Parallel texts (bitexts) have properties that distinguish them from other kinds of parallel data. First, most words translate to only one other word. Second, bitext correspondence is noisy. This article presents methods for biasing statistical translation models to reflect these properties. Analysis of the expected behavior of these biases in the presence of sparse data predicts that they will ...

The research work presented is about helping teachers-designers in focusing on instructional design activities when using widely spread Learning Management System. We originally propose to focus on the implicit LMS pedagogical language and to exploit it outside of the LMS by well-suited instructional design tools. We concretely propose to follow a Domain Specific Modeling approach in order to f...

Online sharing platforms often rely on collaborative tagging systems for annotating content. In this way, users themselves annotate and describe the shared contents using textual labels, commonly called tags. These annotations typically suffer from a number of issues such as tag scarcity or ambiguous labelling. Hence, to minimise some of these issues, tag recommendation systems can be employed ...

One important intention of human-centered information visualization is to represent huge amounts of abstract data in a visual representation that allows even users from foreign application domains to interact with the visualization, to understand the underlying data, and finally, to gain new, application-related knowledge. The visualization will help experts as well as non-experts to link previ...

The allocation and disposal of memory is a ubiquitous operation in most programs. Rarely do programmers concern themselves with details of memory allocators; most assume that memory allocators provided by the system perform well. Yet, in some applications, programmers use domain-specific knowledge in an attempt to improve the speed or memory utilization of memory allocators. In this paper, we d...

Coreference resolution is the problem of clustering mentions into entities and is very critical for natural language understanding. This paper studies the problem of coreference resolution in the context of the newly emerging domain of Electronic Health Records (EHRs). The commonly used “best-link” model for coreference resolution considers only the scores from a pairwise classifier in selectin...

One of the most recent opinion mining research directions falls in the extraction of polarities referring to specific entities (called “aspects”) contained in the analyzed texts. The detection of such aspects may be very critical especially when the domain which documents belong to is unknown. Indeed, while in some contexts it is possible to train domain-specific models for improving the effect...

The Internet can be an effective alternative for data collection for multicenter studies. It has major advantages over the "classical" method of using paper and traditional ("snail") mail. We developed an Internet site and implemented collection of data for a multicenter study of ethical decision-making. The Web site was built with Microsoft FrontPage as the authoring tool. Database management ...

One drawback with using plan recognition in adversarial games is that often players must commit to a plan before it is possible to infer the opponent’s intentions. In such cases, it is valuable to couple plan recognition with plan repair, particularly in multi-agent domains where complete replanning is not computationally feasible. This paper presents a method for learning plan repair policies ...

Domain language model (LM) adaptation consists in re-estimating probabilities of a baseline LM to better match the peculiarities of a given broad topic of interest. To do so, a yet common strategy consists in retrieving adaptation texts from the Web based on a given domain representative seed text. In this report, we extensively study this process by analyzing the impact of numerous parameters....