Conceptual Framework of Kxpert:Knowledge-Based Information Retrieval for Expert Profiling

With the constant demand for expertise within organisation, especially in boosting the credibility of experts in the organisation, it is a need to bring forth a simple yet effective knowledge-based expert profiling based on information retrieved from credential publication sites. A number of frameworks from previous authors are analysed to propose one sound framework for a case university, to improve its existing research expert database, to make it more efficient in the information retrieval process and knowledge repository technique. Knowledge expertise mapping is proposed to be part of the whole mechanism for the conceptual framework called kXpert in this paper. The choice of credential knowledge sources is highlighted due to the updated information made available on the sites that are based on the published works of the internal experts. Very rare that this information is referred to on daily basis when there is a need to find expertise, thinking that the existing database has it all. The proposed conceptual framework presented in this paper is the work to be completed in the next phase, and can be customised for other organisations, industries and purposes.

The history and recent advances of Natural Language Interfaces for Databases Querying

Databases have been always the most important topic in the study of information systems, and an indispensable tool in all information management systems. However, the extraction of information stored in these databases is generally carried out using queries expressed in a computer language, such as SQL (Structured Query Language). This generally has the effect of limiting the number of potential users, in particular non-expert database users who must know the database structure to write such requests. One solution to this problem is to use Natural Language Interface (NLI), to communicate with the database, which is the easiest way to get information. So, the appearance of Natural Language Interfaces for Databases (NLIDB) is becoming a real need and an ambitious goal to translate the user’s query given in Natural Language (NL) into the corresponding one in Database Query Language (DBQL). This article provides an overview of the state of the art of Natural Language Interfaces as well as their architecture. Also, it summarizes the main recent advances on the task of Natural Language Interfaces for databases.

Selection procedure for adaptation devices helping car by driver with disability

The vehicle's equipment in specialized adaptations for drivers with disabilities requires knowledge of many issues, both anatomical, technical, procedural and psychological. In Poland, there are not many experts who have experience in comprehensive customer service with specific needs while driving. The article presents assumptions used to develop an algorithm for the selection of adaptive devices. The algorithm has the form of an expert database and contains: a description of possible dysfunctions, rules for the selection of adaptive devices and offers of European companies regarding specific adaptive solutions. The algorithm developed the knowledge and practice in the field of functional tests carried out in the Automotive Service Centre for the Disabled at the Institute of Motor Transport and serving people with difficult motor dysfunctions. The continuous development of adaptive instrumentation makes it convenient conditions for realizing the important need of mobility of people with disabilities. However, the process by which a disabled person has to pass to get a converted car is often complicated and time-consuming. Adaptation of a car is a very difficult task that requires specialist knowledge and experience. Presentation of existing procedures: from a simple Adaptation Selection Module to a more complicated algorithm, it should pay attention to the need to implement such solutions, among others for the needs of driving instructors or certifying doctors.