We develop a method for predicting query performance by computing the relative entropy between a query language model and the corresponding collection language model. The resultin...
In this paper we study the problem of finding most topical named entities among all entities in a document, which we refer to as focused named entity recognition. We show that th...
Abstract. This paper describes the participation of Dublin City University in the CriES (Cross-Lingual Expert Search) pilot challenge. To realize expert search, we combine traditio...
This work explores the problem of cross-lingual pairwise similarity, where the task is to extract similar pairs of documents across two different languages. Solutions to this pro...
This paper proposes a new method for displaying large-scale tag clouds. We use a topographical image that helps users to grasp the relationship among tags intuitively as a backgro...
Ko Fujimura, Shigeru Fujimura, Tatsushi Matsubayas...