The purpose of the present research is to design a method capable of automatically detecting and extracting one of the multiple entities hidden in patents: the users of the invention.
Patents contain a large quantity of information which is usually neglected. This information is hidden beneath technical and juridical jargon and therefore so many potential readers cannot take advantage of it. State of the art natural language processing tools and in particular named entity recognition tools, could be used to detect valuable concepts in patent documents.
Automatic users extraction from patents
Cimino Andrea;Dell'Orletta Felice
2018
Abstract
Patents contain a large quantity of information which is usually neglected. This information is hidden beneath technical and juridical jargon and therefore so many potential readers cannot take advantage of it. State of the art natural language processing tools and in particular named entity recognition tools, could be used to detect valuable concepts in patent documents.| Campo DC | Valore | Lingua |
|---|---|---|
| dc.authority.ancejournal | WORLD PATENT INFORMATION | - |
| dc.authority.orgunit | Istituto di linguistica computazionale "Antonio Zampolli" - ILC | - |
| dc.authority.people | Chiarello Filippo | it |
| dc.authority.people | Cimino Andrea | it |
| dc.authority.people | Fantoni Gualtiero | it |
| dc.authority.people | Dell'Orletta Felice | it |
| dc.collection.id.s | b3f88f24-048a-4e43-8ab1-6697b90e068e | * |
| dc.collection.name | 01.01 Articolo in rivista | * |
| dc.contributor.appartenenza | Istituto di linguistica computazionale "Antonio Zampolli" - ILC | * |
| dc.contributor.appartenenza.mi | 918 | * |
| dc.date.accessioned | 2024/02/20 17:19:43 | - |
| dc.date.available | 2024/02/20 17:19:43 | - |
| dc.date.issued | 2018 | - |
| dc.description.abstract | The purpose of the present research is to design a method capable of automatically detecting and extracting one of the multiple entities hidden in patents: the users of the invention. | - |
| dc.description.abstracteng | Patents contain a large quantity of information which is usually neglected. This information is hidden beneath technical and juridical jargon and therefore so many potential readers cannot take advantage of it. State of the art natural language processing tools and in particular named entity recognition tools, could be used to detect valuable concepts in patent documents. | - |
| dc.description.affiliations | Università di Pisa; Istituto di Linguistica Computazionale "A. Zampolli", (ILC), CNR, Pisa, Italy | - |
| dc.description.allpeople | Chiarello, Filippo; Cimino, Andrea; Fantoni, Gualtiero; Dell'Orletta, Felice | - |
| dc.description.allpeopleoriginal | Chiarello, Filippo; Cimino, Andrea; Fantoni, Gualtiero; Dell'Orletta, Felice | - |
| dc.description.fulltext | none | en |
| dc.description.numberofauthors | 4 | - |
| dc.identifier.doi | 10.1016/j.wpi.2018.07.006 | - |
| dc.identifier.isi | WOS:000448261100004 | - |
| dc.identifier.scopus | 2-s2.0-85050819071 | - |
| dc.identifier.uri | https://hdl.handle.net/20.500.14243/392587 | - |
| dc.language.iso | eng | - |
| dc.relation.firstpage | 28 | - |
| dc.relation.lastpage | 38 | - |
| dc.relation.numberofpages | 11 | - |
| dc.relation.volume | 54 | - |
| dc.subject.keywords | Patent analysis | - |
| dc.subject.keywords | Deep learning | - |
| dc.subject.keywords | Text mining | - |
| dc.subject.singlekeyword | Patent analysis | * |
| dc.subject.singlekeyword | Deep learning | * |
| dc.subject.singlekeyword | Text mining | * |
| dc.title | Automatic users extraction from patents | en |
| dc.type.driver | info:eu-repo/semantics/article | - |
| dc.type.full | 01 Contributo su Rivista::01.01 Articolo in rivista | it |
| dc.type.miur | 262 | - |
| dc.type.referee | Sì, ma tipo non specificato | - |
| dc.ugov.descaux1 | 434918 | - |
| iris.isi.extIssued | 2018 | - |
| iris.isi.extTitle | Automatic users extraction from patents | - |
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| iris.scopus.extTitle | Automatic users extraction from patents | - |
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| isi.authority.ancejournal | WORLD PATENT INFORMATION###0172-2190 | * |
| isi.authority.sdg | Goal 9: Industry, Innovation, and Infrastructure###12089 | * |
| isi.category | NU | * |
| isi.contributor.affiliation | University of Pisa | - |
| isi.contributor.affiliation | Consiglio Nazionale delle Ricerche (CNR) | - |
| isi.contributor.affiliation | University of Pisa | - |
| isi.contributor.affiliation | Consiglio Nazionale delle Ricerche (CNR) | - |
| isi.contributor.country | Italy | - |
| isi.contributor.country | Italy | - |
| isi.contributor.country | Italy | - |
| isi.contributor.country | Italy | - |
| isi.contributor.name | Filippo | - |
| isi.contributor.name | Andrea | - |
| isi.contributor.name | Gualtiero | - |
| isi.contributor.name | Felice | - |
| isi.contributor.researcherId | DVB-0474-2022 | - |
| isi.contributor.researcherId | FZH-1637-2022 | - |
| isi.contributor.researcherId | GWZ-8445-2022 | - |
| isi.contributor.researcherId | AAX-1864-2020 | - |
