Patents are extremely important in developing business strategy of technological companies. Data Mining and visualization is a powerful technique for analyzing and showing technology landscapes of vast patent data. Such a technique manipulates patent data in order to aid business and research & development decisions and to protect intellectual property rights1.

Importance of Patent Data

Innovation and technology are the two pillars contributing to the growth of a society. Patents are filed by a range of parties from individuals to small organizations and research institutions. Patent data are available to the public through various Government databases and commercial databases that allows for a searchable database of in both English and non-English patent applications.

The major importance of patents are they can provide legally important information on various aspects of a patent namely the Inventor’s details, Assignee’s details, type of technology, date of invention, Priority details, Family details, Geographical distribution of a patent and so on. This information are of tremendous value to the owners of patents, their competitors and for the stakeholders interested to invest either financially or intellectually in key technological areas.

Patent Networks as a key for identifying the niche patents

Patent Networks is one of the different data mining and visualization techniques available to search download and analyze patents data. A patent network signifies the relationships between inventors and companies in the form of an interconnected network. In developing a patent network, patent citation data are utilized. A network of patents signifies that the patents in the centre of the network have more influence and hence are important than the patents which are at the edge of the said network. A sample patent network developed using patent citation data, on different treatments available to treat Alzheimer’s disease reveals the relationships between the patents and the patent applications in the technology. Other information obtained from the network are relative importance of different patents, leading researchers, companies and their contribution in the various therapeutic sectors.

Logics behind adopting ‘citations’ strategy

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Patent applications and granted patents contain information of patent citations. ‘Citations’ are documents that are linked together wherein one documents mentions another document as having related content2. A ‘reverse’ or ‘backward’ citation is the one which in which previously or earlier published patents are referenced in a subject patent. A ‘forward citation’ is the one in which the subject patent will be referenced by the subsequently published patents.

Examples If Patent A (2010) is cited by Patent B (2013)


Patent A is a backward citation of Patent B

Patent B is a forward citation of Patent A

To make an individual assessment of large number of patents is cumbersome and highly error prone task. Therefore, a better solution is to rely on other people’s views of patents. Forward citation serves as an excellent key in obtaining other people’s views of a given patent. The citation system works in way that if a patent applicant or patent examiner has cited an earlier patent, it reflects the importance/relevance of that particular patent. For the aforesaid reason, either the number of

forward citations is used an indicator of patent quality, or when combined with other data such as the number of family members, the number of reverse citations, the numbers of authors and other patent data yield quality results.

Limitations of the citation strategy

  • Forward citation yields a simple number count which is not sufficient in analyzing the quality of the patent from which a forward citation has come.
  • Since the end result from a forward citation is merely a simple number, this number does not reflect any information on how different patents relate to each other.

Advantages of using citation strategy for developing a Patent Network Model:

  • The relationships among patents can be viewed as a visual network and therefore aids the analyst in intuitively understanding the overall technology.
  • Patent network analysis takes diverse keywords into account and produces more meaningful indicators. Network analysis employs a number of parameters hence an exhaustive search is performed and quality results are obtained.
  • Patent Network Analysis is more economical in terms of time and cost, mainly because original random set of documents are transformed into structured data through data mining and visualization technique.
  • The network established by patent citations allows one to trace the flow of technology through time, from patent to patent, and across fields.
  • Patent citation strategy used in patent network analysis aids in analyzing technological spillover effects, the impact or influence of individual patents, the rates of technological development, and other such issues.