research-article

Automatic creation of a technical trend map from research papers and patents

Authors:

Hidetsugu Nanba,

Tomoki Kondo,

Toshiyuki TakezawaAuthors Info & Claims

PaIR '10: Proceedings of the 3rd international workshop on Patent information retrieval

Pages 11 - 16

https://doi.org/10.1145/1871888.1871891

Published: 26 October 2010 Publication History

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Abstract

For a researcher in a field of great industrial relevance, retrieving and analyzing research papers and patents has become an important aspect of assessing the scope of the field. We propose a method for creating a technical trend map automatically from both research papers and patents. For the construction of the technical trend map, we focus on the elemental (underlying) technologies used in a particular field, and their effects. Knowledge of the history and effects of the elemental technologies used in a particular field is essential for grasping the outline of technical trends in the field. Therefore, we have constructed a method that can recognize the application of elemental technologies and their effects in any research field. To investigate the effectiveness of our method, we conducted an experiment using the data in the NTCIR-8 Patent Mining Task. From our experimental results, we obtained Recall and Precision scores of 0.160 and 0.491, respectively, for the analysis of research papers. We also obtained Recall and Precision scores of 0.431 and 0.545, respectively, for the analysis of patents. Finally, we have constructed a system that creates an effective technical trend map for a given field.

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Automatic creation of a technical trend map from research papers and patents

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Published In

PaIR '10: Proceedings of the 3rd international workshop on Patent information retrieval

October 2010

76 pages

ISBN:9781450303842

DOI:10.1145/1871888

General Chair:
John Tait
Information Retrieval Facility, AT
,
Program Chairs:
Christopher Harris
The University of Iowa, USA
,
Mihai Lupu
Information Retrieval Facility, AT

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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Association for Computing Machinery

New York, NY, United States

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Published: 26 October 2010

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CIKM '10

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CIKM '10: International Conference on Information and Knowledge Management

October 26, 2010

ON, Toronto, Canada

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Overall Acceptance Rate 7 of 13 submissions, 54%

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The 34th ACM International Conference on Information and Knowledge Management

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Jiang YMeng RHuang YLu WLiu J(2023)Generating keyphrases for readersJournal of the Association for Information Science and Technology10.1002/asi.2474974:7(759-774)Online publication date: 30-Mar-2023
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Wang SMao JCao YLi G(2022)Integrated knowledge content in an interdisciplinary field: identification, classification, and applicationScientometrics10.1007/s11192-022-04282-0127:11(6581-6614)Online publication date: 14-Feb-2022
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Yanagihori KTsuda K(2015)Verification of Patent Document Similarity of Using Dictionary Data Extracted from Notification of Reasons for RefusalProceedings of the 2015 IEEE 39th Annual Computer Software and Applications Conference - Volume 0310.1109/COMPSAC.2015.162(349-354)Online publication date: 1-Jul-2015
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Technical trend analysis by analyzing research papers' titles

Technical Invention Trend Analysis of Applicants Based on CPC Classification

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