Recent work in supervised learning of term-based retrieval models has shown significantly improved accuracy can often be achieved via better model estimation [2, 10, 11, 17]. In ...
Informationretrieval systems typically weight the importance of search terms according to document and collection statistics (such as by using tf idf scores, where less commonterm...
This paper investigates the problem ofautomatically learning declarative models of information sources available on the Internet. We report on ILA, a domain-independent program th...
Term-weighting functions derived from various models of retrieval aim to model human notions of relevance more accurately. However, there is a lack of analysis of the sources of e...
In this paper, we describe experiments into the application of term weighting techniques from text retrieval to support the automatic identification of significant locations from ...
Zhengwei Qiu, Cathal Gurrin, Aiden R. Doherty, Ala...