Article

Unsupervised prediction of citation influences

Authors:

Steffen Bickel,

Tobias SchefferAuthors Info & Claims

ICML '07: Proceedings of the 24th international conference on Machine learning

Pages 233 - 240

https://doi.org/10.1145/1273496.1273526

Published: 20 June 2007 Publication History

Abstract

Publication repositories contain an abundance of information about the evolution of scientific research areas. We address the problem of creating a visualization of a research area that describes the flow of topics between papers, quantifies the impact that papers have on each other, and helps to identify key contributions. To this end, we devise a probabilistic topic model that explains the generation of documents; the model incorporates the aspects of topical innovation and topical inheritance via citations. We evaluate the model's ability to predict the strength of influence of citations against manually rated citations.

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Cited By

Koochemeshkian PBouguila N(2024)Flexible Distribution Approaches to Enhance Regression and Deep Topic Modelling TechniquesExpert Systems10.1111/exsy.13789Online publication date: 25-Nov-2024
https://doi.org/10.1111/exsy.13789
Azzam IDas SNanda GGarcia Bravo JBreidi F(2024) Investigating Safety Awareness in Assembly Operations via Mixed Reality Technology IISE Transactions on Occupational Ergonomics and Human Factors10.1080/24725838.2024.2431112(1-17)Online publication date: 4-Dec-2024
https://doi.org/10.1080/24725838.2024.2431112
Sakai YMatsumoto M(2023)Topic Selection Using Conceptual Distance: How to Select Topics that are Interesting but Unfamiliar to UsersIEEJ Journal of Industry Applications10.1541/ieejjia.2200678412:4(588-595)Online publication date: 1-Jul-2023
https://doi.org/10.1541/ieejjia.22006784
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Unsupervised prediction of citation influences
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Published In

cover image ACM Other conferences

ICML '07: Proceedings of the 24th international conference on Machine learning

June 2007

1233 pages

ISBN:9781595937933

DOI:10.1145/1273496

Editor:
Zoubin Ghahramani
University of Cambridge, United Kingdom

Copyright © 2007 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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Machine Learning Journal

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 20 June 2007

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ICML '07 & ILP '07

Sponsor:

ICML '07 & ILP '07: The 24th Annual International Conference on Machine Learning held in conjunction with the 2007 International Conference on Inductive Logic Programming

June 20 - 24, 2007

Oregon, Corvalis, USA

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Overall Acceptance Rate 140 of 548 submissions, 26%

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Citations

Cited By

Koochemeshkian PBouguila N(2024)Flexible Distribution Approaches to Enhance Regression and Deep Topic Modelling TechniquesExpert Systems10.1111/exsy.13789Online publication date: 25-Nov-2024
https://doi.org/10.1111/exsy.13789
Azzam IDas SNanda GGarcia Bravo JBreidi F(2024) Investigating Safety Awareness in Assembly Operations via Mixed Reality Technology IISE Transactions on Occupational Ergonomics and Human Factors10.1080/24725838.2024.2431112(1-17)Online publication date: 4-Dec-2024
https://doi.org/10.1080/24725838.2024.2431112
Sakai YMatsumoto M(2023)Topic Selection Using Conceptual Distance: How to Select Topics that are Interesting but Unfamiliar to UsersIEEJ Journal of Industry Applications10.1541/ieejjia.2200678412:4(588-595)Online publication date: 1-Jul-2023
https://doi.org/10.1541/ieejjia.22006784
Raff E(2023)Does the Market of Citations Reward Reproducible Work?Proceedings of the 2023 ACM Conference on Reproducibility and Replicability10.1145/3589806.3600041(89-96)Online publication date: 27-Jun-2023
https://dl.acm.org/doi/10.1145/3589806.3600041
Koochemeshkian PBouguila N(2023)Advancing Multinomial Regression and Topic Modeling with Beta-Liouville Distributions2023 International Conference on Machine Learning and Applications (ICMLA)10.1109/ICMLA58977.2023.00292(1928-1935)Online publication date: 15-Dec-2023
https://doi.org/10.1109/ICMLA58977.2023.00292
Yang CHan J(2023)Revisiting Citation Prediction with Cluster-Aware Text-Enhanced Heterogeneous Graph Neural Networks2023 IEEE 39th International Conference on Data Engineering (ICDE)10.1109/ICDE55515.2023.00058(682-695)Online publication date: Apr-2023
https://doi.org/10.1109/ICDE55515.2023.00058
Koochemeshkian PBouguila N(2023)Generalized Dirichlet-Multinomial Regression: Leveraging Arbitrary Features for Topic Modelling2023 IEEE International Conference on High Performance Computing & Communications, Data Science & Systems, Smart City & Dependability in Sensor, Cloud & Big Data Systems & Application (HPCC/DSS/SmartCity/DependSys)10.1109/HPCC-DSS-SmartCity-DependSys60770.2023.00128(884-891)Online publication date: 17-Dec-2023
https://doi.org/10.1109/HPCC-DSS-SmartCity-DependSys60770.2023.00128
Yallamati SBuradagunta AAlmas SPachhala N(2023)New Data Representation and Simulate Over Social Media Using Bayes Classifier of Machine LearningEnergy Systems, Drives and Automations10.1007/978-981-99-3691-5_45(515-526)Online publication date: 21-Aug-2023
https://doi.org/10.1007/978-981-99-3691-5_45
Jiang XLiu J(2023)Extracting the evolutionary backbone of scientific domains: The semantic main path network analysis approach based on citation context analysisJournal of the Association for Information Science and Technology10.1002/asi.2474874:5(546-569)Online publication date: 21-Mar-2023
https://doi.org/10.1002/asi.24748
Jung SSegev AAlam MBuscaldi DCochez MOsborne FRefogiato Recupero DSack H(2022)Analyzing the generalizability of the network-based topic emergence identification methodSemantic Web10.3233/SW-21295113:3(423-439)Online publication date: 1-Jan-2022
https://dl.acm.org/doi/10.3233/SW-212951
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