Foundations and Trends® in Information Retrieval > Vol 7 > Issue 1

Patent Retrieval

By Mihai Lupu, Vienna University of Technology, Austria, lupu@ifs.tuwien.ac.at | Allan Hanbury, Vienna University of Technology, Austria, hanbury@ifs.tuwien.ac.at

 
Suggested Citation
Mihai Lupu and Allan Hanbury (2013), "Patent Retrieval", Foundations and Trends® in Information Retrieval: Vol. 7: No. 1, pp 1-97. http://dx.doi.org/10.1561/1500000027

Publication Date: 20 Feb 2013
© 2013 M. Lupu and A. Hanbury
 
Subjects
Search,  E-Government,  Databases on the Web,  Information retrieval,  Classification and prediction,  User modelling and user studies for IR,  Usability, interactivity, and visualization issues in IR,  Text mining,  Performance issues for IR systems,  Natural language processing for IR,  Metasearch, rank aggregation and data fusion,  Information extraction,  Information categorization and clustering,  Indexing and retrieval of structured documents,  Evaluation issues and test collections for IR,  Distributed IR and federated search,  Cross-lingual and multilingual IR,  Applications of IR,  Specific user groups (children, elders, etc.),  Multimodal interaction,  Information visualization,  Design and Evaluation,  XML and Semi-Structured Data,  Storage, Access Methods, and Indexing,  Metadata Management,  Information theory and computer science,  Image and Video Retrieval
 
Keywords
Rd, Databases/Information RetrievalRa, Machine Learning
 

Free Preview:

Download extract

Share

Download article
In this article:
1 Introduction 
2 Evaluation 
3 Text Retrieval 
4 Metadata 
5 Beyond Text 
6 Conclusions 
Acknowledgments 
Notations and Acronyms 
References 

Abstract

Intellectual property and the patent system in particular have been extremely present in research and discussion, even in the public media, in the last few years. Without going into any controversial issues regarding the patent system, we approach a very real and growing problem: searching for innovation. The target collection for this task does not consist of patent documents only, but it is in these documents that the main difference is found compared to web or news information retrieval. In addition, the issue of patent search implies a particular user model and search process model. This review is concerned with how research and technology in the field of Information Retrieval assists or even changes the processes of patent search. It is a survey of work done on patent data in relation to Information Retrieval in the last 20–25 years. It explains the sources of difficulty and the existing document processing and retrieval methods of the domain, and provides a motivation for further research in the area.

DOI:10.1561/1500000027
ISBN: 978-1-60198-648-1
109 pp. $75.00
Buy book (pb)
 
ISBN: 978-1-60198-649-8
109 pp. $115.00
Buy E-book (.pdf)
Table of contents:
1: Introduction
2: Evaluation
3: Text Retrieval
4: Metadata
5: Beyond Text
Conclusions
Acknowledgements
Notations and Acronyms
References

Patent Retrieval

Intellectual property and the patent system in particular have garnered a lot of attention, even in the public media, over the last few years. This monograph is not concerned with any of the controversial issues regarding the patent system itself but it does examine a very real and growing problem: searching for innovation. The target collection for this task does not consist of patent documents only, but it is in these documents that the main difference is found compared to web or news information retrieval. In addition, the issue of patent search implies a particular user model and search process model. Patent Retrieval addresses the question of how research and technology in the field of Information Retrieval assists or even changes the processes of patent search. It is a survey of work done on patent data in relation to Information Retrieval in the last 20 to 25 years. It explains the sources of difficulty and the existing document processing and retrieval methods of the domain, and provides a motivation for further research in the area. Patent Retrieval is an ideal reference for Information Retrieval researchers interested in the patent domain and for patent information professionals.

 
INR-027