Advanced pattern mining for complex sata analysis

The thesis has researched a set of critical problems in data mining and has proposed four advanced pattern mining algorithm to discover the most interesting and useful data patterns highly relevant to the user’s application targets from the data is represented in complex structures.

EFP-M2 : efficient model for mining frequent patterns in transactional database

Discovering frequent patterns plays an essential role in many data mining applications. The aim of frequent patterns is to obtain the information about the most common patterns that appeared together. However, designing an efficient model to mine these patterns is still demanding due to the capacity of current database size. Therefore, we propose an Efficient Frequent Pattern Mining Model (EFP-M2) to mine the frequent patterns in timely manner. The result shows that the algorithm in EFP-M2l is outperformed at least at 2 orders of magnitudes against the benchmarked FP-Growth.

The importance and significance of heritage conservation of ex-tin mining landscape in Perak, the Abode of Grace

The thematic history of tin mining in Perak reveals the evolution of tin production, technology, infrastructure, transportation, social and the state economic development. The mining expansion that spread from Larut district to Kinta at the end of nineteenth century has distinctively impact on it's landscape. The surviving evidences that spread over Kinta demonstrates the importance and significance of conservation of ex-tin mining places. These surviving evidences are testimony of the past history and legacy for the present and future generations.

IPMA : Indirect patterns mining algorithm

Indirect pattern is considered as valuable and hidden information in transactional database. It represents the property of high dependencies between two items that are rarely occurred together but indirectly appeared via another items. Indirect pattern mining is very important because it can reveal a new knowledge in certain domain applications. Therefore, we propose an Indirect Pattern Mining Algorithm (IPMA) in an attempt to mine the indirect patterns from data repository. IPMA embeds with a measure called Critical Relative Support (CRS) measure rather than the common interesting measures. The result shows that IPMA is successful in generating the indirect patterns with the various threshold values.

Policy change and industry associability: the Australian mining sector

In this paper we use evidence from the recent trajectories of mining industry associations in the Australian federation to argue for the significance of institutional explanations for the formation and maintenance of interest groups. We argue that the recent lack of consultation by the Commonwealth government with the Minerals Council of Australia over resources rent taxation proposals reflected a weakness that resulted from the shifting basis of associability stemming from institutional changes.

Recognising user identity in twitter social networks via text mining

Social networks have become a convenient and effective means of communication in recent years. Many people use social networks to communicate, lead, and manage activities, and express their opinions in supporting or opposing different causes. This has brought forward the issue of verifying the owners of social accounts, in order to eliminate the effect of any fake accounts on the people. This study aims to authenticate the genuine accounts versus fake account using writeprint, which is the writing style biometric. We first extract a set of features using text mining techniques. Then, training of a supervised machine learning algorithm to build the knowledge base is conducted. The recognition procedure starts by extracting the relevant features and then measuring the similarity of the feature vector with respect to all feature vectors in the knowledge base. Then, the most similar vector is identified as the verified account.

Recalling yesterday, predicting tomorrow : revisit South Australia conservation practice for heritage mining places, a practical guide for Malaysia

Mining started in South Australia in the early 1840s with the discovery of silver-lead ore at Glen Osmond in 1841 and later copper in Kapunda in 1842 and Burra in 1845; all these discoveries greatly contributed to South Australia's economic development. South Australia entered the mining era at the time when the Cornish engine was at the peak of its development, and the horizontal engine was beginning its rise in popularity. These South Australian historic mining sites contain extensive extant evidence of technology, innovation and human endeavours that previously went into the mining activity. This paper seeks to critically review items for inclusion on the South Australian State Heritage Register, the character of mining heritage places, enforcement by legislation, interpretation of the heritage assessment and how these practices could guide Malaysia in recognizing industrial heritage as a significant part of its cultural heritage that needs to be conserved, restored and managed as a legacy for present and future generations.