We propose an approach to build a subspace representation for documents. This more powerful representation is a first step towards the development of a quantum-based model for Info...
Benjamin Piwowarski, Ingo Frommholz, Yashar Moshfe...
Abstract. Learning To Rank (LTR) techniques aim to learn an effective document ranking function by combining several document features. While the function learned may be uniformly ...
Text clustering is an established technique for improving quality in information retrieval, for both centralized and distributed environments. However, for highly distributed envir...
In this paper, we complement the term frequency, which is used in many bag-of-words based information retrieval models, with information about the semantic relatedness of query and...
Abstract. Finding near-duplicate images is a task often found in Multimedia Information Retrieval (MIR). Toward this effort, we propose a novel idea by bridging two seemingly unrel...
Hung-sik Kim, Hau-Wen Chang, Jeongkyu Lee, Dongwon...
Collaborative filtering is one of the most effective techniques for making personalized content recommendation. In the literature, a common experimental setup in the modeling phase...
Topic models have been studied extensively in the context of monolingual corpora. Though there are some attempts to mine topical structure from cross-lingual corpora, they require ...
User-generated short documents assume an important role in online communication due to the established utilization of social networks and real-time text messaging on the Internet. ...
Ranking a set retrieval systems according to their retrieval effectiveness without relying on relevance judgments was first explored by Soboroff et al. [13]. Over the years, a numb...