A technique for ranking friendship closeness in social networking services
- Authors: Sun, Zhaohao , Yearwood, John , Firmin, Sally
- Date: 2013
- Type: Text , Conference paper
- Relation: 24th Australasian Conference on Information Systems (ACIS) p. 1-9
- Full Text:
- Reviewed:
- Description: The concept of friend and friendship are critical to both theoretical and empirical studies of social relations, social media and social networks. Measuring the closeness among friends is a big issue for developing online social networking services (SNS) such as Facebook. This paper will address this issue by proposing a technique for ranking friendship closeness in SNS. The technique consists of an algorithm for ranking need-driven friendship closeness and an algorithm for behaviour-based friendship closeness in online social networking sites. The former is based on Maslow’s hierarchy of needs, while the latter is based on behaviours of users on Facebook and TOPSIS. Examples provided illustrate the viability of the proposed algorithms. The research in this paper shows that ranking friendship closeness will facilitate understanding of needs and behaviours of friends and of friendships in SNS. The proposed approach will facilitate research and development of social media, social commerce, social networks, and SN
A theoretical foundation of demand driven web services
- Authors: Sun, Zhaohao , Yearwood, John
- Date: 2014
- Type: Text , Book chapter
- Relation: Demand-driven web services p. 1-32
- Full Text: false
- Reviewed:
- Description: Web services are playing a pivotal role in business, management, governance, and society with the dramatic development of the Internet and the Web. However, many fundamental issues are still ignored to some extent. For example, what is the unified perspective to the state-of-the-art of Web services? What is the foundation of Demand-Driven Web Services (DDWS)? This chapter addresses these fundamental issues by examining the state-of-the-art of Web services and proposing a theoretical and technological foundation for demand-driven Web services with applications. This chapter also presents an extended Service-Oriented Architecture (SOA), eSMACS SOA, and examines main players in this architecture. This chapter then classifies DDWS as government DDWS, organizational DDWS, enterprise DDWS, customer DDWS, and citizen DDWS, and looks at the corresponding Web services. Finally, this chapter examines the theoretical, technical foundations for DDWS with applications. The proposed approaches will facilitate research and development of Web services, mobile services, cloud services, and social services.
A Tool for Assisting Group Decision-Making for Consensus Outcomes in Organizations
- Authors: Afshar, Faye , Yearwood, John , Stranieri, Andrew
- Date: 2006
- Type: Text , Book chapter
- Relation: E-Supply Chain Technologies and Management p. 316-343
- Full Text: false
- Reviewed:
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
A web-based Narrative construction environment
- Authors: Yearwood, John , Stranieri, Andrew , Osman, Deanna
- Date: 2008
- Type: Text , Conference paper
- Relation: Paper presented at NILE 2008: 5th International Conference on Narrative and Interactive Learning Environments, Edinburgh, Scotland : 6th-8th August 2008 p. 78-81
- Full Text:
- Description: This paper describes a web-based environment for constructing narrative from story snippets contributed by a community of interest. The underlying model uses an argument based structure to infer the next event in the narrative sequence. The approach makes use of both events and higher level story elements derived from Polti’s dramatic situations. Dramatic situations used are consistent with a theme, and events are generally constrained by the dramatic situation. The narrative generated is a function of the event history, the dramatic situations chosen and the plausible inferences about next events that are contributed by a community of interest in the theme. At this stage, a player’s actions are simulated using a random selection from a set and the implementation of a nonsense filter. Example outputs from the system are provided and discussed.
- Description: 2003006499
A within-frame ontological extension on FrameNet : Application in predicate chain analysis and question answering
- Authors: Ofoghi, Bahadorreza , Yearwood, John , Ghosh, Ranadhir
- Date: 2007
- Type: Text , Conference paper
- Relation: Paper presented at 20th Australian Joint Conference on Artificial Intelligence, AI 2007: Advances in Artificial Intelligence, Gold Coast, Queensland : 2nd-6th December 2007 p. 404-414
- Full Text: false
- Description: An ontological extension on the frames in FrameNet is presented in this paper. The general conceptual relations between frame elements, in conjunction with existing characteristics of this lexical resource, suggest more sophisticated semantic analysis of lexical chains (e.g. predicate chains) exploited in many text understanding applications. In particular, we have investigated its benefit for meaning-aware question answering when combined with an inference strategy. The proposed knowledge representation mechanism on the frame elements of FrameNet has been shown to have an impact on answering natural language questions on the basis of our case analysis.
