Zeljko Tekic

Threat of Litigation and Patent Value: What Technology Managers Should Know

OVERVIEW: Patent dealers have achieved exceptional growth in scale and scope of operations; today, their approaches to patent value affect intellectual property strategies for companies in many industries, even beyond the high-technology sector. To clarify the strategy patent dealers use, we studied a set of 392 U.S. patents sold to a patent dealer by a global consumer electronics firm; the dealer then sold the patents during 2010 and 2011. The analysis shows that under the strategy employed by patent dealers, patent value is driven by the threat of litigation—the higher the threat of litigation, the greater the monetary value of the patent. The evidence suggests that broadly drafted, older patents that cover mainstream technology and for which evidence of infringement may be ambiguous present a greater threat of litigation, and therefore carry a higher value.

Effectiveness of text processing in patent documents visualization

This paper analyzes effectiveness of text processing algorithm applied to different document parts for a data set consisting of patent documents. The algorithm is part of the software package which is used as a tool for business intelligence purposes. The tool assembles patent data from publicly available data bases, collects and analyzes patents bibliographic parameters and performs text mining. High-dimensional data contained in the patent documents are transformed into lower dimensionality space (2D or 3D), clustered and visualized. These features of the software tool enabled estimation of the effectiveness of text processing algorithm when run on different parts of the patent, such as abstract, claim, international patent code description and detailed patent description.

Technology matching of the patent documents using clustering algorithms

This paper analyzes the accuracy of different clustering algorithms to handle different parts of the patent documents. The algorithms are part of the software package which is used as a tool for business intelligence purposes. The tool assembles patent data from publicly available data bases, collects and analyzes patents bibliographic parameters and performs text mining. Performances of clustering algorithms: k-means, the neural-gas; fuzzy c-means and ronn algorithm are examined when run on different parts of the patent document, such as abstract, claim, international patent code description and detailed patent description, but applied on the same patent data set. Patent data set was previously classified in technology groups by the experts and obtained results are compared with the purpose of selection of the most suitable algorithm and patent document part.