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Full-Text Articles in Computer Sciences
Rough-Fuzzy Hybrid Approach For Identification Of Bio-Markers And Classification On Alzheimer's Disease Data, Changsu Lee, Chiou-Peng Lam, Martin Masek
Rough-Fuzzy Hybrid Approach For Identification Of Bio-Markers And Classification On Alzheimer's Disease Data, Changsu Lee, Chiou-Peng Lam, Martin Masek
Martin Masek
A new approach is proposed in this paper for identification of biomarkers and classification on Alzheimer's disease data by employing a rough-fuzzy hybrid approach called ARFIS (a framework for Adaptive TS-type Rough-Fuzzy Inference Systems). In this approach, the entropy-based discretization technique is employed first on the training data to generate clusters for each attribute with respect to the output information. The rough set-based feature reduction method is then utilized to reduce the number of features in a decision table obtained using the cluster information. Another rough set-based approach is employed for the generation of decision rules. After the construction and …
Mining Branching-Time Scenarios, Dirk Fahland, David Lo, Shahar Maoz
Mining Branching-Time Scenarios, Dirk Fahland, David Lo, Shahar Maoz
David LO
Specification mining extracts candidate specification from existing systems, to be used for downstream tasks such as testing and verification. Specifically, we are interested in the extraction of behavior models from execution traces. In this paper we introduce mining of branching-time scenarios in the form of existential, conditional Live Sequence Charts, using a statistical data-mining algorithm. We show the power of branching scenarios to reveal alternative scenario-based behaviors, which could not be mined by previous approaches. The work contrasts and complements previous works on mining linear-time scenarios. An implementation and evaluation over execution trace sets recorded from several real-world applications shows …
Automated Library Recommendation, Ferdian Thung, David Lo, Julia Lawall
Automated Library Recommendation, Ferdian Thung, David Lo, Julia Lawall
David LO
Many third party libraries are available to be downloaded and used. Using such libraries can reduce development time and make the developed software more reliable. However, developers are often unaware of suitable libraries to be used for their projects and thus they miss out on these benefits. To help developers better take advantage of the available libraries, we propose a new technique that automatically recommends libraries to developers. Our technique takes as input the set of libraries that an application currently uses, and recommends other libraries that are likely to be relevant. We follow a hybrid approach that combines association …
Applying Data Mining Techniques In The Selection Of Plant Traits, Dean Diepeveen, Leisa Armstrong
Applying Data Mining Techniques In The Selection Of Plant Traits, Dean Diepeveen, Leisa Armstrong
Leisa Armstrong
In the agricultural sector, farmers are provided with crop related information by various research agencies in order to make critical decisions about which is the most profitable crop variety choice. Research agencies provide information which is generic, rather than being tailored to the individual farmers cropping situation. A number of specific plant and growth traits are used to establish the most suitable crop varieties. When selecting crop varieties for release to growers, the application of data mining techniques to crop research data enables the customization of information to each individual farmers farming situation. The challenge for agricultural research perspective is …
An Evaluation Of Methodologies For Eagriculture In An Australian Context, Leisa Armstrong, Dean Diepeveen
An Evaluation Of Methodologies For Eagriculture In An Australian Context, Leisa Armstrong, Dean Diepeveen
Leisa Armstrong
Australian agricultural producers’ profits are dependent on the decisions they make about farm productivity systems. They may use recommendations and information provided by government agencies and private consultants. For cereal growers, success is dependent on decisions made about selection of crop varieties suitable for their agronomic and climatic conditions. This paper reports on research which aimed to evaluate some current eAgriculture methodologies for their application in the Western Australian agricultural industry. In particular the paper illustrates the findings from a project which aimed to explain the variability seen in crop varieties grown in Western Australia. The problems associated with crop …
An Eagriculture-Based Decision Support Framework For Information Dissemination, Leisa Armstrong, Dean Diepeveen, Khumphicha Tantisantisom
An Eagriculture-Based Decision Support Framework For Information Dissemination, Leisa Armstrong, Dean Diepeveen, Khumphicha Tantisantisom
Leisa Armstrong
The ability of farmers to acquire knowledge to make decisions is limited by the information quality and applicability. Inconsistencies information delivery and standards/or the integration o/information also limit decision making processes. This research uses a similar approach to the Knowledge Discovery in Databases (KDD) methodology to develop an ICT based framework which can be used to facilitate the acquisition of knowledge for farmer's' decision making processes. This is one of the leading areas of research and development for information technology in an agricultural industry, which is yet to utilize such technologies fully. The Farmer Knowledge and Decision Support Framework (FKDSF) …
An Information-Based Decision Support Framework For Eagriculture, Leisa Armstrong, Dean Diepeveen
An Information-Based Decision Support Framework For Eagriculture, Leisa Armstrong, Dean Diepeveen
Leisa Armstrong
The ability of farmers to acquire knowledge to make decisions is limited by the information quality and applicability. An inconsistency in information delivery and standards for the integration of information also limits the decision making process. Knowledge Discovery in Databases (KDD) methodology described for the data mining is an example of how frameworks can be used to facilitate such data integration. This research will examine how such a ICT based framework can be used to facilitate the acquisition of knowledge for the farmer decision making process. The Farmer Knowledge and Decision Support Framework (FKDSF) takes information provided to farmers and …
Comprehensive Evaluation Of Association Measures For Fault Localization, Lucia Lucia, David Lo, Lingxiao Jiang, Aditya Budi
Comprehensive Evaluation Of Association Measures For Fault Localization, Lucia Lucia, David Lo, Lingxiao Jiang, Aditya Budi
David LO
In statistics and data mining communities, there have been many measures proposed to gauge the strength of association between two variables of interest, such as odds ratio, confidence, Yule-Y, Yule-Q, Kappa, and gini index. These association measures have been used in various domains, for example, to evaluate whether a particular medical practice is associated positively to a cure of a disease or whether a particular marketing strategy is associated positively to an increase in revenue, etc. This paper models the problem of locating faults as association between the execution or non-execution of particular program elements with failures. There have been …
Word Sense Disambiguation In Biomedical Ontologies With Term Co-Occurrence Analysis And Document Clustering, Bill Andreopoulos, Dimitra Alexopoulou, Michael Schroeder
Word Sense Disambiguation In Biomedical Ontologies With Term Co-Occurrence Analysis And Document Clustering, Bill Andreopoulos, Dimitra Alexopoulou, Michael Schroeder
William B. Andreopoulos
Bi-Level Clustering Of Mixed Categorical And Numerical Biomedical Data, Bill Andreopoulos, Aijun An, Xiaogang Wang
Bi-Level Clustering Of Mixed Categorical And Numerical Biomedical Data, Bill Andreopoulos, Aijun An, Xiaogang Wang
William B. Andreopoulos