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What are the grand challenges for data mining?: KDD-2006 panel report

Authors:

Gregory Piatetsky-Shapiro,

Mohammed ZakiAuthors Info & Claims

ACM SIGKDD Explorations Newsletter, Volume 8, Issue 2

Pages 70 - 77

https://doi.org/10.1145/1233321.1233330

Published: 01 December 2006 Publication History

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Abstract

We discuss what makes exciting and motivating Grand Challenge problems for Data Mining, and propose criteria for a good Grand Challenge. We then consider possible GC problems from multimedia mining, link mining, large-scale modeling, text mining, and proteomics. This report is the result of a panel held at KDD-2006 conference.

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Index Terms

What are the grand challenges for data mining?: KDD-2006 panel report
1. Information systems
  1. Information systems applications

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Information

Published In

ACM SIGKDD Explorations Newsletter Volume 8, Issue 2

December 2006

106 pages

ISSN:1931-0145

EISSN:1931-0153

DOI:10.1145/1233321

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Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 December 2006

Published in SIGKDD Volume 8, Issue 2

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Bertsimas DOrfanoudaki AWiberg H(2021)Interpretable clustering: an optimization approachMachine Language10.1007/s10994-020-05896-2110:1(89-138)Online publication date: 1-Jan-2021
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Allen JGalescu LTeng CPerera I(2020)Conversational Agents for Complex Collaborative TasksAI Magazine10.1609/aimag.v41i4.738441:4(54-78)Online publication date: 1-Dec-2020
https://dl.acm.org/doi/10.1609/aimag.v41i4.7384
Jannach DBauer C(2020)Escaping the McNamara FallacyAI Magazine10.1609/aimag.v41i4.531241:4(79-95)Online publication date: 1-Dec-2020
https://dl.acm.org/doi/10.1609/aimag.v41i4.5312
Clark PEtzioni OKhashabi DKhot TMishra BRichardson KSabharwal ASchoenick CTafjord OTandon NBhakthavatsalam SGroeneveld DGuerquin MSchmitz M(2020)From F to A on the New York Regents Science Exams — An Overview of the Aristo ProjectAI Magazine10.1609/aimag.v41i4.530441:4(39-53)Online publication date: 1-Dec-2020
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Azhar MLi MZhexue Huang J(2019)A Hierarchical Gamma Mixture Model-Based Method for Classification of High-Dimensional DataEntropy10.3390/e2109090621:9(906)Online publication date: 18-Sep-2019
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Yang MHsu WKallumadi S(2018)Predictive Analytics of Social NetworksSocial Media Marketing10.4018/978-1-5225-5637-4.ch042(823-862)Online publication date: 2018
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Liu XChen FLu YLu C(2017)Spatial Prediction for Multivariate Non-Gaussian DataACM Transactions on Knowledge Discovery from Data10.1145/302266911:3(1-27)Online publication date: 27-Mar-2017
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Sebastian YSiew EOrimaye S(2017)Emerging approaches in literature-based discovery: techniques and performance reviewThe Knowledge Engineering Review10.1017/S026988891700004232Online publication date: 16-May-2017
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Yang MHsu WKallumadi S(2016)Predictive Analytics of Social NetworksBusiness Intelligence10.4018/978-1-4666-9562-7.ch056(1080-1116)Online publication date: 2016
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Lu YChen FWang YLu C(2016)Discovering Anomalies on Mixed-Type Data Using a Generalized Student-$t$ Based ApproachIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2016.258342928:10(2582-2595)Online publication date: 1-Oct-2016
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