Visual tools for analysing evolution, emergence, and error in data streams
- Authors: Hart, Sol , Yearwood, John , Bagirov, Adil
- Date: 2007
- Type: Text , Conference paper
- Relation: Paper presented at 6th IEEE/ACIS International Conference on Computer and Information Science, ICIS 2007, Melbourne, Victoria : 11th-13th July 2007 p. 987-992
- Full Text:
- Description: The relatively new field of stream mining has necessitated the development of robust drift-aware algorithms that provide accurate, real time, data handling capabilities. Tools are needed to assess and diagnose important trends and investigate drift evolution parameters. In this paper, we present two new and novel visualisation techniques, Pixie and Luna graphs, which incorporate salient group statistics coupled with intuitive visual representations of multidimensional groupings over time. Through the novel representations presented here, spatial interactions between temporal divisions can be diagnosed and overall distribution patterns identified. It provides a means of evaluating in non-constrained capacity, commonly constrained evolutionary problems.
- Description: 2003005432
A rule based plagiarism detection using decision tree
- Authors: Ghosh, Moumita , Ghosh, Ranadhir , Yearwood, John
- Date: 2004
- Type: Text , Conference paper
- Relation: Paper presented at the CIMCA 2004: International Conference on Computational Intelligence for Modelling, Control and Automation, Gold Coast, Queensland : 12th July, 2004
- Full Text: false
- Reviewed:
- Description: E1
- Description: 2003000858
Multi label classification and drug-reaction associations using global optimization techniques
- Authors: Mammadov, Musa , Yearwood, John , Aliyea, Leyla
- Date: 2004
- Type: Text , Conference paper
- Relation: Paper presented at ICOTA6: 6th International Conference on Optimization - Techniques and Applications, Ballarat, Victoria : 9th December, 2004
- Full Text: false
- Reviewed:
- Description: E1
- Description: 2003000890
Fusion strategies for neural learning algorithms using evolutionary and discrete gradient approaches
- Authors: Ghosh, Ranadhir , Yearwood, John , Ghosh, Moumita , Bagirov, Adil
- Date: 2005
- Type: Text , Conference paper
- Relation: Paper presented at AIA 2005: International Conference on Artificial Intelligence and Applications, Innsbruck, Austria : 14th - 16th February, 2006
- Full Text: false
- Reviewed:
- Description: In this paper we investigate different variants for hybrid models using the Discrete Gradient method and an evolutionary strategy for determining the weights in a feed forward artificial neural network. The Discrete Gradient method has the advantage of being able to jump over many local minima and find very deep local minima. However, earlier research has shown that a good starting point for the discrete gradient method can improve the quality of the solution point. Evolutionary algorithms are best suited for global optimisation problems. Nevertheless they are cursed with longer training times and often unsuitable for real world application. For optimisation problems such as weight optimisation for ANNs in real world applications the dimensions are large and time complexity is critical. Hence the idea of a hybrid model can be a suitable option. In this paper we propose different fusion strategies for hybrid models combining the evolutionary strategy with the discrete gradient method to obtain an optimal solution much quicker. Three different fusion strategies are discussed: a linear hybrid model, an iterative hybrid model and a restricted local search hybrid model Comparative results on a range of standard datasets are provided for different fusion hybrid models.
- Description: E1
- Description: 2003001365
Classification for accuracy and insight : A weighted sum approach
- Authors: Quinn, Anthony , Stranieri, Andrew , Yearwood, John
- Date: 2007
- Type: Text , Conference paper
- Relation: Paper presented at Sixth Australasian Data Mining Conference, AusDM 2007, Gold Coast, Queensland, Victoria : 3rd-4th December 2007 p. 203-208
- Full Text:
- Description: This research presents a classifier that aims to provide insight into a dataset in addition to achieving classification accuracies comparable to other algorithms. The classifier called, Automated Weighted Sum (AWSum) uses a weighted sum approach where feature values are assigned weights that are summed and compared to a threshold in order to classify an example. Though naive, this approach is scalable, achieves accurate classifications on standard datasets and also provides a degree of insight. By insight we mean that the technique provides an appreciation of the influence a feature value has on class values, relative to each other. AWSum provides a focus on the feature value space that allows the technique to identify feature values and combinations of feature values that are sensitive and important for a classification. This is particularly useful in fields such as medicine where this sort of micro-focus and understanding is critical in classification.
