The text, the full text and nothing but the text: Part 1 – Standards for creating textual information in patent documents and general search implications ☆

@article{Adams2010TheTT,
  title={The text, the full text and nothing but the text: Part 1 – Standards for creating textual information in patent documents and general search implications ☆},
  author={Stephen R. Adams},
  journal={World Patent Information},
  year={2010},
  volume={32},
  pages={22-29}
}
  • S. Adams
  • Published 1 March 2010
  • Computer Science
  • World Patent Information
Patent Retrieval
TLDR
This survey of work done on patent data in relation to Information Retrieval in the last 20–25 years is a survey of 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.
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The findings from a survey of patent users conducted to ascertain information about patent users and their requirements with respect to Information Retrieval applications are outlined.
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TLDR
The findings from a survey of patent users conducted to ascertain information about patent users and their search requirements with respect to Information Retrieval systems and applications are reported.
Automatic Extraction and Resolution of Bibliographical References in Patent Documents
TLDR
Conditional Random Fields models surpass significantly existing rule-based algorithms and other machine learning techniques, resulting more particularly in a very high performance for patent reference extractions with a reduction of approx.
Exploring Contextual Models in Chemical Patent Search
TLDR
The top performing retrieval model integrating contextual evidence from multiple levels of patent structure resulted in bpref measurements of 0.8929 for the prior art search task, exceeding the top results reported from the 2009 TREC Chemistry track.
Introduction to Patent Searching
This chapter introduces patent searching in a way that should be accessible and useful to both researchers in information retrieval and other areas of computer science and professionals seeking to
The Missing 15 Percent of Patent Citations
TLDR
It is shown that "in-text" citations bring a different type of information compared to front-page citations, which exhibit higher text-similarity to the citing patents and alter the ranking of patent importance.
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Handbook of special librarianship and information work , Handbook of special librarianship and information work , مرکز فناوری اطلاعات و اطلاع رسانی کشاورزی
Free or controlled vocabularies
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