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Prioritizing a database of items in response to a given query object is a fundamental task in information retrieval and machine learning. We examine a specific realization of this problem in the context of a collection of biomedical articles. Given a query PubMed article, we investigate the problem of identifying and ranking recommended papers that are topically related to the query article. The two...
The plot (content or storyline of a story) may disappoint users who read review comments associated with items containing a story such as comics, novels, and movies. This paper proposes a new method for identifying sentences that include descriptions of the plot of the story. Conventional methods only use information based on the words contained in a target sentence, however, our new method uses contextual...
Web service compositions run in changing environment where different context events can arise to affect the execution of services. In order not to make service execution affected by context events, context-aware service composition becomes one of the major research trends. Service providers can develop context-aware services which can adapt their behaviors dynamically to execution contexts. However,...
This demo presents a framework for personalizing data access on the basis of the users' context and of the preferences they show while in that context. The system is composed of (i) a server application, which “tailors” a view over the available data on the basis of the user's contextual preferences, previously inferred from log data, and (ii) a client application running on the user's mobile device,...
Data-oriented applications have experienced a huge growth mainly in distributed settings. The increasing amount of available data has made it hard for users to find the information they need in the way they consider relevant. To help matters, a user-centric approach may be used to enhance query answering and, particularly, provide query personalization. In this work, we address the issue of personalizing...
When it comes to analysis and interpretation of the results of subjective QoE studies, one often witnesses a lack of attention to the diversity in subjective user ratings. In extreme cases, solely Mean Opinion Scores (MOS) are reported, causing the loss of important information on the user rating diversity. In this paper, we emphasize the importance of considering the Standard deviation of Opinion...
The present work reports results of perceptual experiments aimed to explore the human ability to recognize emotional expressions through the visual and auditory channel, investigating if one channel is more effective than the other to infer emotional information and if this effectiveness is affected by the cultural context and in particular by the language. To this aim American, French, and Italian...
This paper describes a convenient method of processing and contextualizing information extracted from social networking systems such as Myspace, Facebook or Hi5 users in real-time by using the Yahoo! Pipes feed mash-up service and formal concept analysis. Interests referring to media consumption (favorite movies, favorite music, favorite books or role models) declared by users can be expanded into...
A problem of diversified entity summarisation in RDF-like knowledge graphs, with limited ??presentation budget??, is formulated and studied. A greedy algorithm that adapts previous ideas from IR is proposed and preliminary but promising experimental results on real dataset extracted from IMDB database are presented.
With the vast increase in collection and storage of data, the problem of data summarization is most critical for effective data management. Since much of this data is categorical in nature, it can be viewed in terms of a Boolean matrix. Boolean matrix decomposition (BMD) has been used to provide concise and interpretable representations of Boolean data sets. A Boolean matrix can be expressed as a...
The ability to provide both rich and natural answers with respect to a given question, and clear explanations for failures, is a crucial aspect for a future generation of question answering systems able to interact with a user. We argue that such abilities are necessarily based on a deep analysis of the content of both the question and the answer, and propose an ontology-based approach to represent...
Context-aware plays an important role in modern society, especially to preference queries for user preferences depend on user current contexts. Popular mobile devices such as GPS, sensors and RFIDs produce context information to facilitate user right information acquisition. Due to that relational database is a powerful and sophisticated tool to manage large amount of data efficiently, context information...
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