Towards a Predictive Patent Analytics and Evaluation Platform

Nebula Alam, Khoi-Nguyen Tran, Sue Ann Chen, John Wagner, Josh Andres, Mukesh K. Mohania

ECML-PKDD 2019 pp. 773-776

doi:10.1007/978-3-030-46133-1_49 /ecmlpkdd/2019/alam2019ecmlpkdd-predictive/

Abstract

The importance of patents is well recognised across many regions of the world. Many patent mining systems have been proposed, but with limited predictive capabilities. In this demo, we showcase how predictive algorithms leveraging the state-of-the-art machine learning and deep learning techniques can be used to improve understanding of patents for inventors, patent evaluators, and business analysts alike. Our demo video is available at this http URL

PDF ECML-PKDD Semantic Scholar

Cite

Text

Alam et al. "Towards a Predictive Patent Analytics and Evaluation Platform." European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2019. doi:10.1007/978-3-030-46133-1_49

Markdown

[Alam et al. "Towards a Predictive Patent Analytics and Evaluation Platform." European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2019.](https://mlanthology.org/ecmlpkdd/2019/alam2019ecmlpkdd-predictive/) doi:10.1007/978-3-030-46133-1_49

BibTeX

@inproceedings{alam2019ecmlpkdd-predictive,
  title     = {{Towards a Predictive Patent Analytics and Evaluation Platform}},
  author    = {Alam, Nebula and Tran, Khoi-Nguyen and Chen, Sue Ann and Wagner, John and Andres, Josh and Mohania, Mukesh K.},
  booktitle = {European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases},
  year      = {2019},
  pages     = {773-776},
  doi       = {10.1007/978-3-030-46133-1_49},
  url       = {https://mlanthology.org/ecmlpkdd/2019/alam2019ecmlpkdd-predictive/}
}