Learning domain ontology for tag recommendation

Recently, user tagging systems have grown in popularity on the web. The tagging process is quite simple for ordinary users, which contributes to its popularity. However, free vocabulary has lack of standardization and semantic ambiguity. It is possible to capture the semantics from user tagging and represent those in a form of ontology, but the application of the learned ontology for recommendation making has not been that flourishing. In this paper we discuss our approach to learn domain ontology from user tagging information and apply the extracted tag ontology in a pilot tag recommendation experiment. The initial result shows that by using the tag ontology to re-rank the recommended tags, the accuracy of the tag recommendation can be improved.

High-Order Concept Associations Mining and Inferential Language Modeling for Online Review Spam Detection

Despite many incidents about fake online consumer reviews have been reported, very few studies have been conducted to date to examine the trustworthiness of online consumer reviews. One of the reasons is the lack of an effective computational method to separate the untruthful reviews (i.e., spam) from the legitimate ones (i.e., ham) given the fact that prominent spam features are often missing in online reviews. The main contribution of our research work is the development of a novel review spam detection method which is underpinned by an unsupervised inferential language modeling framework. Another contribution of this work is the development of a high-order concept association mining method which provides the essential term association knowledge to bootstrap the performance for untruthful review detection. Our experimental results confirm that the proposed inferential language model equipped with high-order concept association knowledge is effective in untruthful review detection when compared with other baseline methods.

Is there an App for that? : social media uses for road safety

The use of social media has increased dramatically in recent years in the areas of public health and injury prevention, with many organisations creating online and social media content. Despite the adoption of such media by modern society, research relating to the design and evaluation of social media for the promotion of health issues is very much in its infancy. A timely review of the available evidence in relation to the use of social media campaigns from both the road safety and broader public health context will be undertaken. In particular, this paper will address the questions of what social media should be developed, how it should be evaluated, as well as what should be the key measures of success and to what extent do these measures relate to practically significant outcomes, such as behaviour change. Much like more traditional media campaigns, social media may be best regarded as another approach within the array of potential approaches that a health advertising researcher or practitioner may utilise. With younger demographics becoming less likely to engage with more traditional advertising mediums relative to their preference for social media, social media‟s most important role in the road safety advertising context may be to offer the means of delivering road safety messages to high risk, younger road users.

Young children’s beliefs about including others in their play: Social and moral reasoning about inclusion and exclusion

Previous research has emphasised the importance of active citizenship in the early years for the development of a tolerant and cohesive Australian society. This paper presents findings related to young children’s beliefs about exclusion based on gender and race. The findings draw from a larger study exploring the development of children’s moral and social values and teachers’ beliefs and practices related to teaching for moral development, in the early years of school in Australia. This current study examined reasoning about exclusion in early childhood with children aged 5-8 years. One hundred children from seven schools (Preparatory to Grade 3) answered questions relating to two scenarios in which the children had to make a decision about whether to include others of different gender or race in their play. The majority of children believed that others should be included in their play, regardless of their gender or race. When asked to explain, the children primarily gave reasons related to moral concern and fairness. Children were then asked whether they would continue to include or exclude if their friends (social consensus) or teachers (authority) suggested otherwise. The majority of children maintained their beliefs when beliefs to the contrary were voiced by their peers and teachers. The implications of these responses are discussed.

Moral and social development : teachers’ knowledge of learning and teaching strategies in the early years

The intention of the analysis in this paper was to determine, from interviews with eleven early years’ teachers, what knowledge guided their teaching of moral behaviour. Six of the teachers defined moral behaviour in terms of social conventions only. Children’s learning was attributed by five of the teachers to incidental/contextual issues. Nine of the teachers used discussion of issues, in various contexts, as a way of teaching about social and moral issues. The majority of the teachers (n=7) gave the source of their knowledge of pedagogy as practical as opposed to theoretically informed. There was no clear relationship between their definitions, understanding of children’s learning, pedagogy or source of knowledge. Most of the teachers were using discussion, negotiation and reflection to develop the children’s moral and social behaviour. This is probably effective; however, it suggests a strong need for teaching of moral development to be given more prominence and addressed directly in in-service courses so that teachers are clear about their intentions and the most effective ways of achieving them.

