**Author details**

This scheme is based on the principle of knowledge elements that are abstracted from a metadata description characterization that is used for further processing. We have proposed to use ontology together with CBR in acquiring expert knowledge in the industry specific domain. We have developed the domain ontology, and we have studied how the content-based similarity between the concepts typed attributes could be assessed in CBR system. The study analyses the implementation results and evaluates the viability of our approaches in enabling search in intelligent-based digital repositories. It introduced a prototype Web-based CBR retrieval system, which operates on an RDF file store. With this, characteristic of the model ability of an individual will be increased to learn through collective searches experience. Furthermore, an IA was illustrated for assisting the user by suggesting improved ways to query the system on the ground of the resources in industry repositories according to his own preferences, which come to represent his interests. We have used all the profile agents effectively to generate relevant and recommended personalized profile for

OntoEnter can be part of a bigger framework of interacting global information networks including other DIRs, scientific repositories, commercial providers, and relies as much as possible on standards and existing building blocks as well as be based on Web standards. The combination of effective information retrieval techniques and IAs continues to show promising results in improving the performance of the information that is being extracted from the online repositories for users. Our findings suggest that IA is the central manager in the knowledge transfer process. Their mediation is essential to help adapt the knowledge produced by academics and makes it easier to adopt and use by the educational community. We conclude pointing out an important aspect of the obtained integration: improving representation by incorporating more metadata from within the information and intelligent techniques into the retrieval process, the effectiveness of the knowledge retrieval is enhanced. The model has good characteristics in providing preference to the users with a novel approach of finding nearby meaning of query and user can also recommend result

Future work will address the exploitation of information from other institutional repositories and digital services and refine the suggested queries, expand the system to provide other sup-

Future work will focus on the design of distributed and self-managed services based on the

• Able to examine and filter information based on semantic similarity and closeness

• Able to discover, compose, and integrate heterogeneous components automatically.

• Able to perform automated and user-driven application/service orchestration and chore-

• Able to handle heterogeneous data/knowledge /intelligence sources.

port, and refine and evaluate the system through user testing.

• Able to create, deploy, and exploit linked data.

the different users.

142 Knowledge Management Strategies and Applications

pages by their opinion.

Web and services, which are:

ography, etc.

Antonio Martin, Mauricio Burbano and Carlos León\*

\*Address all correspondence to: cleon@us.es

Technology Electronic Department, Seville University, Spain
