Simple and Effective Way to Disambiguate and Standardize Patent Applicants Using an Attention Mechanism With Data Augmentation
Innovation in artificial intelligence and data science has sparked evolutions across numerous industries. Some companies are focusing on developing novel technologies to seize a rapidly evolving market, while others are exploring new business models to keep pace. The former and latter are typically...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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IEEE
2023-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10230244/ |
| _version_ | 1797692157430071296 |
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| author | Juhyun Lee Sangsung Park Junseok Lee |
| author_facet | Juhyun Lee Sangsung Park Junseok Lee |
| author_sort | Juhyun Lee |
| collection | DOAJ |
| description | Innovation in artificial intelligence and data science has sparked evolutions across numerous industries. Some companies are focusing on developing novel technologies to seize a rapidly evolving market, while others are exploring new business models to keep pace. The former and latter are typically referred to as first movers and fast followers in the technology market and identifying them can offer insights into technology market trends. Patent analysis is a good approach to exploring first movers and fast followers. However, patent applicants are classified into different patterns based on the structure or type of a company, making it challenging to disambiguate and standardize patent applicants. Therefore, this study proposes a method to disambiguate and standardize patent applicants. We present a simple and effective data augmentation approach that can help understand patent applicant patterns. The proposed approach trains on the augmented data via the attention mechanism. Our experiments provide empirical evidence for the performance of the proposed method, which accurately classifies 96.6% of the augmented data. Moreover, statistical hypothesis testing validates that the output of the proposed method is consistent with the ground truth. |
| first_indexed | 2024-03-12T02:24:32Z |
| format | Article |
| id | doaj.art-e4913b296f1e45ddbc46d1d58239f64c |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-03-12T02:24:32Z |
| publishDate | 2023-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-e4913b296f1e45ddbc46d1d58239f64c2023-09-05T23:01:48ZengIEEEIEEE Access2169-35362023-01-0111927059271410.1109/ACCESS.2023.330858810230244Simple and Effective Way to Disambiguate and Standardize Patent Applicants Using an Attention Mechanism With Data AugmentationJuhyun Lee0https://orcid.org/0000-0003-3337-1134Sangsung Park1https://orcid.org/0000-0001-6804-2707Junseok Lee2https://orcid.org/0000-0003-0491-9690Institute of Engineering Research, Korea University, Seoul, Republic of KoreaDepartment of Data Science, Cheongju University, Cheongju-si, Republic of KoreaCollege of AI Convergence Engineering, Kangnam University, Youngin-si, Republic of KoreaInnovation in artificial intelligence and data science has sparked evolutions across numerous industries. Some companies are focusing on developing novel technologies to seize a rapidly evolving market, while others are exploring new business models to keep pace. The former and latter are typically referred to as first movers and fast followers in the technology market and identifying them can offer insights into technology market trends. Patent analysis is a good approach to exploring first movers and fast followers. However, patent applicants are classified into different patterns based on the structure or type of a company, making it challenging to disambiguate and standardize patent applicants. Therefore, this study proposes a method to disambiguate and standardize patent applicants. We present a simple and effective data augmentation approach that can help understand patent applicant patterns. The proposed approach trains on the augmented data via the attention mechanism. Our experiments provide empirical evidence for the performance of the proposed method, which accurately classifies 96.6% of the augmented data. Moreover, statistical hypothesis testing validates that the output of the proposed method is consistent with the ground truth.https://ieeexplore.ieee.org/document/10230244/Attention mechanismdata augmentationnamed entity recognitionpatent applicants |
| spellingShingle | Juhyun Lee Sangsung Park Junseok Lee Simple and Effective Way to Disambiguate and Standardize Patent Applicants Using an Attention Mechanism With Data Augmentation IEEE Access Attention mechanism data augmentation named entity recognition patent applicants |
| title | Simple and Effective Way to Disambiguate and Standardize Patent Applicants Using an Attention Mechanism With Data Augmentation |
| title_full | Simple and Effective Way to Disambiguate and Standardize Patent Applicants Using an Attention Mechanism With Data Augmentation |
| title_fullStr | Simple and Effective Way to Disambiguate and Standardize Patent Applicants Using an Attention Mechanism With Data Augmentation |
| title_full_unstemmed | Simple and Effective Way to Disambiguate and Standardize Patent Applicants Using an Attention Mechanism With Data Augmentation |
| title_short | Simple and Effective Way to Disambiguate and Standardize Patent Applicants Using an Attention Mechanism With Data Augmentation |
| title_sort | simple and effective way to disambiguate and standardize patent applicants using an attention mechanism with data augmentation |
| topic | Attention mechanism data augmentation named entity recognition patent applicants |
| url | https://ieeexplore.ieee.org/document/10230244/ |
| work_keys_str_mv | AT juhyunlee simpleandeffectivewaytodisambiguateandstandardizepatentapplicantsusinganattentionmechanismwithdataaugmentation AT sangsungpark simpleandeffectivewaytodisambiguateandstandardizepatentapplicantsusinganattentionmechanismwithdataaugmentation AT junseoklee simpleandeffectivewaytodisambiguateandstandardizepatentapplicantsusinganattentionmechanismwithdataaugmentation |