short-paper

Recommending Scientific Papers: The Role of Citation Contexts

Authors:

Iana AtanassovaAuthors Info & Claims

DTUC '18: Proceedings of the 1st International Conference on Digital Tools & Uses Congress

Article No.: 6, Pages 1 - 4

https://doi.org/10.1145/3240117.3240123

Published: 03 October 2018 Publication History

Abstract

This paper addresses the problem of building recommender systems for scientific papers based on the linguistic and contextual analysis of citation contexts. We explain the importance of taking into consideration citation contexts and the different methodologies that exist as well as the ways that citations impact recommender systems. We also discuss the limits of using citation contexts to generate recommendations.

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Cited By

Hidayat DSensuse DElisabeth DHasani L(2022)Conceptual model of knowledge management system for scholarly publication cycle in academic institutionVINE Journal of Information and Knowledge Management Systems10.1108/VJIKMS-08-2021-016355:1(187-222)Online publication date: 8-Dec-2022
https://doi.org/10.1108/VJIKMS-08-2021-0163
Katyayan ABokhare AGupta RKumari SPardeshi T(2022)Analysis of Unsupervised Machine Learning Techniques for Customer SegmentationMachine Learning and Autonomous Systems10.1007/978-981-16-7996-4_35(483-498)Online publication date: 10-Feb-2022
https://doi.org/10.1007/978-981-16-7996-4_35

Index Terms

Recommending Scientific Papers: The Role of Citation Contexts
1. Computer systems organization
  1. Dependable and fault-tolerant systems and networks
    1. Redundancy
  2. Embedded and cyber-physical systems
    1. Embedded systems
    2. Robotics
2. Networks
  1. Network properties
    1. Network reliability

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DTUC '18: Proceedings of the 1st International Conference on Digital Tools & Uses Congress

October 2018

148 pages

ISBN:9781450364515

DOI:10.1145/3240117

Copyright © 2018 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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CNAM: Conservatoire des Arts et Métiers
Univ. of Turin: University of Turin
Université Paris 8: Université Paris 8

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 03 October 2018

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DTUC '18

DTUC '18: Digital Tools & Uses Congress

October 3 - 5, 2018

Paris, France

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DTUC '18 Paper Acceptance Rate 26 of 46 submissions, 57%;

Overall Acceptance Rate 48 of 88 submissions, 55%

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Cited By

Hidayat DSensuse DElisabeth DHasani L(2022)Conceptual model of knowledge management system for scholarly publication cycle in academic institutionVINE Journal of Information and Knowledge Management Systems10.1108/VJIKMS-08-2021-016355:1(187-222)Online publication date: 8-Dec-2022
https://doi.org/10.1108/VJIKMS-08-2021-0163
Katyayan ABokhare AGupta RKumari SPardeshi T(2022)Analysis of Unsupervised Machine Learning Techniques for Customer SegmentationMachine Learning and Autonomous Systems10.1007/978-981-16-7996-4_35(483-498)Online publication date: 10-Feb-2022
https://doi.org/10.1007/978-981-16-7996-4_35

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