4th Workshop on Patent Text Mining and Semantic Technologies (PatentSemTech2023)

被引:0
|
作者
Krestel, Ralf [1 ,2 ]
Aras, Hidir [3 ]
Andersson, Linda [4 ]
Piroi, Florina [5 ,6 ]
Hanbury, Allan [5 ]
Alderucci, Dean [7 ]
机构
[1] ZBW Leibniz Informat Ctr Econ, Kiel, Germany
[2] Univ Kiel, Kiel, Germany
[3] FIZ Karlsruhe Leibniz Inst Informat Infrastruct, Eggenstein Leopoldshafen, Germany
[4] Artificial Researcher IT GmbH, Vienna, Austria
[5] TU Wien, Vienna, Austria
[6] Res Studios Austria, Vienna, Austria
[7] Carnegie Mellon Univ, Ctr AI & Patent Anal, Pittsburgh, PA USA
来源
PROCEEDINGS OF THE 46TH INTERNATIONAL ACM SIGIR CONFERENCE ON RESEARCH AND DEVELOPMENT IN INFORMATION RETRIEVAL, SIGIR 2023 | 2023年
关键词
patent analysis; text mining; semantic technology; deep learning;
D O I
10.1145/3539618.3591929
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Information retrieval systems for the patent domain have a long history. They can support patent experts in a variety of daily tasks: from analyzing the patent landscape to support experts in the patenting process and large-scale information extraction. Advances in machine learning and natural language processing allow to further automate tasks, such as paragraph retrieval or even patent text generation. Uncovering the potential of semantic technologies for the intellectual property (IP) industry is just getting started. Investigating the use of artificial intelligence methods for the patent domain is therefore not only of academic interest, but also highly relevant for practitioners. Compared to other domains, high quality, semi-structured, annotated data is available in large volumes (a requirement for supervised machine learning models), making training large models easier. On the other hand, domain-specific challenges arise, such as very technical language or legal requirements for patent documents. The focus of the 4th edition of this workshop will be on two-way communication between industry and academia from all areas of information retrieval in particular with the Asian community. We want to bring together novel research results and the latest systems and methods employed by practitioners in the field.
引用
收藏
页码:3483 / 3486
页数:4
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