962 resultados para Social mining


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Homelessness is a complex problem that manifests in all societies. This intractable and ‘wicked’ issue resists single-agency solutions and its resolution and requires a large, on-going investment of financial and professional resources that few organisations can sustain. This paper adopts a social innovation framework to examine government and community sector responses to homelessness. While recent evaluations and policy prescriptions have suggested better integrated and more co-ordinated service delivery models for addressing homelessness, there is little understanding of the innovation framework in which alternative service system paradigms emerge. A framework that identifies/distils and explains different innovation levels is put forward. The framework highlights that while government may lead strategic level innovations, community organisations are active in developing innovation at the service and client level. Moreover, community organisations may be unaware of the innovative capacity that resides in their creative responses to resolving social crisis and marginalisation through being without shelter.

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This paper presents a brief analysis of Seoul trans-youth’s search for identity through urban social networking, arguing that technological, socio-cultural and environmental (urban) contexts frame how mobility and ubiquity are (re)created in Seoul. The paper is empirically based on fieldwork conducted in Seoul, South Korea, from 2007 to 2008 as part of a research project on the mobile play culture of Seoul trans-youth(a term that will be explained in detail in the following section). Shared Visual Ethnography (SVE) was used as the research method which involved sharing of visual ethnographic data that were created by the participants. More specifically, the participants were asked to take photos, which were then shared and discussed with other participants and the researcher on the photo-sharing service Flickr. The research also involved a questionnaire and daily activity diaries, as well as interviews. A total of 44 Korean transyouths – including 23 females and 21 males – participated in interviews and photo-sharing. The paper draws specifically on the qualitative data from individual and/or group interviews, the total duration of which was 2–2.5 hours for each participant.

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This paper seeks to identify the sources of value in a government health screening service. Consumers' use of such services for their won benefits demonstrates desirable behaviour and their continued use of these services indicates maintenance of the behaviour. There are also positive outcomes for society as the health of its members is improved overall through this behaviour. Individual-depth interview with 25 women who use breast cancer screening services provided by BreastScreen (BSQ) revealed five categories of sources of value. They are information sources, interaction sources, service, environment, and consumer participation. These findings provide valuable insights into the value construction of consumers and contribute towards our understanding of the value concept in social marketing.

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Traffic safety is a major concern world-wide. It is in both the sociological and economic interests of society that attempts should be made to identify the major and multiple contributory factors to those road crashes. This paper presents a text mining based method to better understand the contextual relationships inherent in road crashes. By examining and analyzing the crash report data in Queensland from year 2004 and year 2005, this paper identifies and reports the major and multiple contributory factors to those crashes. The outcome of this study will support road asset management in reducing road crashes.

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Advertising has recently entered many new spaces it does not fully understand. The rules that apply in traditional media do not always translate in new media environments. However, their low cost of entry and the availability of hard-to-reach target markets, such as Generation Y, make environments such as online social networking sites attractive to marketers. This paper accumulates teenage perspectives from two qualitative studies to identify attitudes towards advertising in online social network sites and develop implications for marketers seeking to advertising on social network sites.

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Background: While the relationship between socioeconomic disadvantage and cardiovascular disease (CVD) is well established, the role that traditional cardiovascular risk factors play in this association remains unclear. We examined the association between education attainment and CVD mortality and the extent to which behavioural, social and physiological factors explained this relationship. Methods: Adults (n=38 355) aged 40-69 years living in Melbourne, Australia were recruited in 1990-1994. Subjects with baseline CVD risk factor data ascertained through questionnaire and physical measurement were followed for an average of 9.4 years with CVD deaths verified by review of medical records and autopsy reports. Results: CVD mortality was higher for those with primary education only compared to those who had completed tertiary education, with a hazard ratio (HR) of 1.66 (95% confidence interval [CI] 1.11-2.49) after adjustment for age, country of birth and gender. Those from the lowest educated group had a more adverse cardiovascular risk factor profile compared to the highest educated group, and adjustment for these risk factors reduced the HR to 1.18 (95% CI 0.78-1.77). In analysis of individual risk factors, smoking and waist circumference explained most of the difference in CVD mortality between the highest and lowest education groups. Conclusions: Most of the excess CVD mortality in lower socioeconomic groups can be explained by known risk factors, particularly smoking and overweight. While targeting cardiovascular risk factors should not divert efforts from addressing the underlying determinants of health inequalities, it is essential that known risk factors are addressed effectively among lower socioeconomic groups.

