Martina Asenbrener Katic

Intelligent question — Answering systems: Review of research

With the development of ICT the need for automated question-answering systems is becoming increasingly important. Question-answering systems are still under development and experimentation. This paper is an overview of the research area that deals with question-answering systems; it explains the concept of question-answering systems and points out the problems that occur during their development. It also refers to a complex assessment techniques that are necessary when designing such systems. The system described is a real system and so are the test results.

Online vs. Paper-Based Testing: A Comparison of Test Results

This paper presents the results of a comparative research of paper-based testing versus online testing using MudRi. The research was conducted on three courses at the Department of Informatics, University of Rijeka, and included 1231 tests. In observed courses, online tests have largely replaced traditional paper-based tests in the last few years. Therefore, the aim of this research was to determine whether the online testing results differ from the results of traditional paper-based tests. The research results showed that, for the observed courses, the median values of the results achieved during MudRi online tests and traditional paper based tests are not significantly different when online tests include certain percentage of subjective test questions.

Comparison of Two Versions of Formalization Method for Text Expressed Knowledge

The Node of Knowledge (NOK) method is a method for knowledge representation. It is used as a basis for development of formalism for textual knowledge representation (FNOK). Two versions of formalization methods and, respectively, two Question Answering (QA) systems are developed. The first system uses grammars; it is written and implemented in Python. The second, improved system is based on storing text in relational databases without losing semantics and it is implemented in Oracle.

A system for transformation of sentences from the enriched formalized Node of Knowledge record into relational database

Abstract Verbalized text contains knowledge necessary and sufficient for transfer of numerous human cognitions. The question is how this knowledge was saved into text. Authors believe that they found an important idea how to assemble knowledge into nodes of knowledge. Similar methods in the field of knowledge networks exist, but none of them does it in the same way as the Node of Knowledge (NOK) method. Basic terms and concepts in a language are represented in words whose meaning is final and cannot be divided in subterms. More complex meaning can be achieved by combining words in sentences. According to authors’ opinion, each sentence includes connective medium for words in the sentence (related to semantic reasons), which is inwrought in the Node of Knowledge method. Using the Node of Knowledge method each sentence can be presented as a network of connected words. This network is enriched with links between words so a computer can interpret meaning and knowledge of the sentence in the same way an intelligent person does. A formalized and semantically enriched record of sentences (called Formalized Node of Knowledge – FNOK) is developed. Authors find that in this way, even without statistical text analysis, an algorithm can give correct answer to a question set based on written text. This paper presents the system for transformation of textual knowledge expressed in natural language sentences into a relational database. The system is a part of a larger knowledge-based system based on the Node of Knowledge (NOK) conceptual framework for knowledge-based system development. This paper starts with sentences written in the formalized and enriched form for which a logical transformation into the structure of a relational database is proposed. The system and algorithms for the transformation of formalized sentences into n-tuples of the relational database are distributed and represented in several steps. The research has shown that it is possible to store semantically enriched sentences in relational databases. The solution presented in this paper is important for further development of the system for receiving questions from users and providing answers (i.e. question-answering system), with the ability to use well-developed relational SQL languages. Relational database of texts enables numerous applications in the field of expert and intelligent systems.