Automatic domain ontology extraction for context-sensitive opinion mining

Automated analysis of the sentiments presented in online consumer feedbacks can facilitate both organizations’ business strategy development and individual consumers’ comparison shopping. Nevertheless, existing opinion mining methods either adopt a context-free sentiment classification approach or rely on a large number of manually annotated training examples to perform context sensitive sentiment classification. Guided by the design science research methodology, we illustrate the design, development, and evaluation of a novel fuzzy domain ontology based contextsensitive opinion mining system. Our novel ontology extraction mechanism underpinned by a variant of Kullback-Leibler divergence can automatically acquire contextual sentiment knowledge across various product domains to improve the sentiment analysis processes. Evaluated based on a benchmark dataset and real consumer reviews collected from Amazon.com, our system shows remarkable performance improvement over the context-free baseline.

Construction safety : development of an assessment tool to reduce risk on building sites

Australian construction and building workers are exposed to serious workplace risks - including injury, illness and death - and although there have been improvements in occupational health and safety (OHS) performance over the past 20 years, the injury and fatality rate in the Australian construction industry remains a matter of concern. The concept of safety culture is rapidly being adopted in the industry, including recognising the critical role that organisational leaders play in overall safety performance. This paper reviews recent research in construction safety leadership and provides some examples and applications relevant to risk reduction in the workforce. By focusing on developing safety competency in those that fulfil safety critical roles, and clearly articulating the relevant safety management tasks, leaders can positively influence the organisation’s safety culture. Finally, some promising research on Safety Effectiveness Indicators (SEIs) may be an industry-friendly solution to reducing workplace risks across the industry, by providing a credible, accurate, and timely measure of safety performance.

Spectral–texture feature extraction using statistical moments with application to object-based vegetation species classification

The use of appropriate features to characterise an output class or object is critical for all classification problems. In order to find optimal feature descriptors for vegetation species classification in a power line corridor monitoring application, this article evaluates the capability of several spectral and texture features. A new idea of spectral–texture feature descriptor is proposed by incorporating spectral vegetation indices in statistical moment features. The proposed method is evaluated against several classic texture feature descriptors. Object-based classification method is used and a support vector machine is employed as the benchmark classifier. Individual tree crowns are first detected and segmented from aerial images and different feature vectors are extracted to represent each tree crown. The experimental results showed that the proposed spectral moment features outperform or can at least compare with the state-of-the-art texture descriptors in terms of classification accuracy. A comprehensive quantitative evaluation using receiver operating characteristic space analysis further demonstrates the strength of the proposed feature descriptors.

Development sites in the empty city : from picture book to performance

Picturebooks invite performance every time they are read. What happens to them when they’re adapted for live performance? This ongoing practice led research project (2008-) regenerates and transforms picturebook The Empty City (Hachette/Livre 2007) by David Megarrity and Jonathon Oxlade into a live experience. In this rebuilding, interanimation of text and illustration on the picturebook page suddenly open up into a new and complex structure incorporating composition of music, animation, live action, projected image and performing objects. The presenter is the creator of both the source text and writer/composer of the adaptation, providing a unique vantage point that draws on sources from both within and without the creative process up to and including audience reception. From the foundations up, this paper’s focus is on deep, muddy sites of development in the adaptation process, unearthed treasures, and how perceptions of fear and safety push, sway and stress the building of a new performance work for children in content, form and process.

Wide baseline correspondence extraction beyond local features

Robust, affine covariant, feature extractors provide a means to extract correspondences between images captured by widely separated cameras. Advances in wide baseline correspondence extraction require looking beyond the robust feature extraction and matching approach. This study examines new techniques of extracting correspondences that take advantage of information contained in affine feature matches. Methods of improving the accuracy of a set of putative matches, eliminating incorrect matches and extracting large numbers of additional correspondences are explored. It is assumed that knowledge of the camera geometry is not available and not immediately recoverable. The new techniques are evaluated by means of an epipolar geometry estimation task. It is shown that these methods enable the computation of camera geometry in many cases where existing feature extractors cannot produce sufficient numbers of accurate correspondences.

Information extraction from web services : a comparison of Tokenisation algorithms

Most web service discovery systems use keyword-based search algorithms and, although partially successful, sometimes fail to satisfy some users information needs. This has given rise to several semantics-based approaches that look to go beyond simple attribute matching and try to capture the semantics of services. However, the results reported in the literature vary and in many cases are worse than the results obtained by keyword-based systems. We believe the accuracy of the mechanisms used to extract tokens from the non-natural language sections of WSDL files directly affects the performance of these techniques, because some of them can be more sensitive to noise. In this paper three existing tokenization algorithms are evaluated and a new algorithm that outperforms all the algorithms found in the literature is introduced.

An approach to statistical lip modelling for speaker identification via chromatic feature extraction

This paper presents a novel technique for the tracking of moving lips for the purpose of speaker identification. In our system, a model of the lip contour is formed directly from chromatic information in the lip region. Iterative refinement of contour point estimates is not required. Colour features are extracted from the lips via concatenated profiles taken around the lip contour. Reduction of order in lip features is obtained via principal component analysis (PCA) followed by linear discriminant analysis (LDA). Statistical speaker models are built from the lip features based on the Gaussian mixture model (GMM). Identification experiments performed on the M2VTS¹ database, show encouraging results

CDKN2A mutation in a non-FAMMM kindred with cancers at multiple sites results in a functionally abnormal protein

The CDKN2A gene encodes p16 (CDKN2A), a cell-cycle inhibitor protein which prevents inappropriate cell cycling and, hence, proliferation. Germ-line mutations in CDKN2A predispose to the familial atypical multiple-mole melanoma (FAMMM) syndrome but also have been seen in rare families in which only 1 or 2 individuals are affected by cutaneous malignant melanoma (CMM). We therefore sequenced exons 1alpha and 2 of CDKN2A using lymphocyte DNA isolated from index cases from 67 families with cancers at multiple sites, where the patterns of cancer did not resemble those attributable to known genes such as hMLH1, hMLH2, BRCA1, BRCA2, TP53 or other cancer susceptibility genes. We found one mutation, a mis-sense mutation resulting in a methionine to isoleucine change at codon 53 (M531) of exon 2. The individual tested had developed 2 CMMs but had no dysplastic nevi and lacked a family history of dysplastic nevi or CMM. Other family members had been diagnosed with oral cancer (2 persons), bladder cancer (1 person) and possibly gall-bladder cancer. While this mutation has been reported in Australian and North American melanoma kindreds, we did not observe it in 618 chromosomes from Scottish and Canadian controls. Functional studies revealed that the CDKN2A variant carrying the M531 change was unable to bind effectively to CDK4, showing that this mutation is of pathological significance. Our results have confirmed that CDKN2A mutations are not limited to FAMMM kindreds but also demonstrate that multi-site cancer families without melanoma are very unlikely to contain CDKN2A mutations.