Preface: First International Workshop on Patent Mining and Its Applications (IPaMin 2014)

Abstract

1. MOTIVATION The importance of exploiting knowledge in patents is constantly increasing. A large percentage of the most recent technical knowledge is only available in patent documents. Patent mining and the automatic analysis of large numbers of patents are necessary to identify trends in research and development. Applications include the identification of potential areas of investment, avoiding duplicating efforts, competitor analysis, and patent landscape mapping. Advanced methods in information technology bear much potential for improving access to patents and to gain knowledge form patents. This workshop wants to identify current innovative research in patent mining and build a map of research and needs. Another topic will be the discussion about evaluation approaches to patent mining. Several important initiatives have dealt with information retrieval from patents (NTCIR, CLEF-IP, TREC Chem). However, there are few benchmarks for evaluating applications with vaguely defined goals as involved in patent mining.

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Some of the basic assumptions for information retrieval and text mining need to be revisited for patent mining. Due to the nature of patent documents, innovative approaches need to be taken for automatic analysis of patents and in general for big data analytics of scientific content.

Copyright © 2014 for the individual papers by the papers' authors. Copying permitted for private and academic purposes.

This volume is published and copyrighted by its editors.

Published at CEUR-WS.org Information extraction from patents

Modeling of patent documents

Temporal modelling based on patents

Trend mining

Prescriptive Analytics

Approaches to deal with patent terminology Visualization to support human mining tasks User interfaces for patent mining Issues on developing benchmarks for patent mining Lifecycle models of technology applied to mining approaches Advanced Information Retrieval Approaches using Patent Analytics Large scale big data analytics on scientific texts which could be applied to patents Innovative products for patent mining

Complex Event Processing Data management for patent mining Applications based on data mining and analytics

3. ORGANISATION The International Workshop on Patent Mining was a Satellite Event of KONVENS, the Conference on Natural Language Processing ("Konferenz zur Verarbeitung Natürlicher Sprache"). KONVENS seeks to offer a broad perspective on current research and developments within the interdisciplinary field of natural language processing. It provides a forum for researchers from all disciplines relevant to this field of research to present their work: http://www.uni-hildesheim.de/konvens2014 The next IPAMIn workshop will take place in Asia in 2015. Further events are planned. 4. ACKNOWLEDGEMENTS We greatly acknowledge the efforts of the members of the programme committee, namely:      

Norbert Fuhr, Germany

University of Duisburg-Essen, Yongping Du, Beijing University of Technology, China

Sung Pil Choi, Department of Library and Information Science, Kyonggi University, Korea In-Su Kang, Kyungsung University, Busan, Korea Jie Gui, Institute of Scientific and Information of China (ISTIC), Beijing, China Technical Rene Hackl-Sommer, FIZ Karlsruhe – Leibniz Institute for Information Infrastructure, Germany             

Myunggwon Hwang, Korea Insititute of Science and Technology Information (KISTI), Daejon, Korea Taehong Kim, Korea Insititute of Science and Technology Information (KISTI), Daejon, Korea

Steffen Koch, University of Stuttgart, Germany Johannes Leveling, CNGL, Dublin City University (DCU), Ireland

Yiao Liu, Institute of Scientific and Technical Information of China (ISTIC), China

Steffen Lohmann, University of Stuttgart, Germany Florina Piroi, Vienna University of Technology, ISIS, IFS, Austria

Shunji Shimizu, Department of Electrical Systems, Tokyo University of Science, Japan Sa-kwang Song, Korean Institute of Science and Technology Information (KISTI), Daejon, Korea Michael Schwantner, FIZ Karlsruhe – Leibniz Institute for Information Infrastructure, Germany Seungwoo Lee, Korean Institute of Science and Technology Information (KISTI), Daejon, Korea Yunliang Zhang, Institute of Scientific and Technical Information of China (ISTIC), Beijing, China Junsheng Zhang, Institute of Scientific and Technical Information of China (ISTIC), Beijing, China Lijun Zhu, Institute of Scientific and Technical Information of China (ISTIC), Beijing, China

References