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Over the last decade, the rapid growth and adoption of the World Wide Web has further exacerbated user needs for e±cient mechanisms for information and knowledge location, selection, and retrieval. How to gather useful and meaningful information from the Web becomes challenging to users. The capture of user information needs is key to delivering users' desired information, and user pro¯les can help to capture information needs. However, e®ectively acquiring user pro¯les is di±cult. It is argued that if user background knowledge can be speci¯ed by ontolo- gies, more accurate user pro¯les can be acquired and thus information needs can be captured e®ectively. Web users implicitly possess concept models that are obtained from their experience and education, and use the concept models in information gathering. Prior to this work, much research has attempted to use ontologies to specify user background knowledge and user concept models. However, these works have a drawback in that they cannot move beyond the subsumption of super - and sub-class structure to emphasising the speci¯c se- mantic relations in a single computational model. This has also been a challenge for years in the knowledge engineering community. Thus, using ontologies to represent user concept models and to acquire user pro¯les remains an unsolved problem in personalised Web information gathering and knowledge engineering. In this thesis, an ontology learning and mining model is proposed to acquire user pro¯les for personalised Web information gathering. The proposed compu- tational model emphasises the speci¯c is-a and part-of semantic relations in one computational model. The world knowledge and users' Local Instance Reposito- ries are used to attempt to discover and specify user background knowledge. From a world knowledge base, personalised ontologies are constructed by adopting au- tomatic or semi-automatic techniques to extract user interest concepts, focusing on user information needs. A multidimensional ontology mining method, Speci- ¯city and Exhaustivity, is also introduced in this thesis for analysing the user background knowledge discovered and speci¯ed in user personalised ontologies. The ontology learning and mining model is evaluated by comparing with human- based and state-of-the-art computational models in experiments, using a large, standard data set. The experimental results are promising for evaluation. The proposed ontology learning and mining model in this thesis helps to develop a better understanding of user pro¯le acquisition, thus providing better design of personalised Web information gathering systems. The contributions are increasingly signi¯cant, given both the rapid explosion of Web information in recent years and today's accessibility to the Internet and the full text world.

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As multi-stakeholder entities that explicitly inhabit both social and economic domains, social enterprises pose new challenges and possibilities for local governance. In this paper, we draw on new institutional theory to examine the ways in which locally-focused social enterprises disrupt path dependencies and rules in use within local government. Rather than examining the more commonly asked question of the influence of the state on social enterprise, our purpose here is to examine the impacts of social enterprise on governmental institutions at the local level. Our discussion is based on a mixed-methods study, including an online survey of 66 local government staff, document analysis, and in-depth interviews with 24 social enterprise practitioners and local government actors working to support social enterprise development in Victoria, Australia. We find that, in some instances, the hybrid nature of social enterprise facilitates ‘joining up’ between different functional areas of local government. Beyond organisational relationships, social enterprise also influences local governance through the reinterpretation and regeneration of institutionalised public spaces.

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Abstract With the phenomenal growth of electronic data and information, there are many demands for the development of efficient and effective systems (tools) to perform the issue of data mining tasks on multidimensional databases. Association rules describe associations between items in the same transactions (intra) or in different transactions (inter). Association mining attempts to find interesting or useful association rules in databases: this is the crucial issue for the application of data mining in the real world. Association mining can be used in many application areas, such as the discovery of associations between customers’ locations and shopping behaviours in market basket analysis. Association mining includes two phases. The first phase, called pattern mining, is the discovery of frequent patterns. The second phase, called rule generation, is the discovery of interesting and useful association rules in the discovered patterns. The first phase, however, often takes a long time to find all frequent patterns; these also include much noise. The second phase is also a time consuming activity that can generate many redundant rules. To improve the quality of association mining in databases, this thesis provides an alternative technique, granule-based association mining, for knowledge discovery in databases, where a granule refers to a predicate that describes common features of a group of transactions. The new technique first transfers transaction databases into basic decision tables, then uses multi-tier structures to integrate pattern mining and rule generation in one phase for both intra and inter transaction association rule mining. To evaluate the proposed new technique, this research defines the concept of meaningless rules by considering the co-relations between data-dimensions for intratransaction-association rule mining. It also uses precision to evaluate the effectiveness of intertransaction association rules. The experimental results show that the proposed technique is promising.

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In recent years, increasing numbers of Chinese migrants have come to Australia to study or to live. In doing so, they have entered a new cultural space. They are faced with many challenges, not only to do with study experience, workplace experience and life-style practices, but also to do with language, communication, culture and identity. Such new challenges can feel dangerous, unstable and uncomfortable as they require moves out of the safety zone of primary cultural experience. This qualitative research study investigates the perceptions and narratives of three Taiwanese-Australian migrants in terms of their experience of this process of acculturation and social identity construction as migrant tertiary students in the new Australian context and of their subsequent experience professionally. Their accounts of where they see themselves to have 'landed' in terms of their acculturation process and identity construction might provide relevant insights to the experience of hybridity which is intercultural Australia.

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Many data mining techniques have been proposed for mining useful patterns in databases. However, how to effectively utilize discovered patterns is still an open research issue, especially in the domain of text mining. Most existing methods adopt term-based approaches. However, they all suffer from the problems of polysemy and synonymy. This paper presents an innovative technique, pattern taxonomy mining, to improve the effectiveness of using discovered patterns for finding useful information. Substantial experiments on RCV1 demonstrate that the proposed solution achieves encouraging performance.