Article

Automatic patent classification using citation network information: an experimental study in nanotechnology

Authors:

Jiexun LiAuthors Info & Claims

JCDL '07: Proceedings of the 7th ACM/IEEE-CS joint conference on Digital libraries

Pages 419 - 427

https://doi.org/10.1145/1255175.1255262

Published: 18 June 2007 Publication History

Abstract

Classifying and organizing documents in repositories is an active research topic in digital library studies. Manually classifying the large volume of patents and patent applications managed by patent offices is a labor-intensive task. Many previous studies have employed patent contents for patent classification with the aim of automating this process. In this research we propose to use patent citation information, especially the citation network structure information, to address the patent classification problem. We adopt a kernel-based approach and design kernel functions to capture content information and various citation-related information in patents. These kernels. performances are evaluated on a testbed of patents related to nanotechnology. Evaluation results show that our proposed labeled citation graph kernel, which utilized citation network structures, significantly outperforms the kernels that use no citation information or only direct citation information.

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Cited By

Zou TYu LYe JSun LDu BWang D(2024)Adaptive Taxonomy Learning and Historical Patterns Modeling for Patent ClassificationACM Transactions on Information Systems10.1145/367483442:6(1-24)Online publication date: 18-Oct-2024
https://dl.acm.org/doi/10.1145/3674834
Jang YWon KChoi HShin S(2023)Classification of Research Papers on Radio Frequency Electromagnetic Field (RF-EMF) Using Graph Neural Networks (GNN)Applied Sciences10.3390/app1307461413:7(4614)Online publication date: 5-Apr-2023
https://doi.org/10.3390/app13074614
Hachisuka SNakada YNanba HFukuda S(2023)Japanese Patent Classification Using Few-shot Learning2023 14th IIAI International Congress on Advanced Applied Informatics (IIAI-AAI)10.1109/IIAI-AAI59060.2023.00032(118-121)Online publication date: 8-Jul-2023
https://doi.org/10.1109/IIAI-AAI59060.2023.00032
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Index Terms

Automatic patent classification using citation network information: an experimental study in nanotechnology
1. Information systems
  1. Information retrieval
    1. Document representation

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Published In

cover image ACM Conferences

JCDL '07: Proceedings of the 7th ACM/IEEE-CS joint conference on Digital libraries

June 2007

534 pages

ISBN:9781595936448

DOI:10.1145/1255175

General Chair:
Edie Rasmussen
University of British Columbia, Canada
,
Program Chairs:
Ray R. Larson
University of California, Berkeley
,
Elaine Toms
Dalhousie University, Canada
,
Shigeo Sugimoto
University of Tsukuba, Japan

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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Published: 18 June 2007

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JCDL07: Joint Conference on Digital Libraries

June 18 - 23, 2007

BC, Vancouver, Canada

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Overall Acceptance Rate 415 of 1,482 submissions, 28%

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Cited By

Zou TYu LYe JSun LDu BWang D(2024)Adaptive Taxonomy Learning and Historical Patterns Modeling for Patent ClassificationACM Transactions on Information Systems10.1145/367483442:6(1-24)Online publication date: 18-Oct-2024
https://dl.acm.org/doi/10.1145/3674834
Jang YWon KChoi HShin S(2023)Classification of Research Papers on Radio Frequency Electromagnetic Field (RF-EMF) Using Graph Neural Networks (GNN)Applied Sciences10.3390/app1307461413:7(4614)Online publication date: 5-Apr-2023
https://doi.org/10.3390/app13074614
Hachisuka SNakada YNanba HFukuda S(2023)Japanese Patent Classification Using Few-shot Learning2023 14th IIAI International Congress on Advanced Applied Informatics (IIAI-AAI)10.1109/IIAI-AAI59060.2023.00032(118-121)Online publication date: 8-Jul-2023
https://doi.org/10.1109/IIAI-AAI59060.2023.00032
Cassidy C(2020)Parameter tuning Naïve Bayes for automatic patent classificationWorld Patent Information10.1016/j.wpi.2020.10196861(101968)Online publication date: Jun-2020
https://doi.org/10.1016/j.wpi.2020.101968
Abood AFeltenberger D(2018)Automated patent landscapingArtificial Intelligence and Law10.1007/s10506-018-9222-426:2(103-125)Online publication date: 1-Jun-2018
https://dl.acm.org/doi/10.1007/s10506-018-9222-4
Diallo BLupu M(2017)Future Patent SearchCurrent Challenges in Patent Information Retrieval10.1007/978-3-662-53817-3_17(433-455)Online publication date: 26-Mar-2017
https://doi.org/10.1007/978-3-662-53817-3_17
Tran TKavuluru R(2017)Supervised Approaches to Assign Cooperative Patent Classification (CPC) Codes to PatentsMining Intelligence and Knowledge Exploration10.1007/978-3-319-71928-3_3(22-34)Online publication date: 28-Nov-2017
https://doi.org/10.1007/978-3-319-71928-3_3
Nugroho BAritsugi M(2017)Application of k-Step Random Walk Paths to Graph Kernel for Automatic Patent ClassificationDigital Libraries: Data, Information, and Knowledge for Digital Lives10.1007/978-3-319-70232-2_2(14-29)Online publication date: 3-Nov-2017
https://doi.org/10.1007/978-3-319-70232-2_2
Kardes HSevincer AGunes MYuksel M(2014)Complex Network Analysis of Research Funding: A Case Study of NSF GrantsState of the Art Applications of Social Network Analysis10.1007/978-3-319-05912-9_8(163-187)Online publication date: 15-May-2014
https://doi.org/10.1007/978-3-319-05912-9_8
Barirani AAgard BBeaudry C(2013)Discovering and assessing fields of expertise in nanomedicineScientometrics10.1007/s11192-012-0891-694:3(1111-1136)Online publication date: 1-Mar-2013
https://dl.acm.org/doi/10.1007/s11192-012-0891-6
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