Identifying patent monetization entities

Mihai Surdeanu, Sara Jeruss

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

The United States has seen an explosion in patent litigation lawsuits in recent years. Recent studies indicate that a large proportion of these lawsuits, increasing from 22% in 2007 to 40% in 2011, were filed by patent monetization entities (PMEs), i.e., companies that hold patents, license patents, and file patent lawsuits, but do not sell products or provide services practicing the technologies described in their patents. We introduce a classifier that identifies which patent litigation lawsuits are initiated by PMEs. Using features extracted from the entities' litigation behavior, the patents they asserted, and their presence on the web, the proposed classifier correctly separates PMEs from operating companies with a F1 score of 85%. We believe that such a classifier will be a useful tool to policy makers and patent litigators, allowing them to gain a clearer picture of the 37, 000+ patent lawsuits filed to date and assessing newly filed cases in real time.

Original languageEnglish (US)
Title of host publicationProceedings of the International Conference on Artificial Intelligence and Law
Pages131-139
Number of pages9
DOIs
StatePublished - 2013
Event14th International Conference on Artificial Intelligence and Law, ICAIL 2013 - Rome, Italy
Duration: Jun 10 2013Jun 14 2013

Other

Other14th International Conference on Artificial Intelligence and Law, ICAIL 2013
CountryItaly
CityRome
Period6/10/136/14/13

Fingerprint

patent
Classifiers
lawsuit
Explosions
Industry
license

ASJC Scopus subject areas

  • Software
  • Artificial Intelligence
  • Law

Cite this

Surdeanu, M., & Jeruss, S. (2013). Identifying patent monetization entities. In Proceedings of the International Conference on Artificial Intelligence and Law (pp. 131-139) https://doi.org/10.1145/2514601.2514616

Identifying patent monetization entities. / Surdeanu, Mihai; Jeruss, Sara.

Proceedings of the International Conference on Artificial Intelligence and Law. 2013. p. 131-139.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Surdeanu, M & Jeruss, S 2013, Identifying patent monetization entities. in Proceedings of the International Conference on Artificial Intelligence and Law. pp. 131-139, 14th International Conference on Artificial Intelligence and Law, ICAIL 2013, Rome, Italy, 6/10/13. https://doi.org/10.1145/2514601.2514616
Surdeanu M, Jeruss S. Identifying patent monetization entities. In Proceedings of the International Conference on Artificial Intelligence and Law. 2013. p. 131-139 https://doi.org/10.1145/2514601.2514616
Surdeanu, Mihai ; Jeruss, Sara. / Identifying patent monetization entities. Proceedings of the International Conference on Artificial Intelligence and Law. 2013. pp. 131-139
@inproceedings{0cf13f9161dc44d99d01509113d359e7,
title = "Identifying patent monetization entities",
abstract = "The United States has seen an explosion in patent litigation lawsuits in recent years. Recent studies indicate that a large proportion of these lawsuits, increasing from 22{\%} in 2007 to 40{\%} in 2011, were filed by patent monetization entities (PMEs), i.e., companies that hold patents, license patents, and file patent lawsuits, but do not sell products or provide services practicing the technologies described in their patents. We introduce a classifier that identifies which patent litigation lawsuits are initiated by PMEs. Using features extracted from the entities' litigation behavior, the patents they asserted, and their presence on the web, the proposed classifier correctly separates PMEs from operating companies with a F1 score of 85{\%}. We believe that such a classifier will be a useful tool to policy makers and patent litigators, allowing them to gain a clearer picture of the 37, 000+ patent lawsuits filed to date and assessing newly filed cases in real time.",
author = "Mihai Surdeanu and Sara Jeruss",
year = "2013",
doi = "10.1145/2514601.2514616",
language = "English (US)",
isbn = "9781450320801",
pages = "131--139",
booktitle = "Proceedings of the International Conference on Artificial Intelligence and Law",

}

TY - GEN

T1 - Identifying patent monetization entities

AU - Surdeanu, Mihai

AU - Jeruss, Sara

PY - 2013

Y1 - 2013

N2 - The United States has seen an explosion in patent litigation lawsuits in recent years. Recent studies indicate that a large proportion of these lawsuits, increasing from 22% in 2007 to 40% in 2011, were filed by patent monetization entities (PMEs), i.e., companies that hold patents, license patents, and file patent lawsuits, but do not sell products or provide services practicing the technologies described in their patents. We introduce a classifier that identifies which patent litigation lawsuits are initiated by PMEs. Using features extracted from the entities' litigation behavior, the patents they asserted, and their presence on the web, the proposed classifier correctly separates PMEs from operating companies with a F1 score of 85%. We believe that such a classifier will be a useful tool to policy makers and patent litigators, allowing them to gain a clearer picture of the 37, 000+ patent lawsuits filed to date and assessing newly filed cases in real time.

AB - The United States has seen an explosion in patent litigation lawsuits in recent years. Recent studies indicate that a large proportion of these lawsuits, increasing from 22% in 2007 to 40% in 2011, were filed by patent monetization entities (PMEs), i.e., companies that hold patents, license patents, and file patent lawsuits, but do not sell products or provide services practicing the technologies described in their patents. We introduce a classifier that identifies which patent litigation lawsuits are initiated by PMEs. Using features extracted from the entities' litigation behavior, the patents they asserted, and their presence on the web, the proposed classifier correctly separates PMEs from operating companies with a F1 score of 85%. We believe that such a classifier will be a useful tool to policy makers and patent litigators, allowing them to gain a clearer picture of the 37, 000+ patent lawsuits filed to date and assessing newly filed cases in real time.

UR - http://www.scopus.com/inward/record.url?scp=84883538909&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84883538909&partnerID=8YFLogxK

U2 - 10.1145/2514601.2514616

DO - 10.1145/2514601.2514616

M3 - Conference contribution

AN - SCOPUS:84883538909

SN - 9781450320801

SP - 131

EP - 139

BT - Proceedings of the International Conference on Artificial Intelligence and Law

ER -