- Description: 2003005504
A hybrid approach for feature and architecture selection in online handwriting recognition
- Authors: Ghosh, Ranadhir , Ghosh, Moumita , Yearwood, John
- Date: 2004
- Type: Text , Conference paper
- Relation: Paper presented at RASC 2004: Fifth International Conference on Recent Advances in Soft Computing, Nottingham, United Kingdom : 16th - 18th December, 2004
- Full Text: false
- Reviewed:
- Description: E1
- Description: 2003000870
Dynamical systems based on a fuzzy derivative and its applications to data classification
- Authors: Mammadov, Musa , Rubinov, Alex , Yearwood, John
- Date: 2003
- Type: Text , Conference paper
- Relation: Paper presented at the Industrial Optimisation 2003 Conference, Perth : 30th September, 2002
- Full Text: false
- Reviewed:
- Description: E1
- Description: 2003000339
Exploring novel features and decision rules to identify cardiovascular autonomic neuropathy using a hybrid of wrapper-filter based feature selection
- Authors: Huda, Shamsul , Jelinek, Herbert , Ray, Biplob , Stranieri, Andrew , Yearwood, John
- Date: 2010
- Type: Text , Conference paper
- Relation: Paper presented at the 2010 6th International Conference on Intelligent Sensors, Sensor Networks and Information Processing, ISSNIP 2010 p. 297-302
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- Reviewed:
- Description: Cardiovascular autonomic neuropathy (CAN) is one of the important causes of mortality among diabetes patients. Statistics shows that more than 22% of people with type 2 diabetes mellitus suffer from CAN and which in turn leads to cardiovascular disease (heart attack, stroke). Therefore early detection of CAN could reduce the mortality. Traditional method for detection of CAN uses Ewing's algorithm where five noninvasive cardiovascular tests are used. Often for clinician, it is difficult to collect data from for the Ewing Battery patients due to onerous test conditions. In this paper, we propose a hybrid of wrapper-filter approach to find novel features from patients' ECG records and then generate decision rules for the new features for easier detection of CAN. In the proposed feature selection, a hybrid of filter (Maximum Relevance, MR) and wrapper (Artificial Neural Net Input Gain Measurement Approximation ANNIGMA) approaches (MR-ANNIGMA) would be used. The combined heuristics in the hybrid MRANNIGMA takes the advantages of the complementary properties of the both filter and wrapper heuristics and can find significant features. The selected features set are used to generate a new set of rules for detection of CAN. Experiments on real patient records shows that proposed method finds a smaller set of features for detection of CAN than traditional method which are clinically significant and could lead to an easier way to diagnose CAN. © 2010 IEEE.
Applying clustering and ensemble clustering approaches to phishing profiling
- Authors: Webb, Dean , Yearwood, John , Vamplew, Peter , Ma, Liping , Ofoghi, Bahadorreza , Kelarev, Andrei
- Date: 2009
- Type: Text , Conference paper
- Relation: Paper presented at Eighth Australasian Data Mining Conference, AusDM 2009, University of Melbourne, Melbourne, Victoria : 1st–4th December 2009
- Full Text:
- Description: 2003007911
An argumentation-based multi-agent system for e-tourism dialogue
- Authors: Avery, John , Yearwood, John , Stranieri, Andrew
- Date: 2001
- Type: Text , Conference paper
- Relation: Paper presented at Hybrid Information Systems, First International Workshop on Hybrid Intelligent Systems, Adelaide : 11th - 12th December, 2003 p. 497-512
- Full Text: false
- Reviewed:
- Description: E1
- Description: 2003000112
A variable initialization approach to the EM algorithm for better estimation of the parameters of hidden Markov Model based acoustic modeling of speech signals
- Authors: Huda, Shamsul , Ghosh, Ranadhir , Yearwood, John
- Date: 2006
- Type: Text , Conference paper
- Relation: Paper presented at Artificial Intelligence, Advances in Data Mining, Applications in Medicine, Web Mining, Marketing, Image and Signal Mining Conference 2006, Leipzig, Germany : 14th July, 2006 p. 416-430
- Full Text: false
- Reviewed:
- Description: The traditional method for estimation of the parameters of Hidden Markov Model (HMM) based acoustic modeling of speech uses the Expectation-Maximization (EM) algorithm. The EM algorithm is sensitive to initial values of HMM parameters and is likely to terminate at a local maximum of likelihood function resulting in non-optimized estimation for HMM and lower recognition accuracy. In this paper, to obtain better estimation for HMM and higher recognition accuracy, several candidate HMMs are created by applying EM on multiple initial models. The best HMM is chosen from the candidate HMMs which has highest value for likelihood function. Initial models are created by varying maximum frame number in the segmentation step of HMM initialization process. A binary search is applied while creating the initial models. The proposed method has been tested on TIMIT database. Experimental results show that our approach obtains improved values for likelihood function and improved recognition accuracy.
