**2. HR management requirements from business and technical perspective**

Human resource management (HRM) is one of the basic business processes that consists of a wide range of administrative, organizational and employee acquisition and development

Building Expert Profiles Models Applying Semantic Web Technologies 211

improve the performance of the partner network or the virtual organization. Related to inter-enterprise cooperation, interoperability and integration are the following

In order to achieve transparency and comparability of expertise, organizations need tools and technologies to express the core competencies and talents of employees in a standardized, machine processable and understandable format. Based on the competence management business requirements briefly introduced above, we can distinguish three types of expertise management services, namely (1) expert profiling and search, (2) organization profiling and search and (3) knowledge items search and retrieval. Technologies that play a role in implementation of these services originate from the fields of open systems architecture, Web services, information retrieval, data and text mining,

The actual HRM solutions mainly focus on the integration of the distributed legacy databases, typically in the form of the data warehouse where the fact data (i.e. employee data) is arranged in order to answer the analytical queries efficiently. Personal profiles here usually rely on the self declared expertise. Employees keep track of their areas of expertise manually by maintaining a list of keywords or phrases and this list of key qualifications is being defined in the HR sector. This approach is error-prone since users are typically subjective/biased and reluctant to update the file regularly. Also, manually created lists cannot be an exhaustive description of the person's expertise areas. In addition, content based approaches (Sim et al., 2006) to expertise extraction, profiling and finding have been introduced lately that focus on the automatical identification of the expertise entities in the semi-structured and unstructured documents containing the expertise information as well as on the annotation of the identified expertise entities with the semantic mark-up. The input documents are: (1) curricula vitae and résumé that have been published in formats such as text, PDF, DOC and HTML; (2) publications and other legacy documents (Balog et al., 2006; Balog & de Rijke, 2008); (3) e-mails, blog sites and other online social networking related context (Aleman-Meza et al., 2007; Schäfermeier & Paschke, 2011). The expertise extraction and profiling is based on the linguistic analysis, statistical and machine learning classification methods as well as on the inductive logic programming techniques to discover rules for extracting fields from documents (Fang & Xiang Zhai, 2007; Petkova & Bruce Croft, 2006; Jung et al., 2007). Inspired by different research fields such as expert finding, competency management, terminology extraction, keyword extraction and concept extraction (Bordea, 2010), Bordea and Buitelaar (2010) proposed a hybrid approach and the

interoperability of knowledge models with similar schemas on the Web; etc.

 standard description of occupations and competences ; using multi-lingual dictionaries for building expert profiles;

clustering, natural language processing, ontology building, etc.

Saffron system for expert profiling and finding.

**3. State-of-the-art analysis of HR standards and literature 3.1 Analysis of classical approaches to expertise management** 

requirements:

**2.2 Technical requirements** 

activities. Administrative activities include management of different employee records (personal data, qualifications, holidays, business trips) and legal procedures of hiring / dismissal, as well as payment processing. Organizational activities cover strategic issues of enterprise organizations, systematization of working places, planning of team work, team formation and development, etc. Employee acquisition and development activities are directed towards definition of requirements, and standards that employees have to fulfil prior to employment, planning of necessary resources, education and development of employees, and employee performance measurement.

Herein, we would like to discuss the requirement for a comprehensive knowledge model for competence management from business and technical perspective.

#### **2.1 Competence management business requirements**

Competence management (CM) is an important research object in the more general area of human resource management. The idea of "competency" into the HR literature was introduced by the Harvard's psychologist David McClelland in early seventies of the last century (McClelland, 1973) and since then, development and use of competency based approaches within the corporate environment has been rapid (Draganidis & Mentzas, 2006).

#### **2.1.1 Competence management on company level**

Companies adopt different competency models and start competence and skills management initiatives in order to create a setting for the empowerment of their workforce and thus increase competitive advantage, innovation, and effectiveness (Houtzagers, 1999). A competency model is a list of competencies which are derived from observing satisfactory or exceptional performance for a specific occupation or task. Related to in-house competence management mainly aimed at building individual competence models are the following requirements:


#### **2.1.2 Competence management for cooperation and integration of activities with partners on national and international level**

In order to be competitive in the global knowledge economy, companies organize themselves in partner networks or even virtual enterprises that require interlinking of activities, or even existing information systems. Business processes in such networks often spawn different specific tasks that are to be solved by the network members. Therefore, it is essential that partner organizations prove themselves with complementary competencies both on an expert and an organizational level. Developing and maintaining competence profiles of all the relevant parties associated with specific task and topic can significantly improve the performance of the partner network or the virtual organization. Related to inter-enterprise cooperation, interoperability and integration are the following requirements:


#### **2.2 Technical requirements**

210 Security Enhanced Applications for Information Systems

activities. Administrative activities include management of different employee records (personal data, qualifications, holidays, business trips) and legal procedures of hiring / dismissal, as well as payment processing. Organizational activities cover strategic issues of enterprise organizations, systematization of working places, planning of team work, team formation and development, etc. Employee acquisition and development activities are directed towards definition of requirements, and standards that employees have to fulfil prior to employment, planning of necessary resources, education and development of

Herein, we would like to discuss the requirement for a comprehensive knowledge model for

Competence management (CM) is an important research object in the more general area of human resource management. The idea of "competency" into the HR literature was introduced by the Harvard's psychologist David McClelland in early seventies of the last century (McClelland, 1973) and since then, development and use of competency based approaches within the corporate environment has been rapid (Draganidis & Mentzas, 2006).

Companies adopt different competency models and start competence and skills management initiatives in order to create a setting for the empowerment of their workforce and thus increase competitive advantage, innovation, and effectiveness (Houtzagers, 1999). A competency model is a list of competencies which are derived from observing satisfactory or exceptional performance for a specific occupation or task. Related to in-house competence management mainly aimed at building individual competence models are the following

 building central repositories which define competencies for certain communities; building services for identifying experts and finding out and continually recording

**2.1.2 Competence management for cooperation and integration of activities with** 

making expertise available to users so they can answer questions or solve problems that

In order to be competitive in the global knowledge economy, companies organize themselves in partner networks or even virtual enterprises that require interlinking of activities, or even existing information systems. Business processes in such networks often spawn different specific tasks that are to be solved by the network members. Therefore, it is essential that partner organizations prove themselves with complementary competencies both on an expert and an organizational level. Developing and maintaining competence profiles of all the relevant parties associated with specific task and topic can significantly

what people ("experts") in an organization know ("expertise");

employees, and employee performance measurement.

**2.1 Competence management business requirements** 

**2.1.1 Competence management on company level** 

exceed personal or workgroup capabilities;

planning the expertise development paths; etc.

**partners on national and international level** 

requirements:

expertise gap analysis;

competence management from business and technical perspective.

In order to achieve transparency and comparability of expertise, organizations need tools and technologies to express the core competencies and talents of employees in a standardized, machine processable and understandable format. Based on the competence management business requirements briefly introduced above, we can distinguish three types of expertise management services, namely (1) expert profiling and search, (2) organization profiling and search and (3) knowledge items search and retrieval. Technologies that play a role in implementation of these services originate from the fields of open systems architecture, Web services, information retrieval, data and text mining, clustering, natural language processing, ontology building, etc.
