Overall Objectives
Scientific Foundations
Application Domains
New Results
Contracts and Grants with Industry
Other Grants and Activities

Section: Scientific Foundations

Keywords : Artificial Intelligence, Cognitive Sciences, Knowledge-Based System, Knowledge Acquisition, Knowledge Management, Knowledge Engineering, Knowledge representation, Knowledge Server, Corporate Memory, Ontology, Assistance to the User, Co-operation, Multiexpertise, Multiagent System, Conceptual Graph, Structured Document, XML, RDF, OWL, Semantic Web, Web architectures, Intranet, Corporate Web, Information Retrieval.


Knowledge Management (KM) is one of the key progress factors in organizations. It aims at capturing explicit and tacit knowledge of an organization, in order to facilitate its access, sharing out and reuse [57] . The considered organization can be an actual enterprise or a public organization, but it may also just consist of a given department or service; it can also be a group, or a community, or a virtual enterprise (made of members possibly stemming from different companies, but sharing a common interest). An organization is made up of people interacting for common objectives, in an internal environment and with an external environment. These persons may have different functions and tasks in the organization, different competencies, knowledge, opinions, and work methods and they may produce explicit traces of their activities. In the course of their individual or collective tasks, they may need to find people able to give them useful information or to find such helpful information in an information source (a document, a database, a CD-ROM, a film, etc.).

The members of the organization have individual knowledge (that may be explicit, implicit or tacit), as well as individual and collective objectives in the framework of their group or of the whole organization. The organization has global objectives and KM must be guided by a strategic vision. This vision enables the organization to determine the main organizational objectives for KM:

So a KM policy must rely on a deep understanding of what is the organization, what is its corporate culture, what kinds of knowledge exist (either individual, or collective in an internal group or collective in the whole organization), how can the organization intellectual capital be assessed, how can the past explain the present and help prepare the future, what can be the strategic objectives of KM and how they can be achieved according to the corporate culture and the environment of the end-users.

In an organization, knowledge can be individual or collective, it can be explicit, implicit, or tacit. In Nonaka's model [72] , organizational learning relies on transformation between these different types of knowledge. Collective knowledge can also emerge in a community of practice. Tacit knowledge can be transmitted without any language (e.g. through observations), but in order to be transmitted to other persons, explicit knowledge generally needs a medium (i.e. document, database, etc.) so that people can create their own knowledge either by interacting with each other or by retrieving information from explicit traces and productions of other colleagues' knowledge. Knowledge can also be distributed among several knowledge sources in the organization, with possibly heterogeneous viewpoints.

There are three significant aspects to be tackled:

The strategic vision for KM must enable the organization to select the KM priority needs and to orientate the choice of relevant techniques. One possible approach for KM is the building of a corporate memory or organizational memory (OM). A corporate memory can be defined as an ``explicit, disembodied, persistent representation of crucial knowledge and information in an organization, in order to facilitate their access, sharing and reuse by members of the organization, for their individual or collective tasks'' [57] . So different scopes and grains are possible for an organizational memory. Its building can rely on the following steps (cf. 1 ) [57] , with Management throughout all such steps: (1) Detection of needs, (2) Construction, (3) Diffusion, (4) Use, (5) Evaluation, (6) Maintenance and evolution, all these steps being supervised by management.

Figure 1. Life cycle of corporate memory

An organizational memory can be modeled from several perspectives: for whom, why, what, how, when, who and where. It aims at delivering the right knowledge to the right person at the right time in the right format, in order to enable the right action / decision. Although KM is an issue in human resource management and enterprise organization beyond any specific technological issues, there are important aspects that can be supported or even enabled by intelligent information systems. Especially artificial intelligence (AI) and related fields provide solutions for parts of the overall KM problem. Several techniques can be adopted for the building of an OM. The choice of a solution depends on the type of organization, its needs, its culture and must take into account people, organization and technology.

Several research topics can be useful for OM design:

The Acacia approach relies on the analogy between the resources of a corporate memory and the resources of the Web. We consider that a corporate memory can be materialized in a corporate semantic web, that consists of [57] , [58] :

The underlying research topics are:

From knowledge representation viewpoint, we rely on the Sowa's conceptual graphs formalism, more precisely simple conceptual graphs extended by graph rules (Simple Graph SG-family proposed by LIRMM). The CG model enables to represent knowledge through bipartite labelled graphs using the vocabulary offered by a domain ontology. Reasoning on CG can be performed through graph operators such as projection. Reasoning on CG is logically founded since projection is sound and complete w.r.t. deduction in first-order logics, for simple graphs, for nested graphs and for more general graphs equivalent to first-order logics.


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