An incremental FP-growth web content mining and its application in preference identification

This paper presents a real application of Web-content mining using an incremental FP-Growth approach. We firstly restructure the semi-structured data retrieved from the web pages of Chinese car market to fit into the local database, and then employ an incremental algorithm to discover the association rules for the identification of car preference. To find more general regularities, a method of attribute-oriented induction is also utilized to find customer’s consumption preferences. Experimental results show some interesting consumption preference patterns that may be beneficial for the government in making policy to encourage and guide car consumption.

Giving content to the principle of proportionality: happiness and pain as the universal currency for matching offence seriousness and penalty severity

The principle of proportionality prescribes that the punishment should equal the crime. It is one of the most important principles of sentencing. Yet, despite its widespread acceptance it offers no meaningful guide to sentencing. Hence penalty levels fluctuate greatly between jurisdictions and within jurisdictions. This is because there is no universally agreed criterion for measuring offence seriousness or penalty severity. This article suggests that the appropriate criteria for matching offence seriousness and penalty severity is the level of unhappiness or pain stemming from each of these impositions. Thus, for example, the level of pain meted out to a rape offender should equal the level of pain caused to a rape victim. Emerging scientific studies on human well-being and happiness show that human beings are similarly built in terms of the experiences that are either conducive or inimical to well-being. This commonality provides a strong foundation to be confident to make reasonably accurate predictions concerning the extent to which adverse events, such as being the victim of a criminal offence or subjected to a form of criminal sanction will stifle human flourishing. This will then allow us to match accurately offence seriousness and penalty level.

User-generated content and the changing news cycle

Blogs represent a major development in media consumption and practice.  The Pew Center in the United States reported in mid-2005 that about eight million Americans had created blogs and 32 million read them.  That's equivalent to two-thirds the number of people who read a daily newspaper during a week, a challenging giguew in the context of dwindling circulations.  Blogs represent the start of the 'personal media' revolution, but are only the tip of a range of new media developments.  This paper describes the blog phenomenon and notes its arrival via a series of major new stories.  It suggests we are seeing the emergence of a new news cycle, as blogs and other internet-based media usurp broadcast's role in breaking news.  The paper describes a range of emerging digital journalism forms that make up the 'personal media' revolution.  These include blogs delivered via mobile phones (moblogs); video-based blogs (v-logs); newspapers' use of podcasting to deliver content; and wikis, or peer-generated online content. The media's reaction to this new form of content is described, and the other concludes by looking at the forces driving this new form of journalism.

Selenium content of Australian foods: a review of literature values

The aim of this study was to review the published literature values for the selenium content of Australian foods. A secondary aim was to compare the results for Australian foods with food composition data from international sources to investigate the extent of geographical variation. Published food composition data sources for the selenium content in Australian foods were identified and assessed for data quality using established criteria. The selenium content is available for 148 individual food items. The highest values found are for fish (12.0–63.2 μg/100 g), meats (4.75–37.9 μg/100 g) and eggs (9.00–41.4 μg/100 g), followed by cereals (1.00–20.3 μg/100 g). Moderate levels are seen in dairy products (2.00–7.89 μg/100 g) while most fruits and vegetables have low levels (trace—3.27 μg/100 g). High selenium foods show the greatest level of geographical variation, with foods from the United States generally having higher selenium levels than Australian foods and foods from the United Kingdom and New Zealand having lower levels. This is the first attempt to review the available literature for selenium composition of Australian foods. These data serve as an interim measure for the assessment of selenium intake for use in epidemiological studies of diet–disease relationships.

An web content based data mining for car consumption in China

This paper introduces an incremental FP-Growth approach for Web content based data mining and its application in solving a real world problem The problem is solved in the following ways. Firstly, we obtain the semi-structured data from the Web pages of Chinese car market and structure them and save them in local database. Secondly, we use an incremental FP-Growth algorithm for mining association rules to discover Chinese consumers' car consumption preference. To find more general regularities, an attribute-oriented induction method is also utilized to find customer's consumption preference among a range of car categories. Experimental results have revealed some interesting consumption preferences that are useful for the decision makers to make the policy to encourage and guide car consumption. Although the current data we used may not be the best representative of the actual market in practice, it is still good enough for the decision making purpose in terms of reflecting the real situation of car consumption preference under the two assumptions in the context.