We harvest training images for visual object recognition by casting it as an IR task. In contrast to previous work, we concentrate on fine-grained object categories, such as the l...
Abstract We deal with a problem faced by scholars every day: identifying relevant papers on a given topic. In particular, we focus on the scenario where a scholar can come up with ...
Matthias Hagen, Anna Beyer, Tim Gollub, Kristof Ko...
Abstract. In this paper, we explore a geo-spatial learning-to-rank framework for identifying local experts. Three of the key features of the proposed approach are: (i) a learning-b...
The surge of opinionated on-line texts provides a wealth of information that can be exploited to analyze users’ viewpoints and opinions on various topics. This article presents V...
The presentation of news articles to meet research needs has traditionally been a document-centric process. Yet users often want to monitor developing news stories based on an eve...
Term graphs constructed from document collections as well as external resources, such as encyclopedias (DBpedia) and knowledge bases (Freebase and ConceptNet), have been individual...
Automatic query reformulation refers to rewriting a user’s original query in order to improve the ranking of retrieval results compared to the original query. We present a gener...
The availability of data spanning different epochs has inspired a new analysis of cultural, social, and linguistic phenomena from a temporal perspective. This paper describes the...
Pierpaolo Basile, Annalina Caputo, Giovanni Semera...
Abstract. In the last decade, a number of nonsense automatically-generated scientific papers have been published, most of them were produced using probabilistic context free gramm...