- Description: 2003005507
Adaptive clustering with feature ranking for DDoS attacks detection
- Authors: Zi, Lifang , Yearwood, John , Wu, Xin
- Date: 2010
- Type: Text , Conference proceedings
- Full Text:
- Description: Distributed Denial of Service (DDoS) attacks pose an increasing threat to the current internet. The detection of such attacks plays an important role in maintaining the security of networks. In this paper, we propose a novel adaptive clustering method combined with feature ranking for DDoS attacks detection. First, based on the analysis of network traffic, preliminary variables are selected. Second, the Modified Global K-means algorithm (MGKM) is used as the basic incremental clustering algorithm to identify the cluster structure of the target data. Third, the linear correlation coefficient is used for feature ranking. Lastly, the feature ranking result is used to inform and recalculate the clusters. This adaptive process can make worthwhile adjustments to the working feature vector according to different patterns of DDoS attacks, and can improve the quality of the clusters and the effectiveness of the clustering algorithm. The experimental results demonstrate that our method is effective and adaptive in detecting the separate phases of DDoS attacks. © 2010 IEEE.
An algorithm for clustering based on non-smooth optimization techniques
- Authors: Bagirov, Adil , Rubinov, Alex , Sukhorukova, Nadezda , Yearwood, John
- Date: 2003
- Type: Text , Journal article
- Relation: International Transactions in Operational Research Vol. 10, no. 6 (2003), p. 611-617
- Full Text: false
- Reviewed:
- Description: The problem of cluster analysis is formulated as a problem of non-smooth, non-convex optimization, and an algorithm for solving the cluster analysis problem based on non-smooth optimization techniques is developed. We discuss applications of this algorithm in large databases. Results of numerical experiments are presented to demonstrate the effectiveness of this algorithm.
- Description: C1
- Description: 2003000422
An algorithm for minimization of pumping costs in water distribution systems using a novel approach to pump scheduling
- Authors: Bagirov, Adil , Barton, Andrew , Mala-Jetmarova, Helena , Al Nuaimat, Alia , Ahmed, S. T. , Sultanova, Nargiz , Yearwood, John
- Date: 2013
- Type: Text , Journal article
- Relation: Mathematical and Computer Modelling Vol. 57, no. 3-4 (2013), p. 873-886
- Relation: http://purl.org/au-research/grants/arc/LP0990908
- Full Text: false
- Reviewed:
- Description: The operation of a water distribution system is a complex task which involves scheduling of pumps, regulating water levels of storages, and providing satisfactory water quality to customers at required flow and pressure. Pump scheduling is one of the most important tasks of the operation of a water distribution system as it represents the major part of its operating costs. In this paper, a novel approach for modeling of explicit pump scheduling to minimize energy consumption by pumps is introduced which uses the pump start/end run times as continuous variables, and binary integer variables to describe the pump status at the beginning of the scheduling period. This is different from other approaches where binary integer variables for each hour are typically used, which is considered very impractical from an operational perspective. The problem is formulated as a mixed integer nonlinear programming problem, and a new algorithm is developed for its solution. This algorithm is based on the combination of the grid search with the Hooke-Jeeves pattern search method. The performance of the algorithm is evaluated using literature test problems applying the hydraulic simulation model EPANet. © 2012 Elsevier Ltd.
- Description: 2003010583
An algorithm for the optimization of multiple classifers in data mining based on graphs
- Authors: Kelarev, Andrei , Ryan, Joe , Yearwood, John
- Date: 2009
- Type: Text , Journal article
- Relation: The Journal of Combinatorial Mathematics and Combinatorial Computing Vol. 71, no. (2009), p. 65-85
- Full Text: false
- Reviewed:
- Description: This article develops an efficient combinatorial algorithm based on labeled directed graphs and motivated by applications in data mining for designing multiple classifiers. Our method originates from the standard approach described in [37]. It defines a representation of a multiclass classifier in terms of several binary classifiers. We are using labeled graphs to introduce additional structure on the classifier. Representations of this sort are known to have serious advantages. An important property of these representations is their ability to correct errors of individual binary classifiers and produce correct combined output. For every representation like this we develop a combinatorial algorithm with quadratic running time to compute the largest number of errors of individual binary classifiers which can be corrected by the combined multiple classifier. In addition, we consider the question of optimizing the classifiers of this type and find all optimal representations for these multiple classifiers.