- Description: E1
- Description: 2003001542
Designing a decision module for modular artificial neural networks
- Authors: Ferguson, Brent , Ghosh, Ranadhir , Yearwood, John
- Date: 2004
- Type: Text , Conference paper
- Relation: Paper presented at the ICOTA6: 6th International Conference on Optimization - Techniques and Applications, Ballarat, Victoria : 9th December, 2004
- Full Text: false
- Reviewed:
- Description: E1
- Description: 2003000854
Risk : Drug therapy versus adverse drug reaction. A case study approach with consumer, medical and expert views
- Authors: O'Brien, Michelle , Yearwood, John
- Date: 2004
- Type: Text , Conference paper
- Relation: Paper presented at the Health Informatics Conference 2004 - Let's make a difference with health ICT, Brisbane : 25th July, 2004
- Full Text: false
- Reviewed:
- Description: Extracts of three case studies, from a larger qualitative study, are used to illustrate an emerging theme about the issue of the risks versus the benefits of providing detailed information about adverse drug reactions (ADRs) to consumers. The case studies include the consumer, medical and expert views of a single event, a suspected adverse drug reaction. The consumers would like more information. The doctors expressed that providing information about all possible ADRs can result in some consumers choosing not to take medications due to the perceived risk of the medication. The ADR experts stated that providing ADR information to the consumers within the presented case studies, might have assisted in earlier detection of the ADR, resulting in a less severe reaction. This paper aims to illustrate this emerging theme of the risks versus the benefits of providing consumers with information about potential ADRs and suggest some ways of increasing the benefits and minimizing the risk. We then indicate how these finding may inform future development of ADR decision support systems.
- Description: E1
- Description: 2003000911
Online group deliberation for the elicitation of shared values to underpin decision making
- Authors: Feldman, Yishai , Kraft, Donald , Kuflik, Tsvi , Afshar, Faezeh , Stranieri, Andrew , Yearwood, John
- Date: 2009
- Type: Text , Conference paper
- Relation: Paper presented at 7th International Conference, NGITS 2009, Next generation information technologies and systems, Haifa, Israel : 16th-18th June 2009 Vol. 5831, p. 158-168
- Full Text: false
- Description: Values have been shown to underpin our attitudes, behaviour and motivate our decisions. Values do not exist in isolation but have meaning in relation to other values. However, values are not solely the purview of individuals as communities and organisations have core values implicit in their culture, policies and practices. Values for a group can be determined by a minority in power, derived by algorithmically merging values each group member holds, or set by deliberative consensus. The elicitation of values for the group by deliberation is likely to lead to widespread acceptance of values arrived at, however enticing individuals to engage in face to face discussion about values has been found to be very difficult. We present an online deliberative communication approach for the anonymous deliberation of values and claim that the framework has the elements required for the elicitation of shared values.
