A panorama of imminent doctoral research in data mining

Aparna Varde, Nikolaj Tatti

Research output: Contribution to journalArticleResearchpeer-review

Abstract

As databases head towards data streams, discovering knowledge from the data poses challenges. The need to process and mine data is affected by the big data wave, advances in Web technology and other factors. The advent of the cloud with related technologies provides further momentum to enhance knowledge discovery. Data mining is also of interest to research communities outside computer science as there is a need to harvest data from various domains incorporating domainspecific factors. These and other issues motivate PhD students to pursue core and applied research in data mining along with stream data management, big data, cloud computing, Web knowledge discovery, domainspecific techniques and more. A PhD forum on data mining provides an excellent platform for doctoral students to present imminent research and get valuable feedback from experts. In addition it gives them the opportunity to disseminate the results of their work among fellow researchers, and publish their novel contributions at an early stage. IEEE ICDM hosts such a PhD forum for doctoral students with a data mining focus. This article describes the content of the work presented at the ICDM 2013 PhD forum. It also gives a brief overview of the organization of this forum. The article thus provides a panorama of recent doctoral student work in data mining that would be of interest to researchers in database management and related areas.

Original languageEnglish
Pages (from-to)71-74
Number of pages4
JournalSIGMOD Record
Volume43
Issue number3
DOIs
StatePublished - 1 Sep 2014

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Varde, Aparna ; Tatti, Nikolaj. / A panorama of imminent doctoral research in data mining. In: SIGMOD Record. 2014 ; Vol. 43, No. 3. pp. 71-74.
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A panorama of imminent doctoral research in data mining. / Varde, Aparna; Tatti, Nikolaj.

In: SIGMOD Record, Vol. 43, No. 3, 01.09.2014, p. 71-74.

Research output: Contribution to journalArticleResearchpeer-review

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