Pseudo-relevance feedback is an effective technique for improving retrieval results. Traditional feedback algorithms use a whole feedback document as a unit to extract words for ...
A novel method for simultaneous keyphrase extraction and generic text summarization is proposed by modeling text documents as weighted undirected and weighted bipartite graphs. Sp...
This article describes our participation at the Domain-Specific track. We used the Xtrieval framework [2], [3] for the preparation and execution of the experiments. The translatio...
We propose an analytic method to evaluate groupware design. The method was inspired by GOMS, a well-known approach to analyze usability problems with single-user interfaces. GOMS h...
In this paper, we present the Gauss-Newton method as a unified approach to optimizing non-linear noise compensation models, such as vector Taylor series (VTS), data-driven parall...