- Description: 2003007563
An application of consensus clustering for DDoS attacks detection
- Authors: Zi, Lifang , Yearwood, John , Kelarev, Andrei
- Date: 2010
- Type: Text , Conference proceedings
- Full Text:
- Description: The detection of Distributed Denial of Service (DDos) attacks is very important for maintaining the security of networks and the Internet. This paper introduces a novel iterative consensus process based on Hybrid Bipartite Graph Formulation (HGBF) consensus function for DDos attacks detection. First, the features are extracted during feature extraction process based on the analysis of network traffic. Second, several clustering algorithms are applied in combination with the silhouette index to obtain a collection of independent initial clusterings. Third, the HGBF consensus function and silhouette index are used to find an appropriate consensus clustering of the initial clusterings. Fourth, this new consensus clustering is added to the pool of initial clusterings replacing another clustering with the worst Silhouette index. Fifth, the process continues iteratively until the Silhouette index of the resulting consensus clusterings stabilizes. This iterative consensus clustering process can improve the quality of the clusters. The experimental results demonstrate that our iterative consensus process is effective and can be used in practice for detecting the separate phased of DDos attacks.
An application of novel clustering technique for information security
- Authors: Beliakov, Gleb , Yearwood, John , Kelarev, Andrei
- Date: 2011
- Type: Text , Conference paper
- Relation: Applications and Techniques in Information Security Workshop p. 5-11
- Full Text: false
- Reviewed:
- Description: This article presents experimental results devoted to a new application of the novel clustering technique introduced by the authors recently. Our aim is to facilitate the application of robust and stable consensus functions in information security, where it is often necessary to process large data sets and monitor outcomes in real time, as it is required, for example, for intrusion detection. Here we concentrate on the particular case of application to profiling of phishing websites. First, we apply several independent clustering algorithms to a randomized sample of data to obtain independent initial clusterings. Silhouette index is used to determine the number of clusters. Second, we use a consensus function to combine these independent clusterings into one consensus clustering . Feature ranking is used to select a subset of features for the consensus function. Third, we train fast supervised classification algorithms on the resulting consensus clustering in order to enable them to process the whole large data set as well as new data. The precision and recall of classifiers at the final stage of this scheme are critical for effectiveness of the whole procedure. We investigated various combinations of three consensus functions, Cluster-Based Graph Formulation (CBGF), Hybrid Bipartite Graph Formulation (HBGF), and Instance-Based Graph Formulation (IBGF) and a variety of supervised classification algorithms. The best precision and recall have been obtained by the combination of the HBGF consensus function and the SMO classifier with the polynomial kernel.
- Description: 2003009195
An argumentation shell for supporting the development and drafting of legal arguments
- Authors: Yearwood, John , Stranieri, Andrew
- Date: 2002
- Type: Text , Journal article
- Relation: Information and Communication Technology Law Vol. 11, no. 1 (2002), p. 75-86
- Full Text: false
- Reviewed:
- Description: This article describes an argumentation shell to support the formulation, representation and drafting of legal arguments. The shell can be used to capture generic arguments in many legal domains as well as to assist decision-makers in constructing their own actual arguments . The shell demonstrates that knowledge represented using the generic/actual argument model (GAAM) (a variant of Toulmin's argument structure) can be used to: (a) support the development of complex arguments, (b) add context and increase specificity for the retrieval of relevant documents, (c) incorporate background knowledge, (d) assist in the drafting of documents that represent arguments made, and (e) provide a structure for complex inferences requiring a range of mechanisms. The shell can be used to support decision making in a range of legal domains, including discretionary domains.
