PATENT SEARCHES Istituto Nazionale Fisica Nucleare Rossella Osella

Roadmap INTRODUCTION TO PATENT SEARCHES ORBIT Patent searches portal and IP Business Intelligence SEARCH EXAMPLES 2

The role of patents Protection and economic exploitation of the inventions Sources of information: technical, scientific, business publicly available 3

Importance of patent information Volume Content Accessibility First account 4

Use of patent information Survey state of the art competitors’ activities Identify solutions to technical problems licensing opportunities Avoid duplication of R&D efforts infringements 5

Patent databases Worldwide bibliographic Search fields: bibliographic data, title and abstract (as published by the inventor or enriched by the producer) Full text Search fields: bibliographic data, title, abstract (as published by the inventor), description, claims 6

Operators Bibliographic data Keywords Search fields Classification 7

Patent search types State of the art Patentability Freedom of use Bibliographic searches Opposition and validity 8 Landscape and mapping

Fampat: patent family database One database FamPat Legal Status information 45 countries Full Text Data 21 countries Bibliographic patent data 95 countries Patent copies 40 countries Citations 20 countries US reassignments

Language technology Machine translations Multilingual wizard Key-content Concepts

IP Business Intelligence More Charts Filing trend analysis: multi-dimensional views by publication and priority date, publication and priority country Major players identification: Inventors, Assignees, Agents Technology analysis: IPC, ECLA, USCLASS codes Concepts analysis Legal Status analysis Citation analysis Full interactivity with search module Mapping and Clustering based on similarity 12

Search examples Novelty search Are there relevant patents in the field of detection of high energy particles by hybrid diamond-silicon devices? Landscaping Overview on radiation dosimeters: technologies and applications

Search strategy

Search history

NOVELTY SEARCH

Search hit from step 1

LANDSCAPING

Top 30 Assignees

Top 30 Priority countries

Distribution by publication date

G01T-001/00 Measuring X-radiation, gamma radiation, corpuscular radiation or cosmic radiation Top 75 Concepts A61N-005/10 Radiation therapy X-ray therapy; Gamma-ray therapy; Particle-irradiation therapy

Mapping

Grazie

Key content Extracted from US, EP, WO, full-text in English Identify key sentences describing patent object, advantages and drawbacks, independent claims Uses morpho-syntactic analysis to spot important sentences Good compromise between conciseness of bibliographic abstracts and full text

FamPat Concepts – Field available in FamPat – Extracted from US, EP, WO, full-text in English – The Concept Field contains keywords and multiword phrases that can be used in searching, browsing and in analysing

Concept extraction Main idea: extract concepts rather than words as a semantic model of patent documents, weight concepts according to sentence type To deal with large volume we need to do this upfront when loading the data

Semantic concept tagging « noun phrases » identification – Part-of-speech + stemming – Verb Suppression, some adjectives – Suppress typical“patent” terminology « preferred embodiment », « skilled artisan » …. – Syntactic normalization : « surface of screens »  « screen surface » Relevance score computation, based on: – Field, key sentence morpho-syntactic detection, and number of occurrences

Concept extraction example The invention relates generally to molecular level cleaning of parts by vapor degreasing. More particularly, the invention relates to a solvent mixture comprising n-propyl bromide, a [mixture of low boiling solvents] and, … The solvent mixture of the invention is non- flammable, non-corrosive, non-hazardous, and has a low ozone depletion potential.

Normalization examples the heat conductivity the conduction of heat heat conductivity heat conduction HEAT CONDUCTION the user of the cellular telephone cellular phone users a user of a mobile telephone any mobile phone users their user mobile telephones MOBILE PHONE USER

Concepts Each key concept is “scored” Score calculation based on: – Occurrences of the concept in the doc – Fields where the concepts appear – Frequency of the multiword concept in the database – Frequency of the concept words in the database – Non-linear formula (QUESTEL Lingway trade secret) – Normalized to 100 (high score)