Bénédicte Le Grand

Topic Maps, RDF Graphs, and Ontologies Visualization

Information retrieval in current information systems has become very difficult. These systems’ complexity is due to the large volume of data, their lack of structure, and theirmultidimensionality. The SemanticWeb Initiative, proposedbyTimBerners-Lee (2001), aims atmaking computers process datamore efficiently by adding semantics— such as definitions or relationships—between resources on the Web. The Semantic Web is not intended to replace the current Web, but to extend it. Several levels compose the SemanticWeb, thus providing several degrees of expressivity:

Self-organised virtual communities: bridging the gap between web-based communities and P2P systems

In this paper, we argue for the benefits of enabling the self-organisation of virtual online communities, which today are mainly formed and operated by centrally managed web servers. However, self-organisation requires community members themselves to contribute different types of resources (e.g., bandwidth, storage, etc.), as in the case of Peer-to-Peer (P2P) systems. Unfortunately, this cooperation cannot be taken for granted. To address this obstacle, we introduce the notion of a cross-layer incentive mechanism. The main idea is to encourage the contribution of low-level resources using social incentives generated at a higher (social) layer. We believe that this type of incentive mechanism will play a central role toward the realisation of self-organised virtual communities and enable users to take advantage of the attractiveness and value of web-based communities, on the one hand, and the externalities and flexibility of P2P networks, on the other hand. We make a first step toward this direction: a) we categorise the different types of social incentives applicable in this context and b) we provide insights for the design of the appropriate social software required to map the behaviour of the participants at the resource-sharing layer with suitable rewards at the social layer.

Conceptual and Spatial Footprints for Complex Systems Analysis: Application to the Semantic Web

This paper advocates the use of Formal Concept Analysis and Galois lattices for complex systems analysis. This method provides an overview of a system by indicating its main areas of interest as well as its level of specificity/generality. Moreover, it proposes possible entry points for navigation by identifying the most significant elements of the system. Automatic filtering of outliers is also provided. This methodology is generic and may be used for any type of complex systems. In this paper, it is applied to theTopic Map formalism which can be used in the context of the Semantic Web to describe any kind of data as well as ontologies. The proposed Conceptual and Spatial Footprints allow the comparison of Topic Maps both in terms of content and structure. Significant concepts and relationships can be identified, as well as outliers; this method can be used to compare the underlying ontologies or datasets as illustrated in an experiment.

Citations among blogs in a hierarchy of communities: Method and case study ☆

In this paper we propose a generic methodology to study the correlation between nodes interactions in complex networks and their organization into groups called communities. We illustrate it on citations in a blog network. We first define a homophily probability evaluating the tendency of blogs to cite blogs from the same community. We then introduce the notion of community distance to capture whether a blog cites (or is cited by) blogs distant or not from its community. We analyze the distribution of distances corresponding to each citation link, and use it to build maps of relevant communities which help interpreting blogs interactions. This community-oriented approach allows us to study citation links at various abstraction levels, and conversely, to characterize communities with regard to their citation behaviour.

Topic Maps Visualization

The standards developed in the context of the Semantic Web provide means of adding semantics to the data available on the Web. XML is a first level of semantics which allows users to structure data with regard to their content rather than their presentation. However, more semantics can be added with the Resource Description Framework (RDF) (1999) or Topic Maps (1999) standards. RDF was developed by the World Wide Web Consortium (1999) whereas Topic Maps were defined by the International Organization for Standardization (1999). The Topic Map paradigm was recently adapted to the Web by the consortium TopicMaps.Org (2001). Both RDF and Topic Maps aim at representing knowledge about information resources by annotating them.

Navigation in huge information hierarchies application to network management

Complex information systems are very difficult to represent and users often have problems to find relevant information; this is the case with Web navigation: users feel “lost”. Data contained in such systems can often be organized hierarchically, thus it is possible to represent it as a tree. However, most visualizations are cluttered because of the amount of information to display. We propose to solve these problems by using Virtual Reality (VR) techniques. After reviewing different 3D visualization methods, we decided to use cone trees. Unfortunately, the enhancement provided by graphic methods is not sufficient when hierarchies are very large; in such cases, trees must be pruned with filtering methods. We chose to structure and manipulate data with the eXtensible Markup Language [19]. XML allows the description and organization of any type of information. In this paper, we show how we implemented these principles in the field of network management (for networks based on Synchronous Digital Hierarchy (SDH) equipment). The application we developed eases navigation in data extracted from the Management Information Base (MIB) and accelerates access to useful information. In the future, we will apply these results to Web navigation.

File diffusion in a dynamic peer-to-peer network

Many studies have been made on diffusion in the field of epidemiology, and in the last few years, the development of social networking has induced new types of diffusion. In this paper, we focus on file diffusion on a peer-to-peer dynamic network using eDonkey protocol. On this network, we observe a linear behavior of the actual file diffusion. This result is interesting, because most diffusion models exhibit exponential behaviors. In this paper, we propose a new model of diffusion, based on the SI (Susceptible / Infected) model, which produces results close to the linear behavior of the observed diffusion. We then justify the linearity of this model, and we study its behavior in more details.

A Conceptual Approach to Characterize Dynamic Communities in Social Networks: Application to Business Process Management

In the enterprise decision making process, specifically product design and CRM, the analysis of all the available and relevant customer information is a major task. In this paper we propose measures based on Formal Concept Analysis to determine conceptual proximity between people. We explain how FCA can support market analysts in their task of CRM marketing and management, with the automatic discovery of knowledge in large amounts of enterprise information (e.g. document collections). The temporal evolution of this proximity measure may be analyzed, and provides significant insights on trends and market behavior. This approach has been exemplified with a case study on Twitter with an emphasis on content dynamics within user communities.

DIFFUSION CASCADES: SPREADING PHENOMENA IN BLOG NETWORK COMMUNITIES

A diffusion cascade occurs when information spreads from one node to the rest of the network through a succession of diffusion events. So far diffusion phenomena have been mostly considered at a macroscopic scale i.e. by studying all nodes of the network. We give a complementary way to analyse network interactions by considering the problem at different scales. To that purpose, we use the community structure of the network to characterize diffusion between nodes (and between communities) and to identify interactions behaviour patterns.

Contextual and Conceptual Information Retrieval and Navigation on the Web

The goal of this chapter is to propose a methodology and tools to enhance information retrieval and navigation on the Web through contextual and conceptual help. This methodology provides users with an extended navigation space by adding a conceptual and a semantic layer above Web data. The conceptual layer is made of Galois lattices which cluster Web pages into concepts according to their common features (in particular their textual content). These lattices represent the Global Conceptual Context of Web pages. An additional navigation layer is provided by ontologies which are connected to the conceptual level through specific concepts of the lattices. Users may navigate transparently within each of these three layers and go from one to another very easily.