- Description: 2003007509
Managing ontology evolution : Capturing the semantics of change
- Authors: Avery, John , Yearwood, John
- Date: 2004
- Type: Text , Conference paper
- Relation: Paper presented at the Tenth Australian World Wide Web Conference, Gold Coast, Queensland : 4th July, 2004
- Full Text: false
- Reviewed:
- Description: E1
- Description: 2003000844
The integration of narrative and argumentation for a scenario-based learning environment in law
- Authors: Stranieri, Andrew , Yearwood, John
- Date: 2005
- Type: Text , Conference paper
- Relation: Paper presented at the Tenth International Conference on Artificial Intelligence and Law, Bologna, Italy : 6th - 11th June, 2005
- Full Text: false
- Reviewed:
- Description: Narrative or story telling has long been used to structure and organise human experience. In contrast to logical models of reasoning, narrative models enable complex situations to be understood and recalled by humans readily. There is also some indication that narrative models represent the way in which jurors weigh up the veracity of legal evidence. In this work a narrative model is integrated into a logical reasoning model for the purpose of advancing a learning environment that promises to be engaging and effective. The narrative model includes a representation of the point of a story and a simple story grammar. The learning environment is designed to enable the automated generation of plausible scenarios representing a variety of family law property division cases told from the point of view of numerous characters.
- Description: E1
- Description: 2003001432
Establishing phishing provenance using orthographic features
- Authors: Liping, Ma , Yearwood, John , Watters, Paul
- Date: 2009
- Type: Text , Conference paper
- Relation: Paper presented at 2009 eCrime Researchers Summit, eCRIME '09, Tacoma, Washington : 20th-21st October 2009
- Full Text:
- Description: After phishing message detection, determining the provenance of phishing messages and Websites is the second step to tracing cybercriminals. In this paper, we present a novel method to cluster phishing emails automatically using orthographic features. In particular, we develop an algorithm to cluster documents and remove redundant features at the same time. After collecting all the possible features based on observation, we adapt the modified global k-mean method repeatedly, and generate the objective function values over a range of tolerance values across different subsets of features. Finally, we identify the appropriate clusters based on studying the distribution of the objective function values. Experimental evaluation of a large number of computations demonstrates that our clustering and feature selection techniques are highly effective and achieve reliable results.
- Description: 2003007842
A hybrid neural learning algorithm combining evolutionary algorithm with discrete gradient method
- Authors: Ghosh, Ranadhir , Yearwood, John , Bagirov, Adil
- Date: 2004
- Type: Text , Conference paper
- Relation: Paper presented at the Second International Conference on Software Computing and Intelligent Systems, Yokahama, Japan : 21st October, 2004
- Full Text: false
- Reviewed:
- Description: E1
- Description: 2003000860
Web-based decision support for structured reasoning in health
- Authors: Stranieri, Andrew , Yearwood, John , Gervasoni, Susan , Garner, Susan , Deans, Cecil , Johnstone, Alistair
- Date: 2004
- Type: Text , Conference paper
- Relation: Paper presented at Health Informatics Conference 2004 - Let's make a difference with health ICT, Brisbane, Queensland : 25th July, 2004
- Full Text: false
- Reviewed:
- Description: Decision making processes in the health care setting are often complex, demanding of professionals and rapidly changing. Furthermore, there is increasing pressure for professionals to make reasoning transparent and consistent. Decision support technologies have not made a substantial contribution to these issues to date largely because knowledge is difficult to elicit and maintain and existing development tools are very sophisticated yet complex. In this study a method for representing complex and discretionary reasoning used successfully in law was applied to the task of modelling decision making processes that critical care nurses deploy in responding to a low oxygen alarm. The approach, based on decision and argument tree diagrams enables the rapid development of small scale, yet useful web based decision support systems.
- Description: E1
- Description: 2003000831
A hybrid clustering algorithm using two level of abstraction
- Authors: Ghosh, Ranadhir , Mammadov, Musa , Ghosh, Moumita , Yearwood, John
- Date: 2005
- Type: Text , Conference paper
- Relation: Paper presented at Fuzzy Logic, Soft Computing, and Computational Intelligence, 11th International Fuzzy Systems Association World Congress, Beijing, China : 28th - 31st July, 2005
- Full Text: false
- Reviewed:
- Description: E1
- Description: 2003001360