This paper presents a probabilistic information retrieval framework in which the retrieval problem is formally treated as a statistical decision problem. In this framework, querie...
Existing retrieval models generally do not offer any guarantee for optimal retrieval performance. Indeed, it is even difficult, if not impossible, to predict a model’s empirica...
The purpose of contextual information retrieval is to make some exploration towards designing user specific search engines that are able to adapt the retrieval model to the variety...
In this paper, we present EgoIR, an approach for retrieving legal information based on ontologies; this approach has been developed with Legal Ontologies to be deployed within the...
In this paper, we proposed the learning resource ontology(LRO) models to formally describe learning content and learning context, respectively. In addition to utilizing the models...
Zongkai Yang, Tao Huang, Qingtang Liu, Xia Li, Bei...