EStream: online mining of frequent sets with precise error guarantee

In data stream applications, a good approximation obtained in a timely  manner is often better than the exact answer that’s delayed beyond the window of opportunity. Of course, the quality of the approximate is as important as its timely delivery. Unfortunately, algorithms capable of online processing do not conform strictly to a precise error guarantee. Since online processing is essential and so is the precision of the error, it is necessary that stream algorithms meet both criteria. Yet, this is not the case for mining frequent sets in data streams. We present EStream, a novel algorithm that allows online processing while producing results strictly within the error bound. Our theoretical and experimental results show that EStream is a better candidate for finding frequent sets in data streams, when both constraints need to be satisfied.

Adaptive load shedding for mining frequent patterns from data streams

Most algorithms that focus on discovering frequent patterns from data streams assumed that the machinery is capable of managing all the incoming transactions without any delay; or without the need to drop transactions. However, this assumption is often impractical due to the inherent characteristics of data stream environments. Especially under high load conditions, there is often a shortage of system resources to process the incoming transactions. This causes unwanted latencies that in turn, affects the applicability of the data mining models produced – which often has a small window of opportunity. We propose a load shedding algorithm to address this issue. The algorithm adaptively detects overload situations and drops transactions from data streams using a probabilistic model. We tested our algorithm on both synthetic and real-life datasets to verify the feasibility of our algorithm.

Automatic pattern-taxonomy extraction for web mining

In this paper, we propose a model for discovering frequent sequential patterns, phrases, which can be used as profile descriptors of documents. It is indubitable that we can obtain numerous phrases using data mining algorithms. However, it is difficult to use these phrases effectively for answering what users want. Therefore, we present a pattern taxonomy extraction model which performs the task of extracting descriptive frequent sequential patterns by pruning the meaningless ones. The model then is extended and tested by applying it to the information filtering system. The results of the experiment show that pattern-based methods outperform the keyword-based methods. The results also indicate that removal of meaningless patterns not only reduces the cost of computation but also improves the effectiveness of the system.

Safely delegating data mining tasks

Data mining is playing an important role in decision making for business activities and governmental administration. Since many organizations or their divisions do not possess the in-house expertise and infrastructure for data mining, it is beneficial to delegate data mining tasks to external service providers. However, the organizations or divisions may lose of private information during the delegating process. In this paper, we present a Bloom filter based solution to enable organizations or their divisions to delegate the tasks of mining association rules while protecting data privacy. Our approach can achieve high precision in data mining by only trading-off storage requirements, instead of by trading-off the level of privacy preserving.

Vision for transnational curriculum inquiry

This essay presents the foundation Editor's vision for Transnational Curriculum Inquiry (TCI), the journal of the International Association for the Advancement of Curriculum Studies (IAACS). It explores some theoretical and practical possibilities for building new transnational and transcultural solidarities in postcolonial curriculum inquiry and argues that building such solidarities requires a rethinking of the ways in which we perform and represent curriculum inquiry, so that curriculum work within a global knowledge economy does not merely assimilate national (local) curriculum discourses-practices into an imperial (global) archive.

Transnational citizenship: problems of definition, culture and democracy

There is widespread disagreement over whether transnational citizenship provides defensible extensions of, or meaningful complements to, national citizenship. A significant strand of criticism relies upon empirical arguments about political motivation and the consequences of transnationalism. This paper addresses two questions arising from empirical arguments relating to the nation state and democracy. Do the alleged cultural requirements for effective political action provide an insuperable barrier to transnational citizenship? Does transnational citizenship necessarily require a commitment to transnational democracy? I argue that these largely empirical criticisms do not succeed in casting doubt upon the normative plausibility or practical viability of transnational projects. On the first question, I point to a growing transnational political culture that serves to motivate transnational citizens. On the second question, I argue for a legitimate category of transnational citizenship that, although inspired by cosmopolitan morality, is different from it, and that does not require transnational democracy.

Transnational curriculum inquiry : building postcolonialist constituencies and solidarities

In this paper I explore some theoretical and practical possibilities for building new transnational and transcultural solidarities in postcolonial curriculum inquiry. I argue that building such solidarities requires a rethinking of the ways in which we perform and represent curriculum inquiry, so that curriculum work within a global knowledge economy does not merely assimilate national (local) curriculum discourses-practices into an imperial (global) archive. I draw on the initial stages of research on internationalisation, inclusivity, and innovative knowledge work conducted with colleagues at Deakin University, and elsewhere, which focuses on the possibilities of producing knowledge in transnational virtual spaces. This includes studies of the formation of new (and we hope more inclusive) transnational scholarly communities and constituencies, and of strategies to improve modes of intercultural communication that facilitate transnational knowledge work. I situate part of my discussion of these arguments and issues in the practicalities of establishing Transnational Curriculum Inquiry (TCI), an electronic open-access journal that is both a site for transnational scholarly conversations and a site for inquiry into the ways that electronic publishing procedures facilitate and/or constrain inclusive knowledge work and postcolonialist curriculum inquiry.