NDLI: Domain-agnostic discovery of similarities and concepts at scale

Content Provider	Springer Nature Link
Author	Görnerup, Olof Gillblad, Daniel Vasiloudis, Theodore
Copyright Year	2016
Abstract	Appropriately defining and efficiently calculating similarities from large data sets are often essential in data mining, both for gaining understanding of data and generating processes and for building tractable representations. Given a set of objects and their correlations, we here rely on the premise that each object is characterized by its context, i.e., its correlations to the other objects. The similarity between two objects can then be expressed in terms of the similarity between their contexts. In this way, similarity pertains to the general notion that objects are similar if they are exchangeable in the data. We propose a scalable approach for calculating all relevant similarities among objects by relating them in a correlation graph that is transformed to a similarity graph. These graphs can express rich structural properties among objects. Specifically, we show that concepts—abstractions of objects—are constituted by groups of similar objects that can be discovered by clustering the objects in the similarity graph. These principles and methods are applicable in a wide range of fields and will be demonstrated here in three domains: computational linguistics, music, and molecular biology, where the numbers of objects and correlations range from small to very large.
Starting Page	531
Ending Page	560
Page Count	30
File Format	PDF
ISSN	02191377
Journal	Knowledge and Information Systems
Volume Number	51
Issue Number	2
e-ISSN	02193116
Language	English
Publisher	Springer London
Publisher Date	2016-08-30
Publisher Place	London
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Similarity discovery Concept mining Distributional semantics Graph processing Information Systems and Communication Service IT in Business
Content Type	Text
Resource Type	Article
Subject	Artificial Intelligence Information Systems Human-Computer Interaction Hardware and Architecture Software

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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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
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