demonstration

EventCube: multi-dimensional search and mining of structured and text data

KDD '13: Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining

Pages 1494 - 1497

https://doi.org/10.1145/2487575.2487718

Published: 11 August 2013 Publication History

Abstract

A large portion of real world data is either text or structured (e.g., relational) data. Moreover, such data objects are often linked together (e.g., structured specification of products linking with the corresponding product descriptions and customer comments). Even for text data such as news data, typed entities can be extracted with entity extraction tools. The EventCube project constructs TextCube and TopicCube from interconnected structured and text data (or from text data via entity extraction and dimension building), and performs multidimensional search and analysis on such datasets, in an informative, powerful, and user-friendly manner. This proposed EventCube demo will show the power of the system not only on the originally designed ASRS (Aviation Safety Report System) data sets, but also on news datasets collected from multiple news agencies, and academic datasets constructed from the DBLP and web data. The system has high potential to be extended in many powerful ways and serve as a general platform for search, OLAP (online analytical processing) and data mining on integrated text and structured data. After the system demo in the conference, the system will be put on the web for public access and evaluation.

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Zhang CHan J(2019)Multidimensional Mining of Massive Text DataSynthesis Lectures on Data Mining and Knowledge Discovery10.2200/S00903ED1V01Y201902DMK01711:2(1-198)Online publication date: 21-Mar-2019
https://doi.org/10.2200/S00903ED1V01Y201902DMK017
Meng YHuang JShang JHan J(2019)TextCubeProceedings of the VLDB Endowment10.14778/3352063.335211312:12(1974-1977)Online publication date: 1-Aug-2019
https://dl.acm.org/doi/10.14778/3352063.3352113
Janakiraman VGuo YFarooq F(2018)Explaining Aviation Safety Incidents Using Deep Temporal Multiple Instance LearningProceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining10.1145/3219819.3219871(406-415)Online publication date: 19-Jul-2018
https://dl.acm.org/doi/10.1145/3219819.3219871
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Index Terms

EventCube: multi-dimensional search and mining of structured and text data
1. Information systems
  1. Information systems applications
    1. Data mining

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Published In

KDD '13: Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining

August 2013

1534 pages

ISBN:9781450321747

DOI:10.1145/2487575

Editors:
Rayid Ghani
University of Chicago
,
Ted E. Senator
SAIC
,
Paul Bradley
MethodCare, Inc.
,
Rajesh Parekh
Groupon
,
Jingrui He
Stevens Institute of Technology
,
General Chairs:
Robert L. Grossman
University of Chicago and Open Data Group
,
Ramasamy Uthurusamy
General Motors Corporation (retired)
,
Program Chairs:
Inderjit S. Dhillon
University of Texas
,
Yehuda Koren
Google

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Published: 11 August 2013

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KDD' 13: The 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

August 11 - 14, 2013

Illinois, Chicago, USA

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KDD '13 Paper Acceptance Rate 125 of 726 submissions, 17%;

Overall Acceptance Rate 1,133 of 8,635 submissions, 13%

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Zhang CHan J(2019)Multidimensional Mining of Massive Text DataSynthesis Lectures on Data Mining and Knowledge Discovery10.2200/S00903ED1V01Y201902DMK01711:2(1-198)Online publication date: 21-Mar-2019
https://doi.org/10.2200/S00903ED1V01Y201902DMK017
Meng YHuang JShang JHan J(2019)TextCubeProceedings of the VLDB Endowment10.14778/3352063.335211312:12(1974-1977)Online publication date: 1-Aug-2019
https://dl.acm.org/doi/10.14778/3352063.3352113
Janakiraman VGuo YFarooq F(2018)Explaining Aviation Safety Incidents Using Deep Temporal Multiple Instance LearningProceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining10.1145/3219819.3219871(406-415)Online publication date: 19-Jul-2018
https://dl.acm.org/doi/10.1145/3219819.3219871
Jiang MFaloutsos CHan JKrishnapuram BShah MSmola AAggarwal CShen DRastogi R(2016)CatchTartanProceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining10.1145/2939672.2939749(945-954)Online publication date: 13-Aug-2016
https://dl.acm.org/doi/10.1145/2939672.2939749
Li KZhang JYao CShi C(2016)Automatic Relation Extraction from Text: A Survey2016 International Conference on Identification, Information and Knowledge in the Internet of Things (IIKI)10.1109/IIKI.2016.58(83-86)Online publication date: Oct-2016
https://doi.org/10.1109/IIKI.2016.58
Leite Dde Souza Baptista Cde Oliveira MFilho JEduardo da Silva T(2016)ExpOLAP: Towards exploratory OLAP2016 IEEE/ACS 13th International Conference of Computer Systems and Applications (AICCSA)10.1109/AICCSA.2016.7945731(1-8)Online publication date: Nov-2016
https://doi.org/10.1109/AICCSA.2016.7945731
Tao FBrova GHan JJi HWang CNorick BEl-Kishky ALiu JRen XSun YDyreson CLi FÖzsu M(2014)NewsNetExplorerProceedings of the 2014 ACM SIGMOD International Conference on Management of Data10.1145/2588555.2594537(1091-1094)Online publication date: 18-Jun-2014
https://dl.acm.org/doi/10.1145/2588555.2594537
Kamat NJayachandran PTunga KNandi A(2014)Distributed and interactive cube exploration2014 IEEE 30th International Conference on Data Engineering10.1109/ICDE.2014.6816674(472-483)Online publication date: Mar-2014
https://doi.org/10.1109/ICDE.2014.6816674

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