NDLI: Active Preference Learning for Ranking Patterns

Content Provider	IEEE Xplore Digital Library
Author	Dzyuba, V. Van Leeuwen, M. Nijssen, S. De Raedt, L.
Copyright Year	2013
Description	Author affiliation: Dept. of Comput. Sci., KU Leuven, Leuven, Belgium (Dzyuba, V.; Van Leeuwen, M.; Nijssen, S.; De Raedt, L.)
Abstract	Pattern mining provides useful tools for exploratory data analysis. Numerous efficient algorithms exist that are able to discover various types of patterns in large datasets. However, the problem of identifying patterns that are genuinely interesting to a particular user remains challenging. Current approaches generally require considerable data mining expertise or effort and hence cannot be used by typical domain experts. We show that it is possible to resolve this issue by interactive learning of user-specific pattern ranking functions, where a user ranks small sets of patterns and a general ranking function is inferred from this feedback by preference learning techniques. We present a general framework for learning pattern ranking functions and propose a number of active learning heuristics that aim at minimizing the required user effort. In particular we focus on Subgroup Discovery, a specific pattern mining task. We evaluate the capacity of the algorithm to learn a ranking of a subgroup set defined by a complex quality measure, given only reasonably small sample rankings. Experiments demonstrate that preference learning has the capacity to learn accurate rankings and that active learning heuristics help reduce the required user effort. Moreover, using learned ranking functions as search heuristics allows discovering subgroups of substantially higher quality than those in the given set. This shows that active preference learning is potentially an important building block of interactive pattern mining systems.
Sponsorship	IEEE Comput. Soc.
Starting Page	532
Ending Page	539
File Size	615285
Page Count	8
File Format	PDF
ISSN	10823409
e-ISBN	9781479929726
DOI	10.1109/ICTAI.2013.85
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-11-04
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Vectors Data mining Context Support vector machines Current measurement Heuristic algorithms Standards pattern mining preference learning active learning
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Libarray of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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