The association between playgroup participation, learning competence and social-emotional wellbeing for children aged 4-5 years in Australia

Data from Growing Up in Australia: The Longitudinal Study of Australian Children is used to examine the associations between playgroup participation and the outcomes for children aged 4 to 5 years. Controlling for a range of socio-economic and family characteristics, playgroup participation across the ages of 0-3 years was used to predict learning competence and social-emotional functioning outcomes at age 4-5 years. For learning competence, both boys and girls from disadvantaged families scored 3-4% higher if they attended playgroup when aged 0-1 and 2-3 years compared to boys and girls from disadvantaged families who did not attend playgroup. For social and emotional functioning, girls from disadvantaged families who attended playgroup when they were aged 0-1 and 2-3 years scored nearly 5% higher than those who did not attend. Demographic characteristics also showed that disadvantaged families were the families least likely to access these services. Despite data limitations, this study provides evidence that continued participation in playgroups is associated with better outcomes for children from disadvantaged families.

A social marketing approach to value creation in a Well-Women’s health service

Understanding consumer value is imperative in health care as the receipt of value drives the demand for health care services. While there is increasing research into health-care that adopts an economic approach to value, this paper investigates a non-financial exchange context and uses an experiential approach to value, guided by a social marketing approach to behaviour change. An experiential approach is deemed more appropriate for government health-care services that are free and for preventative rather than treatment purposes. Thus instead of using an illness-paradigm to view health services outcomes, we adopt a wellness paradigm. Using qualitative data gathered during 25 depth interviews the authors demonstrate how social marketing thinking has guided the identification of six themes that represent four dimensions of value (functional, emotional, social and altruistic) evident during the health care consumption process of a free government service.

Neo-planning: Location-based social media to engage Australia’s new digital locals

Community engagement with time poor and seemingly apathetic citizens continues to challenge local governments. Capturing the attention of a digitally literate community who are technology and socially savvy adds a new quality to this challenge. Community engagement is resource and time intensive, yet local governments have to manage on continually tightened budgets. The benefits of assisting citizens in taking ownership in making their community and city a better place to live in collaboration with planners and local governments are well established. This study investigates a new collaborative form of civic participation and engagement for urban planning that employs in-place digital augmentation. It enhances people’s experience of physical spaces with digital technologies that are directly accessible within that space, in particular through interaction with mobile phones and public displays. The study developed and deployed a system called Discussions in Space (DIS) in conjunction with a major urban planning project in Brisbane. Planners used the system to ask local residents planning-related questions via a public screen, and passers-by sent responses via SMS or Twitter onto the screen for others to read and reflect, hence encouraging in-situ, real-time, civic discourse. The low barrier of entry proved to be successful in engaging a wide range of residents who are generally not heard due to their lack of time or interest. The system also reflected positively on the local government for reaching out in this way. Challenges and implications of the short-texted and ephemeral nature of this medium were evaluated in two focus groups with urban planners. The paper concludes with an analysis of the planners’ feedback evaluating the merits of the data generated by the system to better engage with Australia’s new digital locals.

New variational Bayesian approaches for statistical data mining : with applications to profiling and differentiating habitual consumption behaviour of customers in the wireless telecommunication industry

This thesis investigates profiling and differentiating customers through the use of statistical data mining techniques. The business application of our work centres on examining individuals’ seldomly studied yet critical consumption behaviour over an extensive time period within the context of the wireless telecommunication industry; consumption behaviour (as oppose to purchasing behaviour) is behaviour that has been performed so frequently that it become habitual and involves minimal intentions or decision making. Key variables investigated are the activity initialised timestamp and cell tower location as well as the activity type and usage quantity (e.g., voice call with duration in seconds); and the research focuses are on customers’ spatial and temporal usage behaviour. The main methodological emphasis is on the development of clustering models based on Gaussian mixture models (GMMs) which are fitted with the use of the recently developed variational Bayesian (VB) method. VB is an efficient deterministic alternative to the popular but computationally demandingMarkov chainMonte Carlo (MCMC) methods. The standard VBGMMalgorithm is extended by allowing component splitting such that it is robust to initial parameter choices and can automatically and efficiently determine the number of components. The new algorithm we propose allows more effective modelling of individuals’ highly heterogeneous and spiky spatial usage behaviour, or more generally human mobility patterns; the term spiky describes data patterns with large areas of low probability mixed with small areas of high probability. Customers are then characterised and segmented based on the fitted GMM which corresponds to how each of them uses the products/services spatially in their daily lives; this is essentially their likely lifestyle and occupational traits. Other significant research contributions include fitting GMMs using VB to circular data i.e., the temporal usage behaviour, and developing clustering algorithms suitable for high dimensional data based on the use of VB-GMM.