An adaptive browsing-based approach for creating a photographic story

Pictures are often self-explanatory; they capture a moment in time. However, a single photo cannot represent the whole moment. The creation of photographic stories is a means to better preserve memories. Relying on the content-based and contextual metadata within digital photos we could assist users to explore their collection to create the stories with regard to their events and experiences. In this poster we propose a novel approach for supporting the self creation of stories with digital photographs. By incorporating an adaptive learning scheme to capture implicit user feedback, our approach supports content and context assisted browsing

Application and evaluation of multi-dimensional diversity

Traditional information retrieval (IR) systems mostly focus on finding documents relevant to queries without considering other documents in the search results. This approach works quite well in general cases; however, this also means that the set of returned documents in a result list can be very similar to each other. This can be an undesired system property from a user's perspective. The creation of IR systems that support the search result diversification present many challenges, indeed current evaluation measures and methodologies are still unclear with regards to specific search domains and dimensions of diversity. In this paper, we highlight various issues in relation to image search diversification for the ImageClef 2009 collection and tasks. Furthermore, we discuss the problem of defining clusters/subtopics by mixing diversity dimensions regardless of which dimension is important in relation to information need or circumstances. We also introduce possible applications and evaluation metrics for diversity based retrieval

User centred evaluation of a recommendation based image browsing system

In this paper, we introduce a novel approach to recommend images by mining user interactions based on implicit feedback of user browsing. The underlying hypothesis is that the interaction implicitly indicates the interests of the users for meeting practical image retrieval tasks. The algorithm mines interaction data and also low-level content of the clicked images to choose diverse images by clustering heterogeneous features. A user-centred, task-oriented, comparative evaluation was undertaken to verify the validity of our approach where two versions of systems { one set up to enable diverse image recommendation { the other allowing browsing only { were compared. Use was made of the two systems by users in simulated work task situations and quantitative and qualitative data collected as indicators of recommendation results and the levels of user's satisfaction. The responses from the users indicate that they nd the more diverse recommendation highly useful

Connected subgroups of SO(2,n) acting irreducibly on R^{2,n}

We classify all connected subgroups of SO(2, n) that act irreducibly on R^{2, n

Quark condensate for various heavy flavors

The quark condensate is calculated within the world-line effective-action formalism, by using for the Wilson loop an ansatz provided by the stochastic vacuum model. Starting with the relation between the quark and the gluon condensates in the heavy-quark limit, we diminish the current quark mass down to the value of the inverse vacuum correlation length, finding in this way a 64%-decrease in the absolute value of the quark condensate. In particular, we find that the conventional formula for the heavy-quark condensate cannot be applied to the c-quark, and that the corrections to this formula can reach 23% even in the case of the b-quark. We also demonstrate that, for an exponential parametrization of the two-point correlation function of gluonic field strengths, the quark condensate does not depend on the non-confining non-perturbative interactions of the stochastic background Yang-Mills fields.Comment: 12 pages, 2 figures, to appear in Eur. Phys. J.