Interestingness Measures for Multi-Level Association Rules

Association rule mining is one technique that is widely used when querying databases, especially those that are transactional, in order to obtain useful associations or correlations among sets of items. Much work has been done focusing on efficiency, effectiveness and redundancy. There has also been a focusing on the quality of rules from single level datasets with many interestingness measures proposed. However, with multi-level datasets now being common there is a lack of interestingness measures developed for multi-level and cross-level rules. Single level measures do not take into account the hierarchy found in a multi-level dataset. This leaves the Support-Confidence approach,which does not consider the hierarchy anyway and has other drawbacks, as one of the few measures available. In this paper we propose two approaches which measure multi-level association rules to help evaluate their interestingness. These measures of diversity and peculiarity can be used to help identify those rules from multi-level datasets that are potentially useful.

Investigating the use of association rules in improving recommender systems

Recommender systems are widely used online to help users find other products, items etc that they may be interested in based on what is known about that user in their profile. Often however user profiles may be short on information and thus when there is not sufficient knowledge on a user it is difficult for a recommender system to make quality recommendations. This problem is often referred to as the cold-start problem. Here we investigate whether association rules can be used as a source of information to expand a user profile and thus avoid this problem, leading to improved recommendations to users. Our pilot study shows that indeed it is possible to use association rules to improve the performance of a recommender system. This we believe can lead to further work in utilising appropriate association rules to lessen the impact of the cold-start problem.

'When everything old is new again' : class, consumerism and masculinity in Alasdair Duncan's Metro

Alasdair Duncan’s narrative Metro, set in Brisbane in the early twenty-first century, focuses on Liam, an unapologetically self-styled ‘white, upper middle-class brat’ whose sense of place and identity is firmly mapped by spatial and economic co-ordinates. This article considers the linkages between spatiality and identity in Duncan’s narrative, as well as the ways in which traditional, hegemonic (heterosexual) forms of masculinity are re-invigorated in the enactment of an upper-middle-class script of success, privilege and consumerism. It argues that the safeguarding of these hegemonic forms of masculine identity involves strategies of spatial and bodily expression underpinned by conspicuous consumption, relegating other forms of sexual identity to an exploitable periphery

Analyzing web multimedia query reformulation behavior

Current multimedia Web search engines still use keywords as the primary means to search. Due to the richness in multimedia contents, general users constantly experience some difficulties in formulating textual queries that are representative enough for their needs. As a result, query reformulation becomes part of an inevitable process in most multimedia searches. Previous Web query formulation studies did not investigate the modification sequences and thus can only report limited findings on the reformulation behavior. In this study, we propose an automatic approach to examine multimedia query reformulation using large-scale transaction logs. The key findings show that search term replacement is the most dominant type of modifications in visual searches but less important in audio searches. Image search users prefer the specified search strategy more than video and audio users. There is also a clear tendency to replace terms with synonyms or associated terms in visual queries. The analysis of the search strategies in different types of multimedia searching provides some insights into user’s searching behavior, which can contribute to the design of future query formulation assistance for keyword-based Web multimedia retrieval systems.

The managerial benefits of tax compliance: perception by small business taxpayers

Research undertaken in 2006 – 2007 investigated the perception of managerial benefits of tax compliance by small business taxpayers. Survey data from a sample of 300 small business taxpayers and responses to semi-structured interviews of owner managers were examined. The study found that a majority of small business taxpayers recognised that tax compliance activities led to better record keeping and to an improved knowledge of their financial affairs. However, there seemed to be a general reluctance by respondents to accept the idea that benefits could be derived as a result of complying with tax. The findings of this study are important as it is the first research that systematically investigated managerial benefits and their perception by small business taxpayers in Australia.