English

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

Digital Libraries 2020-07-28 v1 Computation and Language Information Retrieval Machine Learning Social and Information Networks

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.

Keywords

Cite

@article{arxiv.2007.13520,
  title  = {Identification, Tracking and Impact: Understanding the trade secret of catchphrases},
  author = {Jagriti Jalal and Mayank Singh and Arindam Pal and Lipika Dey and Animesh Mukherjee},
  journal= {arXiv preprint arXiv:2007.13520},
  year   = {2020}
}

Comments

To be published in the proceedings of the ACM/IEEE Joint Conference on Digital Libraries (JCDL 2020)