Mining for Significant Information from Unstructured and Structured Biological Data and Its Applications

Massive amounts of biological data are being accumulated in science. Searching for significant meaningful information and patterns from different types of data is necessary towards gaining knowledge from these large amounts of data available to users. However, data mining techniques do not normally deal with significance. Integrating data mining techniques with standard statistical procedures provides a way for mining statistically signi- ficant, interesting information from both structured and unstructured data. In this dissertation, different algorithms for mining significant biological information from both unstructured and structured data are proposed. A weighted-density-based approach is presented for mining item data from unstructured textual representations. Different algorithms in the area of radiation hybrid mapping are developed for mining significant information from structured binary data. The proposed algorithms have different applications in the ordering problem in radiation hybrid mapping including: identifying unreliable markers, and building solid framework maps. Effectiveness of the proposed algorithms towards improving map stability is demonstrated. Map stability is determined based on resampling analysis. The proposed algorithms deal effectively and efficiently with multidimensional data and also reduce computational cost dramatically. Evaluation shows that the proposed algorithms outperform comparative methods in terms of both accuracy and computation cost

An exploration of the eThekwini Municipality's indigent policy and its administration with focusing on provision of basic services.

Masters Degree. University of KwaZulu-Natal, Durban.The execution of the indigent policy within eThekwini Metropolitan Municipality would help address the huge issue of the three-fold challenges of poverty, lack of employment and disparities, a core objective in consolidating and advancing developmental local governance in South Africa. These policies were designed to support poor households in an effect to uplift everyday living conditions. Nearly thirty years into democracy South Africa still has places where indigent programmes have not been enforced by state and district municipalities. While many studies have focused on poverty alleviation less attention has been paid to investigating how the indigency programmes can be improved to support struggling households. The research pursued to bridge this space in the literature by seeking to understand the eThekwini Municipality’s indigent policy execution strategy in meeting the needs of poor households in order to explore ways in which it can be improved. This study was conducted within the interpretive model which employs a qualitative research approach to explore the Indigent Policy within the eThekwini Metropolitan Municipality in Durban, South Africa and its administration with regards to the delivery of essential services to frame the solution for holistic execution of the policy. The study draws its participants from the municipal officials at the eThekwini municipality. A purposive sampling technique was adopted to identify eleven participants who had adequate knowledge regarding the execution of the indigent policy among poor households in eThekwini. The analysis of empirical findings shows various obstacles encountered by the municipality in the provision of indigent support to poor households. While a variety of perspectives were expressed by participants in the study on the execution of the policy in its current form, a common thread was that the policy execution was affected by various challenges that include inter alia insufficient funding, departments working in silos, the absence of an indigent register, lack of accountability and poor administration with no clear execution plan. The findings of this study pointed to a gap in the lack of internal control systems, a consolidated approach to execution and a dedicated office to deal with the roll out of the support. The results of this study show that to ensure successful indigent support is rendered poor communities need to be accordingly identified and that regular monitoring and evaluation is done to mitigate the lack of compliance with regulations aligned to indigent support programmes. The researcher recommends that the municipality develops a clear execution plan for the indigent policy and establishes a dedicated team and office to strengthen the activation of the indigent support. One of the core tasks suggested should be the drawing up of an indigent register

The advances of stemming algorithms in text analysis from 2013 to 2018

Stemming is an activity within the pre-processing step of Text Analysis. It plays a role in the Text Analysis results. It drives Data Mining in fields such as Business Information Systems. Eight percent of existing organisational data that contributes Big Data is in an unstructured format. One of the focus areas within the concept of “Big Data” is the complexity of processing the data and being able to represent the results in such a way that they are easily understood. This challenge has been taken up by researchers over time. To determine the advances in Stemming Algorithm research, a systematic review was performed on articles on Stemming Algorithms published in journals from 2013 to 2018. Data was collected from accessible scholarly databases. The articles were then filtered by year and topic. The remaining articles were processed through a set of methodological quality criteria. The final articles were put through a bi-gram Text Analysis process to answer the research questions. The results concluded that the research focus for Stemming Algorithms has started to decrease as it reaches the plateau of productivity. The results show an evident drop in the collected articles from 58 in 2017 to 19 in 2018. Results show that information retrieval is still a common field of application for Stemming Algorithms. A major unexpected set of themes revolves around artificial intelligence, based on an increase in interest in this topic. Results show that a focus on Stemming Algorithms has shifted away from its development and moved towards its application. There is also a high interest in social media as an application of Stemming Algorithms. Future research suggestions include designing a Stemming Algorithm that would automatically and responsively adapt to the historical and morphological changes of language text.Dissertation (MCom)--University of Pretoria, 2019.TM2019InformaticsMComUnrestricte

A fault model for ontology mapping, alignment, and linking systems

There has been much work devoted to the mapping, alignment, and linking of ontologies (MALO), but little has been published about how to evaluate systems that do this. A fault model for conducting fine-grained evaluations of MALO systems is proposed, and its application to the system described in Johnson et al. [15] is illustrated. Two judges categorized errors according to the model, and inter-judge agreement was calculated by error category. Overall inter-judge agreement was 98 % after dispute resolution, suggesting that the model is consistently applicable. The results of applying the model to the system described in [15] reveal the reason for a puzzling set of results in that paper, and also suggest a number of avenues and techniques for improving the state of the art in MALO, including the development of biomedical domain specific language processing tools, filtering of high frequency matching results, and word sense disambiguation. 1