Scalable learning technologies for big data mining

Gerard De Melo, Aparna Varde

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

As data expands into big data, enhanced or entirely novel data mining algorithms often become necessary. The real value of big data is often only exposed when we can adequately mine and learn from it. We provide an overview of new scalable techniques for knowledge discovery. Our focus is on the areas of cloud data mining and machine learning, semi-supervised processing, and deep learning. We also give practical advice for choosing among different methods and discuss open research problems and concerns.

Original languageEnglish
Title of host publicationDatabase Systems for Advanced Applications - 20th International Conference, DASFAA 2015, Hanoi, Vietnam, April 20-23, 2015 Proceedings, Part II
EditorsMuhammad Aamir Cheema, Matthias Renz, Cyrus Shahabi, Xiaofang Zhou
PublisherSpringer Verlag
ISBN (Print)9783319181226
StatePublished - 1 Jan 2015
Event20th International Conference on Database Systems for Advanced Applications, DASFAA 2015 - Hanoi, Viet Nam
Duration: 20 Apr 201523 Apr 2015

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9050
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other20th International Conference on Database Systems for Advanced Applications, DASFAA 2015
CountryViet Nam
CityHanoi
Period20/04/1523/04/15

Fingerprint

Data mining
Data Mining
Knowledge Discovery
Expand
Learning systems
Machine Learning
Necessary
Processing
Learning
Big data
Deep learning

Keywords

  • Big Data
  • Cloud Data Mining
  • Deep Learning
  • Semi-Supervised Learning

Cite this

De Melo, G., & Varde, A. (2015). Scalable learning technologies for big data mining. In M. A. Cheema, M. Renz, C. Shahabi, & X. Zhou (Eds.), Database Systems for Advanced Applications - 20th International Conference, DASFAA 2015, Hanoi, Vietnam, April 20-23, 2015 Proceedings, Part II (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9050). Springer Verlag.
De Melo, Gerard ; Varde, Aparna. / Scalable learning technologies for big data mining. Database Systems for Advanced Applications - 20th International Conference, DASFAA 2015, Hanoi, Vietnam, April 20-23, 2015 Proceedings, Part II. editor / Muhammad Aamir Cheema ; Matthias Renz ; Cyrus Shahabi ; Xiaofang Zhou. Springer Verlag, 2015. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
@inproceedings{783a3e7117aa41ddbf0afefc5ab07e5b,
title = "Scalable learning technologies for big data mining",
abstract = "As data expands into big data, enhanced or entirely novel data mining algorithms often become necessary. The real value of big data is often only exposed when we can adequately mine and learn from it. We provide an overview of new scalable techniques for knowledge discovery. Our focus is on the areas of cloud data mining and machine learning, semi-supervised processing, and deep learning. We also give practical advice for choosing among different methods and discuss open research problems and concerns.",
keywords = "Big Data, Cloud Data Mining, Deep Learning, Semi-Supervised Learning",
author = "{De Melo}, Gerard and Aparna Varde",
year = "2015",
month = "1",
day = "1",
language = "English",
isbn = "9783319181226",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
editor = "Cheema, {Muhammad Aamir} and Matthias Renz and Cyrus Shahabi and Xiaofang Zhou",
booktitle = "Database Systems for Advanced Applications - 20th International Conference, DASFAA 2015, Hanoi, Vietnam, April 20-23, 2015 Proceedings, Part II",

}

De Melo, G & Varde, A 2015, Scalable learning technologies for big data mining. in MA Cheema, M Renz, C Shahabi & X Zhou (eds), Database Systems for Advanced Applications - 20th International Conference, DASFAA 2015, Hanoi, Vietnam, April 20-23, 2015 Proceedings, Part II. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 9050, Springer Verlag, 20th International Conference on Database Systems for Advanced Applications, DASFAA 2015, Hanoi, Viet Nam, 20/04/15.

Scalable learning technologies for big data mining. / De Melo, Gerard; Varde, Aparna.

Database Systems for Advanced Applications - 20th International Conference, DASFAA 2015, Hanoi, Vietnam, April 20-23, 2015 Proceedings, Part II. ed. / Muhammad Aamir Cheema; Matthias Renz; Cyrus Shahabi; Xiaofang Zhou. Springer Verlag, 2015. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9050).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

TY - GEN

T1 - Scalable learning technologies for big data mining

AU - De Melo, Gerard

AU - Varde, Aparna

PY - 2015/1/1

Y1 - 2015/1/1

N2 - As data expands into big data, enhanced or entirely novel data mining algorithms often become necessary. The real value of big data is often only exposed when we can adequately mine and learn from it. We provide an overview of new scalable techniques for knowledge discovery. Our focus is on the areas of cloud data mining and machine learning, semi-supervised processing, and deep learning. We also give practical advice for choosing among different methods and discuss open research problems and concerns.

AB - As data expands into big data, enhanced or entirely novel data mining algorithms often become necessary. The real value of big data is often only exposed when we can adequately mine and learn from it. We provide an overview of new scalable techniques for knowledge discovery. Our focus is on the areas of cloud data mining and machine learning, semi-supervised processing, and deep learning. We also give practical advice for choosing among different methods and discuss open research problems and concerns.

KW - Big Data

KW - Cloud Data Mining

KW - Deep Learning

KW - Semi-Supervised Learning

UR - http://www.scopus.com/inward/record.url?scp=84942693823&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:84942693823

SN - 9783319181226

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

BT - Database Systems for Advanced Applications - 20th International Conference, DASFAA 2015, Hanoi, Vietnam, April 20-23, 2015 Proceedings, Part II

A2 - Cheema, Muhammad Aamir

A2 - Renz, Matthias

A2 - Shahabi, Cyrus

A2 - Zhou, Xiaofang

PB - Springer Verlag

ER -

De Melo G, Varde A. Scalable learning technologies for big data mining. In Cheema MA, Renz M, Shahabi C, Zhou X, editors, Database Systems for Advanced Applications - 20th International Conference, DASFAA 2015, Hanoi, Vietnam, April 20-23, 2015 Proceedings, Part II. Springer Verlag. 2015. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).