- Description: C1
- Description: 2003000141
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
An evolutionary neural learning algorithm for offline cursive handwriting words with hamming network lexicon
- Authors: Ghosh, Moumita , Ghosh, Ranadhir , Yearwood, John
- Date: 2004
- Type: Text , Conference paper
- Relation: Paper presented at Seventeenth International Florida Artificial Intelligence Research Symposium Conference, FLAIRS 2004, Miami Beach, USA : 15th May, 2004
- Full Text: false
- Reviewed:
- Description: In this paper we incorporate a hybrid evolutionary method, which uses a combination of genetic algorithm and matrix based solution method such as QR factorization. A heuristic segmentation algorithm is initially used to over segment each word. Then the segmentation points are passed through the rule-based module to discard the incorrect segmentation points and include any missing segmentation points. Following the segmentation the connected contour is extracted between two correct segmentation points. The contour is passed through the feature extraction module that extracts the angular features of the contour, after which the EALS-BT algorithm finds the architecture and the weights for the classifier network. These recognized characters are grouped into words and passed to a variable length lexicon that retrieves words that has highest confidence value. Hamming neural network is used as a lexicon that rectifies the word misrecognized by the classifier. We have used CEDAR benchmark dataset and UCI Machine Learning repository (Upper case) to test the train and test the system
- Description: E1
- Description: 2003000865
An experiment in task decomposition and ensembling for a modular artificial neural network
- Authors: Ferguson, Brent , Ghosh, Ranadhir , Yearwood, John
- Date: 2004
- Type: Text , Conference paper
- Relation: Paper presented at Innovations in Applied Artificial Intelligence: 17th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, Ottawa, Canada : 17th May, 2004
- Full Text:
- Reviewed:
- Description: Modular neural networks have the possibility of overcoming common scalability and interference problems experienced by fully connected neural networks when applied to large databases. In this paper we trial an approach to constructing modular ANN's for a very large problem from CEDAR for the classification of handwritten characters. In our approach, we apply progressive task decomposition methods based upon clustering and regression techniques to find modules. We then test methods for combining the modules into ensembles and compare their structural characteristics and classification performance with that of an ANN having a fully connected topology. The results reveal improvements to classification rates as well as network topologies for this problem.
- Description: E1
- Description: 2003000852
An interaction framework for scenario-based three dimensional environments
- Authors: Macfadyen, Alyx , Stranieri, Andrew , Yearwood, John
- Date: 2006
- Type: Text , Conference paper
- Relation: Paper presented at IE 2006, the 3rd Australasian Conference on Interactive Entertainment, Perth : 4th December, 2006
- Full Text:
- Reviewed:
- Description: Although popular and engaging, three dimensional environments are rarely deployed to depict strong narratives involving complex characters engaged in reasoning. The design of three dimensional environments rich in narrative and character depth can be facilitated with a detailed representation of interactions between characters. However, the representation of interaction in current 3D development environments such as game engines is quite basic. This work advances a scheme for representing interactions that integrates a representation of semantics from linguistics called FrameNet with conceptualizations of drama and narrative by Georges Polti and Joseph Campbell. The resulting interaction frame facilitates the design of 3D environments by providing designers rich, yet standard elements that include spatial and temporal data, with which to represent complex interactions in 3D environments. This has application for the authoring of dynamically generated interactive narrative environments.
- Description: E1
- Description: 2003001839
An introduction algorithm with selection significance based on a fuzzy deriviative
- Authors: Mammadov, Musa , Yearwood, John
- Date: 2002
- Type: Text , Conference paper
- Relation: Paper presented at Hybrid Information Systems (Advances in Soft Computing), Adelaide : 11th December, 2001
- Full Text: false
- Reviewed:
- Description: E1
- Description: 2003000076
Analysis of the Australian credit database
- Authors: Rubinov, Alex , Sukhorukova, Nadezda , Yearwood, John
- Date: 2003
- Type: Text , Conference paper
- Relation: Paper presented at the Symposium on Industrial Optimisation and the 9th Australian Optimisation Day, Perth : 30th September, 2002
- Full Text: false
- Reviewed:
- Description: E1
- Description: 2003000353
Analytics service oriented architecture for enterprise information systems
- Authors: Sun, Zhaohao , Strang, Kenneth , Yearwood, John
- Date: 2014
- Type: Text , Conference paper
- Relation: 16th International Conference on Information Integration and Web-based Applications & Services
- Full Text: false
- Reviewed:
- Description: Big data analytics and business analytics are disruptive technology and innovative solution for enterprise development. However, what is the relationship between big data analytics and business analytics? What is the relationship between business analytics and enterprise information systems (EIS)? How can business analytics enhance the development of EIS? These are still big issues for EIS development. This paper addresses these three issues by proposing an ontology of business analytics, presenting an analytics service-oriented architecture (ASOA) and applying ASOA to EIS, where our surveyed data analysis showed that the proposed ASOA can enhance to develop EIS. This paper also discusses the interrelationship between data analysis and business analytics, and between data analytics and big data analytics. The proposed approaches in this paper will facilitate research and development of EIS, business analytics, big data analytics, and business intelligence.