Using extended random set to find specific patterns

With the overwhelming increase in the amount of data on the web and data bases, many text mining techniques have been proposed for mining useful patterns in text documents. Extracting closed sequential patterns using the Pattern Taxonomy Model (PTM) is one of the pruning methods to remove noisy, inconsistent, and redundant patterns. However, PTM model treats each extracted pattern as whole without considering included terms, which could affect the quality of extracted patterns. This paper propose an innovative and effective method that extends the random set to accurately weigh patterns based on their distribution in the documents and their terms distribution in patterns. Then, the proposed approach will find the specific closed sequential patterns (SCSP) based on the new calculated weight. The experimental results on Reuters Corpus Volume 1 (RCV1) data collection and TREC topics show that the proposed method significantly outperforms other state-of-the-art methods in different popular measures.

Reflections on the Research Students' 2015 Art Exhibition and Operetta/morality play "The Trial of Homo Economicus: The dollar hunting animal"

The paper outlines the process of organising research student participants and creating a public musical performance at QUT. The theme of the Operetta/Morality play is the clash between economic values of humans necessitating growth and the basic needs of the other life on planet earth. The one act play is set in a court room presided over by a judge who adjudicates the court proceedings.Homo economicus is in the dock and victims(various animals and birds) raise their grievances.

The state of the art of business process management research as published in the BPM Conference

The research field of Business Process Management (BPM) has gradually developed as a discipline situated within the computer, management and information systems sciences. Its evolution has been shaped by its own conference series, the BPM conference. Still, as with any other academic discipline, debates accrue and persist, which target the identity as well as the quality and maturity of the BPM field. In this paper, we contribute to the debate on the identity and progress of the BPM conference research community through an analysis of the BPM conference proceedings. We develop an understanding of signs of progress of research presented at this conference, where, how, and why papers in this conference have had an impact, and the most appropriate formats for disseminating influential research in this conference. Based on our findings from this analysis, we provide conclusions about the state of the conference series and develop a set of recommendations to further develop the conference community in terms of research maturity, methodological advance, quality, impact, and progression.

Beyond Gauss: Image-set matching on the Riemannian manifold of PDFs

State-of-the-art image-set matching techniques typically implicitly model each image-set with a Gaussian distribution. Here, we propose to go beyond these representations and model image-sets as probability distribution functions (PDFs) using kernel density estimators. To compare and match image-sets, we exploit Csiszar´ f-divergences, which bear strong connections to the geodesic distance defined on the space of PDFs, i.e., the statistical manifold. Furthermore, we introduce valid positive definite kernels on the statistical manifold, which let us make use of more powerful classification schemes to match image-sets. Finally, we introduce a supervised dimensionality reduction technique that learns a latent space where f-divergences reflect the class labels of the data. Our experiments on diverse problems, such as video-based face recognition and dynamic texture classification, evidence the benefits of our approach over the state-of-the-art image-set matching methods.

Autoethnography : critical appreciation of an emerging art

In this article, the author discusses how she applied autoethnography in a study of the design of hypermedia educational resources and shows how she addressed problematic issues related to autoethnographic legitimacy and representation. The study covered a 6-year period during which the practitioner’s perspective on the internal and external factors influencing the creation of three hypermedia CD-ROMs contributed to an emerging theory of design. The author highlights the interrelationship between perception and reality as vital to qualitative approaches and encourages researchers to investigate their reality more fully by practicing the art of autoethnography.

An application of fractal image-set coding in facial recognition

Faces are complex patterns that often differ in only subtle ways. Face recognition algorithms have difficulty in coping with differences in lighting, cameras, pose, expression, etc. We propose a novel approach for facial recognition based on a new feature extraction method called fractal image-set encoding. This feature extraction method is a specialized fractal image coding technique that makes fractal codes more suitable for object and face recognition. A fractal code of a gray-scale image can be divided in two parts – geometrical parameters and luminance parameters. We show that fractal codes for an image are not unique and that we can change the set of fractal parameters without significant change in the quality of the reconstructed image. Fractal image-set coding keeps geometrical parameters the same for all images in the database. Differences between images are captured in the non-geometrical or luminance parameters – which are faster to compute. Results on a subset of the XM2VTS database are presented.