2001 National Research and Development Conference
https://hdl.handle.net/10500/24479
2024-03-28T20:37:01ZImplication in three-valued logics of partial information
https://hdl.handle.net/10500/25440
Implication in three-valued logics of partial information
Britz, K
Renaud, K.; Kotze, P.; Barnard, A.
In formal logic, both semantic entailment and the conditional connective are used to formalize the intuitive notion of implication. The former is defined in the meta-language of the logic, and the latter in the language of the logic. Their interaction determines to what extent the conditional connective relates to entailment as an implication should. This paper addresses this question for a number of related three-valued logics based on Kleene's strong truth tables, and defines a suitable implication for Partial Logic.
2001-01-01T00:00:00ZFinite-state computational morphology - treatment of the Zulu noun
https://hdl.handle.net/10500/25439
Finite-state computational morphology - treatment of the Zulu noun
Pretorius, L; Bosch, SE
Renaud, K.; Kotze, P.; Barnard, A.
Morphological analysis is a basic enabling application for further kinds of natural lan guage processing, including part-of-speech tagging, parsing, translation and other high-level applications. Automated morphological analyzers exist for many of the European languages, but have not been reported for any of the indigenous languages
of southern Africa. Our project in computational morphological analysis/generation includes the production of
an automated morphological analyzer/generator for Zulu, using finite-state methods and tools. In this paper we elaborate on the use of finite-state methods in computational morphology, and report on our treatment of the Zulu noun.
2001-01-01T00:00:00ZThe development of a user classification model for a multi-cultural society
https://hdl.handle.net/10500/25437
The development of a user classification model for a multi-cultural society
Streicher, M; Wesson, JL; Calitz, A
Renaud, K.; Kotze, P.; Barnard, A.
During the last ten years, a number of computerised testing systems have been developed without considering the users' level of computer proficiency. Students at the University of Port Elizabeth come from a diverse background, both in home language and population group. The level of computer expertise of these students is diverse, and this may influence the test scores they obtain in computerised tests. In this study, various factors were found to be significant indicators of performance on computer-based tasks. These factors include previous computer and software experience, attitude towards computers, self-perceived ability to work with computers, contact with technology, gender, and home language. This paper discusses the development of a user classification model to classify students into three user groups, namely novice, intermediate and expert. Two methods were used for classification. The first followed a quantitative approach to user modeling and required users to perform simple computer-based tasks. The second method was qualitative in nature and used a questionnaire to assess the factors that were found to be significant indicators of performance in human-computer interaction. The hypothesis is that a user classification model can be developed for the first year student population at the University of Port Elizabeth. During the last ten years, a number of computerised testing systems have been developed without considering the users' level of computer proficiency. Students at the University of Port Elizabeth come from a diverse background, both in home language and population group. The level of computer expertise of these students is diverse, and this may influence the test scores they obtain in computerised tests. In this study, various factors were found to be significant indicators of performance on computer-based tasks. These factors include previous computer and software experience, attitude towards computers, self-perceived ability to work with computers, contact with technology, gender, and home language. This paper discusses the development of a user classification model to classify students into three user groups, namely novice, intermediate and expert. Two methods were used for classification. The first followed a quantitative approach to user modeling and required users to perform simple computer-based tasks. The second method was qualitative in nature and used a questionnaire to assess the factors that were found to be significant indicators of performance in human-computer interaction. The hypothesis is that a user classification model can be developed for the first year student population at the University of Port Elizabeth.
2001-01-01T00:00:00ZEffectively exploiting server log information for large scale web sites
https://hdl.handle.net/10500/24780
Effectively exploiting server log information for large scale web sites
Wong, B; Marsden, G
Renaud, K.; Kotze, P; Barnard, A
With the continuing growth of the Internet, an increasing number of organisations are incorporating the Web into their business activities. The appeal of a site to users in terms of both attractiveness and usability determines whether it will improve profits or cause on-line failure. It is thus vital that web site designers have access to tools that will aid them in evaluating site usage so that they can identify problem areas and alter them accordingly. At present, the most popular tools utilised in this evaluation make use of a technique called log file analysis, a process by which server log files are parsed to extract information
about visitors to a site. However, when visualising this information, current tools have either neglected site structure or else failed to utilise properties unique to web sites. We address both these issues by developing a visualisation of server log data that incorporates site structure and caters specifically for web sites by exploiting their unique characteristics.
2001-01-01T00:00:00Z