NDLI: Exploiting reference section to classify paper's topics

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Exploiting reference section to classify paper's topics

Content Provider	ACM Digital Library
Author	Ali, Tariq Ahmad, Munir Afzal, Muhammad Tanvir Qadir, Muhammad Abdul Sajid, Naseer Ahmed
Abstract	Classification is an important task in data mining. Classification is about organizing data into relevant nodes in taxonomy. In scientific domain, classification of documents to predefined category (ies) is an important research problem and supports number of tasks such as: information retrieval, finding experts, recommender systems etc. In Computer Science, the ACM categorization system is commonly used for organizing research papers in the topical hierarchy defined by the ACM. Accurately assigning a research paper to a predefined category (ACM topic) is a difficult task especially when the paper belongs to multiple topics. In the past, different approaches have been applied to find the actual topics of a paper such as content based analysis, metadata analysis, and semantic analysis etc. However, in this paper, we exploit the reference section of a research paper to discover topics of the paper. It is assumed that in most of the cases, papers belonging to the same or similar category are cited by an author. We have evaluated our technique for a dataset of Journal of Universal Computer Science (J.UCS). Our system collected 1460 documents from J. UCS along with their predefined topics assigned by authors and verified by journal's administration. The system used 1010 documents for training dataset. The system extracted references from training dataset and grouped them in a Topic Reference pair such as TR {Topic, Reference}. Subsequently, the system was tested on the remaining 450 documents. The references of the focused paper are parsed and compared in the pair TR {Topic, Reference}. The system collects corresponding list of topics matched with the references in the said pair. Subsequently multiple weights are assigned during the process of this matching. The system was able to predict the first node in the ACM topic (topic A to K) with 70% accuracy.
Starting Page	220
Ending Page	225
Page Count	6
File Format	PDF
ISBN	9781450310475
DOI	10.1145/2077489.2077531
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2011-11-21
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Acm classification Multi-label classification Document classification Scientific documents classification Citations
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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