Patentstar : A Wolfram 
Expert System 
for the 
European Patent Office

Mario Veruete, Ph.D. 
Quantum Datalab

#WolframTechConf

Joint work with Gianni Mocellin, Ph. D. Straco, Geneva, Switzerland

“Science is the joy of discussing in order to understand”

Talk on Friday : “4 Points in a 3-Universe”

ABSTRACT

We present a Wolfram-based expert system for patent analysis that leverages intelligent agents, combining native Wolfram Entities with user-defined ones, to interact with structured patent databases.

#SymbolicReasoning, #Automation, #KnowledgeRepresentation

Shaping the global flow of technological progress.

Patents

What is a patent?

A patent is a legal right granted to an inventor for a novel, non-obvious, and industrially applicable invention, giving exclusive control over its use and commercialization for a limited time.

Patents are identified by a unique number, like EP1431481162B1

Why patents are important?

individual scale: 
reward creativity, secure investment, protect intellectual effort

industrial scale: 
technology transfer, 
promote competition through disclosure, 
measurable assets for companies

societal scale:
fosters innovation ecosystems by transforming knowledge into structured, searchable information

Structure of a patent

Figures, Abstract, Description and Claims

With[
{
document=Import["/Users/dr.marioveruete/Downloads/US1329559.pdf","PageImages",ImageSize->Large]
},
Manipulate[
Part[document,page],
{page,1,Length[document],1},
ControlType->Setter,
ControlPlacement->Top,
SaveDefinitions->True
]
]

Patents Databases

Patent databases represent one of the most complex and structured information repositories in the legal and technical domains.

Data contained in a patent

Each patent record contains multiple interconnected data fields: bibliographic information (inventors, applicants, dates), technical content (claims, descriptions, drawings), citation networks, and legal metadata.

Using Entities

We create an entity for each patent containing its metadata

(Entity["EP  1323695  B1", Entity["Patent","EP  1323695  B1"], "Entity[\"Patent\", \"EP  1323695  B1\"]", "Patent"])

Metadata can be retrieved easily

(Entity["EP  1323695  B1", Entity["Patent","EP  1323695  B1"], "Entity[\"Patent\", \"EP  1323695  B1\"]", "Patent"])["publication.date"]

(Entity["EP  1323695  B1", Entity["Patent","EP  1323695  B1"], "Entity[\"Patent\", \"EP  1323695  B1\"]", "Patent"])["applicant"]

(Entity["EP  1323695  B1", Entity["Patent","EP  1323695  B1"], "Entity[\"Patent\", \"EP  1323695  B1\"]", "Patent"])["title.en"]

(Entity["EP  1323695  B1", Entity["Patent","EP  1323695  B1"], "Entity[\"Patent\", \"EP  1323695  B1\"]", "Patent"])["description.text"]

Patentstar live demo

Entities

AI agents

Data visualization

Patentstar uses Systar, our artificial science engine (developed in collaboration with Gianni Mocellin)