Call for Papers

The PatentSemTech 2021 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.

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 mining and analysing, including
    • Patent landscaping
    • Hotspot analysis
    • Technology trend analysis
    • Innovative user interaction
    • Visual user interface concepts

Important Dates:

  • Submission deadline: AoE, May 9th, May 16th 2021 (Extended)
  • Acceptance notification: June 1st, 2021
  • Camera ready submission: June 15th, 2021
  • Workshop day: July 15th, 2021


We welcome two types of contributions: full papers to present original research and short papers to report on case studies, system demonstrations, and resources.

Full Research Paper (max 9 pages) Case Study, Demo, or Resource Paper (max 4 pages)
Main Topics. We welcome any kind of original research related to patents including, but not limited to, descriptions of novel applications, novel tasks, novel user interfaces, novel evaluation methods, novel benchmark datasets, novel analysis insights, as well as survey and overview papers related to the IP domain. Case Study Paper. We are interested in short descriptions of focused case studies making use of semantic technologies or machine learning, interesting IP-related task descriptions and best practices for patent analysis.

Demo Paper. We welcome short descriptions of in-use systems or prototype implementation of semantic technologies or deep learning approaches that can be presented and demonstrated. The focus of the demo can be on processing or analysing data from the IP domain, or focused on user experience or interfaces.

Resource Papers that describe novel resources related to patents or related legal documents. Further, they can describe external resources to augment IP datasets, e.g., linked open data.

Submission Guidelines

The papers need to be original and not submitted or accepted for publication in any other workshop,conference,or journal. 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: ("sigconf" template for LaTeX; Interim Template for Word)

Submissions of full research papers must be at most 9 pages (including figures) in length + unrestricted space for references. Submissions of demonstration, case study, and resource papers must be at most 4 pages (including figures) in length + unrestricted space for references. Submissions must be anonymous and should be submitted electronically via EasyChair:

At least one author of each accepted paper is required to register for, and present the work at the workshop.


Workshop post-proceedings will be published as Open Access on TU Wien’s reposiTUm infrastructure. Selected papers will be invited to submit their paper to Elsevier’s World Patent Information (WPI) journal for inclusion in the virtual special issue on “Patent Text Mining and Semantic Technologies”.


  • Ralf Krestel (HPI Potsdam, 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 and