Access to millions of US patents records will dramatically improve

January 07, 2016

AMHERST, Mass. - Thanks to the work of computer science researchers at the University of Massachusetts Amherst, the online database of the country's millions of inventors and patents will be much better to navigate for innovators, business and policy makers.

A team of UMass Amherst computer scientists took the top prize in an international competition sponsored by the U.S. Patent and Trademark Office (USPTO) and U.S. Department of Commerce. They designed a computer algorithm that rapidly removes inventor ambiguity from patent records, which will provide users more efficient and effective searches. Their winning approach will be incorporated into the USPTO's new online platform, PatentsView.

The team, advised by professor Andrew McCallum's Information Extraction and Synthesis Laboratory, produced the winning algorithm to take the top prize, which attracted entries from China, Germany, Australia, Belgium and the United States. McCallum, who is also the director of the UMass Center for Data Science, says other team members included graduate students Nicholas Monath and Ari Kobren; Michael Wick, now at Oracle Labs; Sameer Singh, now at the University of Washington, and Jack Sullivan, now at Cambridge Semantics.

Undersecretary of Commerce for Intellectual Property and USPTO director Michelle K. Lee said the goal of the workshop was "to encourage the development of novel approaches to reveal inventor identities across nearly 40 years of U.S. patent data." It will provide users more efficient and effective searches of the country's millions of inventors and patents.

As part of its win, the lab will receive a $25,000 stipend for technical guidance on applying the "entity disambiguation" algorithm to millions of patent records in the PatentsView platform.

"Winning was a great honor and it's a thrill to know this research will be used by the USPTO for the public good," says Monath, a native of Harvard, Mass. "The workshop also provided the opportunity to talk with people outside of computer science, in economics and policy, who rely on inventor data, which gave me new perspective for my research."

The UMass team took the top prize because its solution excelled in time and accuracy. "We had the fastest system in the competition and the system with the highest accuracy score," Monath says.

Entity disambiguation means differentiating among many individuals (entities) with similar attributes and grouping them together correctly, that is, unambiguously, says Monath, who studies machine learning and natural language processing. Inventor disambiguation is important to the USPTO because inventors often appear in patent records with different names, spellings and nicknames or because multiple inventors may have the same name.

Such ambiguities in the current system make data queries unreliable, requiring time-consuming manual intervention, the computer scientists explain. The competition asked contestants to "disambiguate" the inventors of over 12 million patent records filed between 1976 and 2014. Given the large size of the data set, manual data resolution would be unreasonable, which is why automated methods are necessary, they add.

Monath says, "Our method uses a hierarchical approach to disambiguation, which has several advantages over alternative pairwise approaches. Our method considers groups of two or more mentions in determining the disambiguation and has a more efficient disambiguation procedure."

Russell Slifer, USPTO deputy director, said at the competition workshop that PatentsView, a new web tool for the public to explore its warehouse of patenting data in the U.S., is intended to help innovators, business and policy makers by democratizing USPTO data. The office had always made 225 years of patent and trademark data available to the public, but it was difficult to use because of inconsistent formatting and complicated data formats. These cause inventor ambiguities, making the data useable only by the few people willing to spend the required time and effort.

PatentsView provides a more accessible online interface for patent searches. It allows any user to explore technological, regional and individual-level patent trends via search filters with multiple viewing options.
-end-


University of Massachusetts at Amherst

Related Algorithm Articles from Brightsurf:

CCNY & partners in quantum algorithm breakthrough
Researchers led by City College of New York physicist Pouyan Ghaemi report the development of a quantum algorithm with the potential to study a class of many-electron quantums system using quantum computers.

Machine learning algorithm could provide Soldiers feedback
A new machine learning algorithm, developed with Army funding, can isolate patterns in brain signals that relate to a specific behavior and then decode it, potentially providing Soldiers with behavioral-based feedback.

New algorithm predicts likelihood of acute kidney injury
In a recent study, a new algorithm outperformed the standard method for predicting which hospitalized patients will develop acute kidney injury.

New algorithm could unleash the power of quantum computers
A new algorithm that fast forwards simulations could bring greater use ability to current and near-term quantum computers, opening the way for applications to run past strict time limits that hamper many quantum calculations.

QUT algorithm could quash Twitter abuse of women
Online abuse targeting women, including threats of harm or sexual violence, has proliferated across all social media platforms but QUT researchers have developed a sophisticated statistical model to identify misogynistic content and help drum it out of the Twittersphere.

New learning algorithm should significantly expand the possible applications of AI
The e-prop learning method developed at Graz University of Technology forms the basis for drastically more energy-efficient hardware implementations of Artificial Intelligence.

Algorithm predicts risk for PTSD after traumatic injury
With high precision, a new algorithm predicts which patients treated for traumatic injuries in the emergency department will later develop posttraumatic stress disorder.

New algorithm uses artificial intelligence to help manage type 1 diabetes
Researchers and physicians at Oregon Health & Science University have designed a method to help people with type 1 diabetes better manage their glucose levels.

A new algorithm predicts the difficulty in fighting fire
The tool completes previous studies with new variables and could improve the ability to respond to forest fires.

New algorithm predicts optimal materials among all possible compounds
Skoltech researchers have offered a solution to the problem of searching for materials with required properties among all possible combinations of chemical elements.

Read More: Algorithm News and Algorithm Current Events
Brightsurf.com is a participant in the Amazon Services LLC Associates Program, an affiliate advertising program designed to provide a means for sites to earn advertising fees by advertising and linking to Amazon.com.