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PatentSemTech 2023 : 4th Workshop on Patent Text Mining and Semantic Technologies

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Link: http://ifs.tuwien.ac.at/patentsemtech/
 
When Jul 27, 2023 - Jul 27, 2023
Where Taipei (Taiwan)
Submission Deadline Apr 25, 2023
Notification Due May 23, 2023
 

Call For Papers



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

================================================================================

The PatentSemTech2023 workshop aims to establish a long-term collaboration and a

two-way communication channel between the IP industry and academia from relevant

fields such as natural language processing (NLP), text and data mining (TDM), and

semantic technologies (ST) in order to explore and transfer new knowledge, methods,

and technologies for the benefit of industrial applications as well as support

research in applied sciences for the IP and neighbouring domains.



Call for Contributions

======================

PatentSemTech2023 will be held as a full-day event in conjunction with SIGIR 2023.

Workshop website: http://ifs.tuwien.ac.at/patentsemtech/



Important Dates

===============

Submission deadline: April 25, 2023

Notification: May 23, 2023

SIGIR PatentSemTech2023 workshop: July 27, 2023



Topics of Interest

==================

We encourage submissions of high quality research papers on all topics related

to the IP domain. Topics of interest include (but are not limited to):

• Text mining and retrieval from patents, legal documents, or other

scientific-technical information sources

• Machine learning methods, in particular deep learning methods for

– Representation learning (word and document embeddings)

– Query expansion

– Clustering and classification

– Recommendation

– IPC/CPC prediction

– Trend detection

– Entity extraction

• Semantic approaches for

– Linking semantic information

– Integrating external knowledge sources

– Semantic enrichment

• Methods and applications for retrieving, mining, and analysing, including

– Patent landscaping

– Hot spot / White spot analysis

– Multi-modal analysis

– Technology trend analysis

– Innovative user interfaces

– Visual user interface concepts



Contributions

=============

We solicit two types of submissions: full papers and short papers for three tracks: research, demo, and summarization task. Full papers will be limited to 8 pages (including references); short papers will be 4 pages (including references).



The submissions will be peer-reviewed by at least two program committee members and evaluated based on innovativeness, novelty, interestingness, and impact.

We plan for three tracks:



*Research Track*

For this track, we solicit contributions from academia that present

• Novel applications of existing state of the art methods for the IP domain

• Novel methods or tasks in the IP domain

• Novel user interfaces for the IP domain

• Novel evaluation or analysis insights in the IP domain

• Novel benchmark datasets or other resources of interest

• A survey or overview related to a particular task in the IP domain



*Demo/System Track*

We solicit demos, case study, insights, or novel ideas from industry that present

• Focused case studies making use of semantic technologies or machine learning

• Interesting IP-related task descriptions or best practices for patent analysis

• In-use systems or prototype implementations of semantic technologies

• Demos on processing or analysing data from the IP domain, or user interfaces

• In-use resources related to patents or external resources, e.g., linked open data.



*Summarization Task Track*

Within the patent text mining community, especially from the industry, there is an interest in developing text mining tools targeting text summarization.

• Participants are free to use publicly available data sets to train their models. We recommend exploring US Patents, which many contain the text section SUMMARY OF THE INVENTION.

• We will also publish a small training and test data set on the 23rd of February. The provided data set is composed of patents within the field of Green Plastics Technology.

• Participants are asked to submit a short (4 pages) scientific paper, which will be peer-reviewed by the workshop organizers. The most interesting submissions will be invited to present their solution at the workshop.

• Furthermore, we will have an additional interactive evaluation to reflect a more real-life scenario at the workshop, making it possible to evaluate not only the performance in terms of F1, ROUGE, recall, precision etc., but also efficiency. Therefore the invited participants will be asked to set-up their solutions as a service and provide a REST API. Input will be a patent document (PDF,DOCX), and output should be a summary of not more than 700 words.





Submission Guidelines

=====================

Submissions must be in English, in PDF, and in the current ACM two-column conference

format. Suitable LaTeX, Word, and Overleaf templates are available from the ACM Website:

https://www.acm.org/publications/proceedings-template ("sigconf" template for LaTeX;

Interim Template for Word). Submissions should be at most 8 (full) or 4 (short) pages (including figures and references) in length. Submissions should be submitted electronically via EasyChair:

https://www.easychair.org/conferences/?conf=patentsemtech2023.

At least one author of each accepted paper is required to register for,

and present the work in person at the workshop.



Publication

===========

Accepted papers will be published as CEUR proceedings. Selected contributions

will be invited to submit extended, full papers to Elsevier’s World Patent

Information (WPI) journal: https://www.journals.elsevier.com/world-patent-information/



Organizers

==========

Ralf Krestel (ZBW & CAU Kiel, Germany), Hidir Aras (FIZ Karlsruhe, Germany),

Linda Andersson (Artificial Researcher, Austria), Florina Piroi (Data Science Studio,

RSA FG, Austria), Allan Hanbury (TU Wien, Austria), Dean Alderucci (CMU, USA)



All questions about submissions should be emailed to:

r.krestel@zbw.eu and hidir.aras@fiz-karlsruhe.de


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