Content marketing objectives are to create and distribute valuable, relevant, and consistent content to attract and retain a clearly defined targeted audience. To earn credibility, the brand creates messages that are useful and make a positive difference in the lives of the prospects. As content items, at the most basic level, is information, this paper will present how semantic information fusion operator introduced by [17] becomes a cornerstone of an overall content marketing tool chain. After introducing Mathematical Morphology framework, this operator which relies on a conceptual graphs, will be sound defined. Some underlying morphological properties such as dilation or idempotence are demonstrated, and we explain how these properties can be used within semantic information fusion.

The wide adoption of social and connected tools in organizations lead them to think again about their behavior and to consider the indexing of the resources users can now produce with such tools, in the same way they index other documentary resources. This indexing process has to be done along the core frame of reference of the organization. We present in this paper the model of a system which permit the indexing with the help of an ontology of both documentary resources or those produced on a social platform resources.

Motivated by the problem of computing trajectories of a set of aircraft in their final descent, we introduce the K king problem, a dramatic simplification of the initial problem in which time and space are discretized. A constraint-based model relying on several specific global constraints is introduced. Computational experiments are reported and show that small instances of this problem can be solved in reasonable time.

The first challenge in crisis response management is the early damage and needs assessment based on all incoming information from various sources such as on field deployed sensors or human observations. Likewise, it is important for an efficient crisis response management to make sure that ambiguous terminology is clearly defined, and methodologies and indicators explained. To support the damage assessment, all the relevant items need to be formally modelled and represented in a machine-readable format. For that purpose, a formal ontology would provide the basis for the verbal description of the current situation understanding as well as the underlying semantics for any fusion related tasks and display operations.

One of the key issues of strategic intelligence within a crisis situation is to build an early assessment of the situation, based on a context sensitive information interpretation and through a well constructed situation representation. Our proposal is based on the conjunction of a conceptual modelling to represent situations out of document analysis and a reactive rule-based modelling to analyze them according to a domain knowledge and a goal. This paper focuses on this situation analysis process. But we present our global approach and sum-up the situation representation and its objectives. We introduce the complex event processing formalism used for the analysis and dynamic recognition of such situations. We illustrate our approach through a case study taken from what happened during the energy crisis in California in 2001

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This paper presents a technique to map automatically a complete digital signal processing (DSP) application onto a parallel machine with distributed memory. Unlike other applications where coarse or medium grain scheduling techniques can be used, DSP applications integrate several thousand of tasks and hence necessitate fine grain considerations. Moreover finding an effective mapping imperatively require to take into account both architectural resources constraints and real time constraints. The main contribution of this paper is to show how it is possible to handle and to solve data partitioning, and fine-grain scheduling under the above operational constraints using concurrent constraints logic programming languages (CCLP). Our concurrent resolution technique undertaking linear and nonlinear constraints takes advantage of the special features of signal processing applications and provides a solution equivalent to a manual solution for the representative panoramic analysis (PA) application.

This paper presents a new method of texture characterization, recognition and defect detection in textures, based on mathematical morphology transformations: structural opening and top-hat. The structural opening and its properties of invariance allow the extraction of primitive patterns from a texture, some kind of "textons" which entirely characterize it. As a result, defect detection can be performed by a top-hat transformation for a similar textural set with defects, and texture recognition can be led by a reference set.