic Smy...