Personalised ontology learning and mining for web information gathering

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.

Granule-based knowledge representation for intra and inter transaction association mining

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.

Effective pattern taxonomy mining in text documents

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.

Where the bloody hell does parody fit in Australian copyright law?

This article examines the role of the recently introduced fair dealing exception for the purposes of parody and satire in Australian copyright law. Parody and satire, while central to Australian expression, pose a substantial challenge for copyright policy. The law is asked to strike a delicate balance between an author’s right to exploit their work, the interests of the public in stimulating free speech and critical discussion, the rights of artists who rely on existing material in creating their own expression, and the rights of all artists in their reputation and the integrity of their works. This article highlights the difficulty parodists and satirists have historically faced in Australia and examines the potential of the new fair dealing exceptions to relieve this difficulty. This article concludes that the new exceptions have the potential, if read broadly, not only to bridge the gap between humorous and non-humorous criticism, but also to allow for the use of copyright material to critique figures other than the copyright owner or author, extending to society generally. This article will argue that the new exceptions should be read broadly to further this important policy goal while also being limited in their application so as to prevent mere substitutable uses of copyright material. To achieve these twin goals, I suggest that the primary indication of fairness of an unlicensed parody should be whether or not it adds significant new expression so as not to be substitutable for the original work.

Traceability : retracing law and public policy on measurement standards

This presentation outlines key aspects of public policy in broad terms insofar as they relate to establishment, implementation and compliance with legal measurement standards. It refers in particular to traceability of a legal measurement unit from its source in a single international standard as a compliance issue. It comments on accreditation of legal measurement and liability concerned with errors in measurement.

Cyber bullying in schools and the law : is there an effective means of addressing the power imbalance?

Cyber bullying – or bullying through the use of technology – is a growing phenomenon which is currently most commonly experienced by young people and the consequences manifested in schools. Cyber bullying shares many of the same attributes as face-to-face bullying such as a power imbalance and a sense of helplessness on the part of the target. Not surprisingly, targets of face-to-face bullying are increasingly turning to the law, and it is likely that targets of cyber bullying may also do so in an appropriate case. This article examines the various criminal, civil and vilification laws that may apply to cases of cyber bullying and assesses the likely effectiveness of these laws as a means of redressing that power imbalance between perpetrator and target.

Researching and writing in law (3rd ed.)

The revolution in legal research provides exciting challenges for those exploring and writing about the legal landscape. Cumbersome paper sources have largely been replaced by electronic files and a new range of skills and sources are required to successfully conduct legal research.--------- Researching and Writing in Law, 3rd Edition is an updated research guide, mapping the developments that have taken place and providing the keys to the fundamental electronic sources of legal research, especially those now available on the web, as well as exploring traditional doctrinal methodologies. Included in this edition are extensive checklists for locating and validating the law in Australia, England, Canada, the United States, New Zealand, India and the European Union.-------- This third edition includes expanded discussion of the process of formulating a research proposal, writing project abstracts and undertaking a literature review (Chapter 7). Research methodologies are also extensively examined, focusing on the process of doctrinal methodology as well as discussing other useful methodologies, such as Comparative Research and Content Analysis (Chapter 5). Further highlighted are issues surrounding research ethics, including plagiarism and originality, the importance of developing skills in critique, and the influence of current university research environments on postgraduate legal research.-------- Law students and members of the practising profession aiming to update their research, knowledge and skills will find Researching and Writing in Law, 3rd Edition invaluable.