The novelty task consists of finding relevant and novel sentences in a ranking of documents given a query. In the literature, different techniques have been applied to address this problem. Nevertheless, little is known about Language Models for novelty detection and, especially, the effect of smoothing on the selection of novel sentences. Language Models can be used to study novelty and releva...

Ranking blog posts that express opinions regarding a given topic should serve a critical function in helping users. We explored a couple of methods for opinion retrieval in the framework of probabilistic language models. The first method combines topic-relevance model and opinion-relevance model, at document level, that captures topic dependence of the opinion expressions. The second method com...

This thesis presents a new general probabilistic framework for text retrieval based on Bayesian decision theory. In this framework, queries and documents are modeled using statistical language models, user preferences are modeled through loss functions, and retrieval is cast as a risk minimization problem. This risk minimization framework not only unifies several existing retrieval models withi...

Speech recognition transcripts are far from perfect; they are not of sufficient quality to be useful on their own for spoken document retrieval. This is especially the case for conversational speech. Recent efforts have tried to overcome this issue by using statistics from speech lattices instead of only the 1best transcripts; however, these efforts have invariably used the classical vector spa...

Ranking documents or sentences according to both topic and sentiment relevance should serve a critical function in helping users when topics and sentiment polarities of the targeted text are not explicitly given, as is often the case on the web. In this paper, we propose several sentiment information retrieval models in the framework of probabilistic language models, assuming that a user both i...

We adapt the aliasing constraints approach for designing a flexible typing of evolving objects. Types are singleton types (addresses of objects, as a matter of fact) whose relevance is mainly due to the sort of safety property they guarantee. In particular we provide a type system for an imperative object based calculus with delegation and which supports method and delegate overriding, addition...

Abstract. In this work we present a transcoding framework and an object-based technique to adapt live and stored videos to the user bandwidth and resources capabilities. Multiple transcoding policies are reviewed and a performance evaluation metric based on the Weighted Mean Square Error that allows different classes of relevance is presented. We present results for different transcoding polici...

This paper addresses the issue of identifying persons with expertise knowledge on a given topic. Traditional methods usually estimate the relevance between the query and the support documents of candidate experts using, for example, a language model. However, the language model lacks the ability of identifying semantic knowledge, thus results in some right experts cannot be found due to not occ...

The author investigated the conditions under which a congruent or incongruent orientation word affects processing of the orientation of visual objects. Participants named the orientation of a rectangle that partially occluded another rectangle. Congruent or incongruent orientation words appeared in the relevant object, in the irrelevant object, or in the background. There were two main results....

At present, the software engineering community places emphasis on the relevance of understanding the organizational context before starting the development of an information system. In this context, several research works focus on proposing mechanisms to generate information systems from early requirements specifications in an agent-based approach. However, only a few research works offer a gui...