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The International Society for Patent Information Professionals

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Webinar 3: Generating Spatial Concept Maps

  • 21 Mar 2019
  • 11:00 AM - 12:00 PM
  • Webinar
  • 93


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Preparing Patent Analytics Projects and Patent Landscape Reports- Hands-On Lessons

PIUG presents an opportunity to learn valuable practical skills from Tony Trippe, a leading expert with many years of experience in Patinformatics. Join us for a series of webinars providing details on some of the stages required for performing patent analytics, and for the preparation of a Patent Landscape Report (PLR).

Patent analytics and PLRs support informed decision-making and are designed to efficiently address the concerns associated with making high stakes decisions in technologically advanced areas with a maximum degree of confidence. For many years’ decision-makers operated based on personal networks and intuition. With the institution of patent analytics, and PLRs, it is possible for these critical decisions to be made with data-driven approaches that deliver informed choices, and lower risk profiles. Working with patent data can be complicated due to the nature of the subject matter, and the lack of standard in the way it is delivered from the offices that generate it.

This four part series of webinars provides specific steps for the production of patent analysis projects and PLRs including step-by-step instructions for performing these operations:

  • 3.       Generating Spatial Concept Maps
    • One of the most misunderstood, but potentially most visually impactful analysis is spatial concept mapping. Senior management, and decision makers are especially interested in this type of visualization and the use of one can help an analyst quickly compare the coverage between two organizations in an area of interest. Spatial concept mapping is related to clustering, or classification, since it generally begins with one of these methods, but adds an extra component, identification of relative similarity between the categories created, to one another. The tools involved take the document clusters, or classes, and arrange them in 2-dimensional space by considering the similarity of the documents, or clusters, relative to one another, over the entire collection. Documents that share elements in common are placed closer together spatially, while ones with less similarity, are placed further away. In this webinar two different tools will be used to demonstrate methods for making maps that support the conclusions an analyst is working to demonstrate to their clients.

Time listed is in US Eastern Time Zone

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