NDLI: Extraction, Identification, and Ranking of Network Structures from Data Sets

Content Provider	IEEE Xplore Digital Library
Author	Trovati, M. Bessis, N. Huber, A. Zelenkauskaite, A. Asimakopoulou, E.
Copyright Year	2014
Description	Author affiliation: Dept. of Culture & Commun., Drexel Univ., Philadelphia, PA, USA (Zelenkauskaite, A.) \|\| Sch. of Comput. & Math., Univ. of Derby, Derby, UK (Trovati, M.; Bessis, N.; Huber, A.; Asimakopoulou, E.)
Abstract	Networks are widely used to model a variety of complex, often multi-disciplinary, systems in which the relationships between their sub-parts play a significant role. In particular, there is extensive research on the topological properties associated with their structure as this allows the analysis of the overall behaviour of such networks. However, extracting networks from structured and unstructured data sets raises several challenges, including addressing any inconsistency present in the data, as well as the difficulty in investigating their properties especially when the topological structure is not fully determined or not explicitly defined. In this paper, we propose a novel method to address the automated identification, assessment and ranking of the most likely structure associated with networks extracted from a variety of data sets. More specifically, our approach allows to mine data to assess whether their associated networks exhibit properties comparable to well-known structures, namely scale-free, small world and random networks. The main motivation is to provide a toolbox to classify and analyse real-world networks otherwise difficult to fully assess due to their potential lack of structure. This can be used to investigate their dynamical and statistical behaviour which would potentially lead to a better understanding and prediction of the properties of the system (s) they model. Our initial validation shows the potential of our method providing relevant and accurate results.
Starting Page	331
Ending Page	337
File Size	562649
Page Count	7
File Format	PDF
e-ISBN	9781479943258
DOI	10.1109/CISIS.2014.46
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-07-02
Publisher Place	UK
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Sentiment analysis Networks Social graphs Feature extraction Knowledge discovery Data models Data analytics Information extraction Data mining Approximation methods Mathematical model Standards
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 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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