Identification, Tracking and Impact: Understanding the trade secret of catchphrases

July 20, 2020 Β· Declared Dead Β· πŸ› ACM/IEEE Joint Conference on Digital Libraries

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Authors Jagriti Jalal, Mayank Singh, Arindam Pal, Lipika Dey, Animesh Mukherjee arXiv ID 2007.13520 Category cs.DL: Digital Libraries Cross-listed cs.CL, cs.IR, cs.LG, cs.SI Citations 1 Venue ACM/IEEE Joint Conference on Digital Libraries Last Checked 3 months ago
Abstract
Understanding the topical evolution in industrial innovation is a challenging problem. With the advancement in the digital repositories in the form of patent documents, it is becoming increasingly more feasible to understand the innovation secrets -- "catchphrases" of organizations. However, searching and understanding this enormous textual information is a natural bottleneck. In this paper, we propose an unsupervised method for the extraction of catchphrases from the abstracts of patents granted by the U.S. Patent and Trademark Office over the years. Our proposed system achieves substantial improvement, both in terms of precision and recall, against state-of-the-art techniques. As a second objective, we conduct an extensive empirical study to understand the temporal evolution of the catchphrases across various organizations. We also show how the overall innovation evolution in the form of introduction of newer catchphrases in an organization's patents correlates with the future citations received by the patents filed by that organization. Our code and data sets will be placed in the public domain soon.
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