In this paper we will describe Berkeley's approach to the ImageCLEF Wikipedia Retrieval task for 2010. Our approach to this task was primarily to use text-based searches on th...
Abstract This vandalism detector uses features primarily derived from a wordpreserving differencing of the text for each Wikipedia article from before and after the edit, along wit...
Abstract. Most Information Retrieval models take documents as Bagof-Words and are thereby bound to the language of the documents. In this paper, we present an approach using Linked...
In this paper, we present the LIP6 annotation models for the ImageCLEFannotation 2010 task. We study two methods to train and merge the results of different classifiers in order to...
Ali Fakeri-Tabrizi, Sabrina Tollari, Nicolas Usuni...
Abstract. Our participation at ResPubliQA 2010 was based on applying an Information Retrieval (IR) engine of high performance and a validation step for removing incorrect answers. ...
Abstract. In this paper, we describe an approach for the automatic modality classification in medical image retrieval task of the 2010 CLEF cross-language image retrieval campaign ...
A good clustering performance depends on the quality of the distance function used to asses similarity. In this paper we propose a pairwise document coreference model to improve pe...
Iustin Dornescu, Constantin Orasan, Tatiana Lesnik...
We reported some experiments conducted by our members in the SIG team at the IRIT laboratory in the CLEF medical retrieval task, namely ImageCLEFmed. In 2010, we are particularly i...
This paper describes UAIC1 's Question Answering systems participating in the ResPubliQA 2010 competition, designed to answer questions on a juridical corpora in Romanian, Eng...
Adrian Iftene, Diana Trandabat, Maria Husarciuc, M...