NDLI: Top-k and Clustering with Noisy Comparisons

Content Provider	ACM Digital Library
Author	Khanna, Sanjeev Milo, Tova Davidson, Susan Roy, Sudeepa
Copyright Year	2014
Abstract	We study the problems of $max/top-\textit{k}$ and clustering when the comparison operations may be performed by oracles whose answer may be erroneous. Comparisons may either be of $\textit{type}$ or of $\textit{value}:$ given two data elements, the answer to a type comparison is “yes” if the elements have the same type and therefore belong to the same group (cluster); the answer to a value comparison orders the two data elements. We give efficient algorithms that are guaranteed to achieve correct results with high probability, analyze the cost of these algorithms in terms of the total number of comparisons (i.e., using a fixed-cost model), and show that they are essentially the best possible. We also show that fewer comparisons are needed when values and types are correlated, or when the error model is one in which the error decreases as the distance between the two elements in the sorted order increases. Finally, we examine another important class of cost functions, concave functions, which balances the number of rounds of interaction with the oracle with the number of questions asked of the oracle. Results of this article form an important first step in providing a formal basis for $max/top-\textit{k}$ and clustering queries in crowdsourcing applications, that is, when the oracle is implemented using the crowd. We explain what simplifying assumptions are made in the analysis, what results carry to a generalized crowdsourcing setting, and what extensions are required to support a full-fledged model.
Starting Page	1
Ending Page	39
Page Count	39
File Format	PDF
ISSN	03625915
e-ISSN	15574644
DOI	10.1145/2684066
Volume Number	39
Issue Number	4
Journal	ACM Transactions on Database Systems (TODS)
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2014-12-30
Publisher Place	New York
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	$Top-\textit{k}$ Algorithm Approximation Clustering Crowdsourcing
Content Type	Text
Resource Type	Article
Subject	Information Systems

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 Library 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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