Several applications require the matching of user profiles, e.g., job recruitment or dating systems. In this paper we present a logical framework for specifying user profiles that allows profile description to be incomplete in the parts that are unavailable or are considered irrelevant by the user. We present an algorithm for matching demands and supplies of profiles, taking into account incompleteness of profiles and incompatibility between demand and supply. We specialize our framework to dating services; however, the same techniques can be directly applied to several other contexts.

Abstract: Modeling competences is an integral part of many Human Resource (HR) and e-Learning related activities. HR departments use competence descriptions to define requirements needed for performing specific tasks or jobs. The same competences are acquired by employees and applicants by e.g. experience or certifications. Typically, HR departments need to match such required and acquired competences in order to find suitable candidates. In e-Learning a similar situation arises. Curricula or training programmes need to describe prerequisites that must be fulfilled before joining and the competences that will be acquired after successful completion. This paper analyses the limitations and extends existing approaches for modeling competences in order to allow (semi-)automatic competence matching. 1

Abstract: Knowledge management is characterized by many different activities ranging from the elicitation of knowledge to its storing, sharing, maintenance, usage and creation. Skill management is one of such activities, with its own peculiarities, as it focuses on full exploitation of knowledge individuals in an organization have, in order to carry out at best given tasks. In this paper a semantic-based automated Skill Management System is proposed, which supports competences search and creation. The system implements an approach exploiting the formalism and the reasoning services provided by Description Logics. The approach embeds also non standard Description Logics reasoning services to extend the set of provided features. Here we present main characteristics of our system and focus on a novel algorithm exploiting advanced inference services for the one-to-one assignment of a set of individuals to a set of tasks, endowed of logical explanation features for missing/conflicting skills.

Abstract: This paper is focused on the problem of skill matching in an organizational context. We endow the classical weighted bipartite graph approach with a semantic based assignment of arcs weight and we describe a skill matching system implementing the approach. The system takes curricula and project specifications as inputs and extracts from them individual profiles respectively offered and requested, according to an ontology modeling skill management context. The suitability of each available individual to each task to assign is evaluated based on an algorithm whose returned scores are used as arc weights. As a result the semantics of profile descriptions is taken into account in the assignment process.

Abstract. Several applications require the matching of user profiles, e.g., job recruitment or dating systems. In this paper we present a logical framework for specifying user profiles that allows profile description to be incomplete in the parts that are unavailable or are considered irrelevant by the user. We present an algorithm for matching demands and supplies of profiles, taking into account incompleteness of profiles and incompatibility between demand and supply. We specialize our framework to dating services; however, the same techniques can be directly applied to several other contexts. 1

Abstract: A logic-based approach to the semantic-based composition of task oriented teams using candidates profiles and task description is presented, in the framework of a skill management system. The selection process exploits Concept Covering, carried out using non-standard inference services in Description Logics. The approach is motivated andcomparedwithothersemantic-orientedproposals.

In the paper we present the importance of collaboration between researchers for the improvement of their creativity. A unified methodology to support collaboration strategies of researchers and research teams based on knowledge sharing is introduced. We argue that a defined methodology together with an efficient technological system supporting the methodology should improve the creativity of research teams and consequentially facilitate the development. Based on the required functionalities of such a system, we propose the semantic web as the underlying technology. It is indicated how the semantic web technologies could provide the necessary solutions for the integration of data resources, the transformation of data into valuable knowledge, the effective use of knowledge by intelligent information services and knowledge sharing both within an organization and inter-organizationally. Finally, the prototype architecture of an intelligent agent within a database system is outlined, which serves as an information integration mechanism. Povzetek: Semantična integracija virov znanja v podporo sodelovanju. 1

Searching and comparing products in electronic markets is still a challenging problem. On one hand, the expressive power of the search mechanisms offered by the existing electronic markets is too limited. On the other hand, the price is mostly the only criterium of comparing the results with each other. In this paper, we introduce SMART (Semantic Matchmaking Portal) to improve searching and comparing products in electronic markets. Therefore, we present a novel matchmaking approach based on fuzzy descriptions that provide a more expressive search mechanism that is closer to human reasoning and aggregates multiple search criteria to a single value (ranking of an offer relative to the query), thus enabling better selection of offers that should be considered for the negotiation.

Abstract: In knowledge intensive companies intellectual capital assumes a crucial role in the organizational strategy and, as any other strategical asset, it needs to be scheduled to achieve sustainable competitive advantage. When the required knowledge is a resource available inside the company, its assignment represents a key success factor, which many research efforts are devoted to. On the other side, when the needed competence is unavailable within the company, training programs may be seen as methods to strengthen such a strategic asset. In this paper we show a semantic-based integrated system aimed at supporting both the assignment of available intellectual resources in three different multiplicity scenarios and the search for training programs ad-hoc composed to fill possible knowledge gaps.

Finding rapidly suitable experts in an organization to compose a team able to solve specific tasks is a typical problem in large consulting firms. In this paper we present a Description Logics approach to the semantic-based composition of ad-hoc teams based on individuals skill profiles and on task description. The selection process is carried out using a novel Concept Covering algorithm that exploits the recently proposed Concept Abduction inference service in Description Logics. The approach has been deployed as part of a skill management system that takes text files with curricula and project specifications as inputs and extracts from them available individual profiles and task descriptions, according to an ontology modeling skills.