Section: Overall Objectives

Introduction

Context and Objectives

The Web is no longer perceived as a documentary system. Among its many evolutions, it became a virtual place where persons and software interact in mixed communities. These large scale interactions create many problems in particular the one of reconciling formal semantics of computer science (e.g. logics, ontologies, typing systems, etc.) on which the Web architecture is built, with soft semantics of people (e.g. posts, tags, status, etc.) on which the Web content is built.

Let us take a concrete and very common example of such semantic frictions on the Web. Many Web sites include forums, blogs, status feeds, wikis, etc. In other words, many Web sites include content management systems and rapidly build huge collections of information resources. As these collections grow, several tasks become harder to automate: search, notification, restructuring, navigation assistance, recommendation, trend analysis, etc. One of the main problems is the gap between the fairly informal way content is generated (e.g. plain text, short messages, free keywords) and the need for structured data and formal semantics to automate these functionalities (e.g. efficient indexes, domain thesauri). Mixed structures are starting to appear (e.g. structured folksonomies, hash tags, machine tags, etc.) but automating support in such collaboration spaces requires efficient and complete methods to fully bridge that gap.

As the Web becomes a ubiquitous infrastructure bathing all the objects of our world, this is just one example of the many frictions it will create between formal semantics and social semantics. This is why the Wimmics team proposes to study models and methods to bridge formal semantics and social semantics on the Web.

Research Topics

Our main challenge is to bridge formal semantics and social semantics.

From a formal modeling point of view, one of the consequences of the evolutions of the Web is that the initial graph of linked pages has been joined by a growing number of other graphs. This initial graph is now mixed with sociograms capturing the social network structure, workflows specifying the decision paths to be followed, browsing logs capturing the trails of our navigation, service compositions specifying distributed processing, open data linking distant datasets, etc.

Moreover, these graphs are not available in a single central repository but distributed over many different sources and some sub-graphs are public (e.g. dbpedia (http://dbpedia.org )) while other are private (e.g. corporate data). Some sub-graphs are small and local (e.g. a users’ profile on a device), some are huge and hosted on clusters (e.g. Wikipedia), some are largely stable (e.g. thesaurus of Latin), some change several times per second (e.g. social network statuses), etc.

Each type of network of the Web is not an isolated island. Networks interact with each other: the networks of communities influence the message flows, their subjects and types, the semantic links between terms interact with the links between sites and vice-versa, etc.

Not only do we need means to represent and analyze each kind of graphs, we also need the means to combine them and to perform multi-criteria analysis on their combination. Wimmics proposes to address this problem focusing on the characterization of (a) typed graphs formalisms to model and capture these different pieces of knowledge and (b) hybrid operators to process them jointly. We will especially consider the problems that occur in such structures when we blend formal stable semantic models and socially emergent and evolving semantics. We believe Wimmics can contribute to this understanding by combining two research domains:

• by proposing a multidisciplinary approach to analyze and model the many aspects of these intertwined information systems, their communities of users and their interactions;

• by formalizing and reasoning on these models to propose new analysis tools and indicators, and support new functionalities and better management.

International and industrial relations

We have a joint Ph.D with Alcatel Lucent Bell Labs and another joint Ph.D with SAP.

We collaborate with the LIRIMA International Lab and with the W3C.

We have an ongoing collaboration with the Heron laboratory, University of Montreal.

We obtained the first ANR LabCom (joint laboratory SMILK) in computer science with the company Viseo.