NDLI: Using Topic Hierarchies with Privileged Information to Improve Context-Aware Recommender Systems

Content Provider	IEEE Xplore Digital Library
Author	Sundermann, C.V. Domingues, M.A. Marcacini, R.M. Rezende, S.O.
Copyright Year	2014
Description	Author affiliation: Inst. de Cienc. Mat. e de Comput., Univ. de Sao Paulo, Sao Carlos, Brazil (Sundermann, C.V.; Domingues, M.A.; Rezende, S.O.) \|\| Univ. Fed. do Mato Grosso do Sul, Tres Lagoas, Brazil (Marcacini, R.M.)
Abstract	Recommender systems are designed to assist individuals to identify items of interest in a set of options. A context-aware recommender system makes recommendations by incorporating available contextual information into the recommendation process. One of the major challenges in context-aware recommender systems research is the lack of automatic methods to obtain contextual information for these systems. Considering this scenario, in this paper, we propose to use contextual information from topic hierarchies to improve the performance of context-aware recommender systems. Three different types of topic hierarchies are constructed by using the LUPI-based Incremental Hierarchical Clustering method: a topic hierarchy using only a traditional bag-of-words, a second topic hierarchy using a bag-of-words of named entities and a third topic hierarchy using both information. We evaluate the contextual information in four context-aware recommender systems. The empirical results demonstrate that by using topic hierarchies we can provide better recommendations.
Starting Page	61
Ending Page	66
File Size	279505
Page Count	6
File Format	PDF
ISBN	9781479956180
DOI	10.1109/BRACIS.2014.22
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-10-18
Publisher Place	Brazil
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Context Recommender Systems Web pages Context-Aware Recommender Systems Filtering algorithms Topic Hierarchy Data models Text Mining Named Entities Data mining Recommender systems Context modeling
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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