=Paper=
{{Paper
|id=Vol-3775/preface
|storemode=property
|title=None
|pdfUrl=https://ceur-ws.org/Vol-3775/preface.pdf
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==None==
https://ceur-ws.org/Vol-3775/preface.pdf
5th Workshop on Patent Text Mining
and Semantic Technologies (PatentSemTech)
collocated with the 47th International ACM SIGIR Conference on Research and
Development in Information Retrieval
Ralf Krestel1 , Hidir Aras2 , Linda Andersson3 , Florina Piroi4 , Allan Hanbury5 and
Dean Alderucci6
1
ZBW – Leibniz Information Centre for Economics & Kiel University, Düsternbrooker Weg 120, 24105, Kiel, Germany
2
FIZ Karlsruhe - Leibniz Institute for Information Infrastructure, Hermann-von-Helmholtz-Platz 1, 76344
Eggenstein-Leopoldshafen, Germany
3
Artificial Researcher IT GmbH, Taubstummengasse 11 (i2c), 1040, Wien Austria
4
RSA FG Studio Data Science, Thurngasse 8/16, 1090, Vienna Austria
5
Institute of Information Systems Engineering, TU Wien, Favoritenstr. 9-11/194-04, Vienna, Austria
6
Center for AI and Patent Analysis, Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, PA 15213, USA
5th Workshop on Patent Text Mining and Semantic Technologies (PatentSemTech) 2024
$ rkr@informatik.uni-kiel.de (R. Krestel)
0000-0002-5036-8589 (R. Krestel)
© 2024 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
i
CEUR
ceur-ws.org
Workshop ISSN 1613-0073
Proceedings
Ralf Krestel et al. CEUR Workshop Proceedings i–iii
Preface
The fifth edition (PatentSemTech2024) of the workshop series Patent Text Mining and Semantic
Technologies was held as a full-day event in conjunction with the SIGIR 2024 conference. As
in the previous editions, the workshop focused on new developments and research in patent
retrieval and patent analytics. An important focus of the workshop was to address the adaptation
of existing deep learning models, e.g. large language models, for the patent domain, covering
diverse scientific subject areas, such as chemistry, pharmacology, etc. In general, patent data
is more difficult to analyse compared to corpora comprising other text genres. Working with
patent data, besides its challenging aspects, does bring a richness of facets to be exploited
with text mining and semantic analysis methods as well: (1) It constitutes a huge corpus of
scientific-technical documents for a variety of technological domains. (2) They are rich in
available meta-data such as spatial data, bibliographic data, classifications, temporal data, etc.
(3) Patents describe essential scientific-technical knowledge enclosing solutions for real-world
applications. (4) They are complementary knowledge to scientific literature, e.g. chemical and
physical properties, bio-science knowledge for drug-target-interaction, which appears first in
patents, mostly not published elsewhere. With the PatentSemTech2024 workshop we continued
our series of workshops launched in 2019, aiming to establish a long-term collaboration and a
two-way communication channel between the IP industry and academia from relevant fields.
Therefore, the 5th PatentSemTech workshop was organized as a full-day event with 10 research
paper presentations that were accepted after peer-review out of 17 submissions. 6 long papers
were presented as oral presentations while 4 short papers were presented as posters. In addition,
Matthew Wahlrab, CEO of RapidAlpha, gave a keynote speech on "Unlocking Strategic Growth:
The Role of AI Technology in Intellectual Property". In an open discussion on "How to transform
research insights into products?", the workshop participants exchanged ideas and reported their
experience with applying AI in the patent domain. The workshop closed with Linda Andersson
looking back at 5 successful PatentSemTech workshops and how the field has developed over
these years.
Germany, Austria, USA, July 2024 Ralf Krestel,
Hidir Aras,
Linda Andersson,
Florina Piroi,
Allan Hanbury,
Dean Alderucci
ii
Ralf Krestel et al. CEUR Workshop Proceedings i–iii
Organizers
• Ralf Krestel (ZBW - Leibniz Information Centre for Economics & Kiel University, Germany)
• Hidir Aras (FIZ Karlsruhe, Germany)
• Linda Andersson (Artificial Researcher IT GmbH, Vienna, Austria)
• Florina Piroi (TU Wien & Data Science Studio, Vienna, Austria)
• Allan Hanbury (TU Wien, Austria)
• Dean Alderucci (Carnegie Mellon University, Pittsburgh, USA)
Program Committee
• Alexander Klenner-Bajaja (European Patent Office, Netherlands)
• Anthony Trippe (Patinformatics, Ireland)
• Christoph Hewel (Paustian & Partner, Germany)
• Eric Müller-Budack (TIB Hannover, Germany)
• Florina Piroi (TU Wien, Austria)
• Hans-Peter Zorn (inovex Gmbh, Karlsruhe, Germany)
• Hidir Aras (FIZ Karlsruhe, Germany)
• Karin Verspoor (RMIT University, Melbourne, Australia)
• Lei Zhang (FIZ Karlsruhe, Germany)
• Linda Andersson (Artificial Researcher IT GmbH, Vienna, Austria)
• Michail Salampasis (International Hellenic University, Thessaloniki, Greece)
• Ralf Krestel (ZBW Kiel, Germany)
• Rene Hackl-Sommer (DeepL SE, Germany)
• Simone Ponzetto (University of Mannheim, Germany)
• Tobias Fink (TU Wien, Austria)
Website
Further information on the topics, schedule, and further developments of the PatentSemTech
workshop can be found on the website: http://ifs.tuwien.ac.at/patentsemtech/
iii