| isi.contributor.subaffiliation | Dept Energy Syst Terr & Construct Engn | - |
| isi.contributor.subaffiliation | CNR | - |
| isi.contributor.subaffiliation | Dept Mech Nucl & Prod Engn | - |
| isi.contributor.subaffiliation | CNR | - |
| isi.contributor.surname | Chiarello | - |
| isi.contributor.surname | Cimino | - |
| isi.contributor.surname | Fantoni | - |
| isi.contributor.surname | Dell'Orletta | - |
| isi.date.issued | 2018 | * |
| isi.description.abstracteng | Patents contain a large quantity of information which is usually neglected. This information is hidden beneath technical and juridical jargon and therefore so many potential readers cannot take advantage of it. State of the art natural language processing tools and in particular named entity recognition tools, could be used to detect valuable concepts in patent documents.The purpose of the present research is to design a method capable of automatically detecting and extracting one of the multiple entities hidden in patents: the users of the invention.The method is based on a new approach tailored for users extraction by integrating state-of-the-art computational linguistics tools with a large knowledge base. Furthermore the paper shows a comparison among different machine learning algorithms with the twofold aim of achieving the highest recall and evaluating the performance in terms of precision and computational effort.Finally, a case study on two patent sets has been conducted to evaluate the effectiveness and the output of the entire tool-chain. | * |
| isi.description.allpeopleoriginal | Chiarello, F; Cimino, A; Fantoni, G; Dell'Orletta, F; | * |
| isi.document.sourcetype | WOS.ESCI | * |
| isi.document.type | Article | * |
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| isi.identifier.doi | 10.1016/j.wpi.2018.07.006 | * |
| isi.identifier.eissn | 1874-690X | * |
| isi.identifier.isi | WOS:000448261100004 | * |
| isi.journal.journaltitle | WORLD PATENT INFORMATION | * |
| isi.journal.journaltitleabbrev | WORLD PAT INF | * |
| isi.language.original | English | * |
| isi.publisher.place | RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS | * |
| isi.relation.firstpage | 28 | * |
| isi.relation.lastpage | 38 | * |
| isi.relation.volume | 54 | * |
| isi.title | Automatic users extraction from patents | * |
| scopus.authority.ancejournal | WORLD PATENT INFORMATION###0172-2190 | * |
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| scopus.contributor.affiliation | University of Pisa | - |
| scopus.contributor.affiliation | Institute for Computational Linguistics of the Italian National Research Council (ILC-CNR) | - |
| scopus.contributor.affiliation | University of Pisa | - |
| scopus.contributor.affiliation | Institute for Computational Linguistics of the Italian National Research Council (ILC-CNR) | - |
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| scopus.contributor.country | Italy | - |
| scopus.contributor.country | Italy | - |
| scopus.contributor.country | Italy | - |
| scopus.contributor.country | Italy | - |
| scopus.contributor.dptid | 104458854 | - |
| scopus.contributor.dptid | - | |
| scopus.contributor.dptid | 104458875 | - |
| scopus.contributor.dptid | - | |
| scopus.contributor.name | Filippo | - |
| scopus.contributor.name | Andrea | - |
| scopus.contributor.name | Gualtiero | - |
| scopus.contributor.name | Felice | - |
| scopus.contributor.subaffiliation | Department of Energy;Systems;Territory and Construction Engineering; | - |
| scopus.contributor.subaffiliation | - | |
| scopus.contributor.subaffiliation | Department of Mechanical;Nuclear and Production Engineering; | - |
| scopus.contributor.subaffiliation | - | |
| scopus.contributor.surname | Chiarello | - |
| scopus.contributor.surname | Cimino | - |
| scopus.contributor.surname | Fantoni | - |
| scopus.contributor.surname | Dell'Orletta | - |
| scopus.date.issued | 2018 | * |
| scopus.description.abstracteng | Patents contain a large quantity of information which is usually neglected. This information is hidden beneath technical and juridical jargon and therefore so many potential readers cannot take advantage of it. State of the art natural language processing tools and in particular named entity recognition tools, could be used to detect valuable concepts in patent documents. The purpose of the present research is to design a method capable of automatically detecting and extracting one of the multiple entities hidden in patents: the users of the invention. The method is based on a new approach tailored for users extraction by integrating state-of-the-art computational linguistics tools with a large knowledge base. Furthermore the paper shows a comparison among different machine learning algorithms with the twofold aim of achieving the highest recall and evaluating the performance in terms of precision and computational effort. Finally, a case study on two patent sets has been conducted to evaluate the effectiveness and the output of the entire tool-chain. | * |
| scopus.description.allpeopleoriginal | Chiarello F.; Cimino A.; Fantoni G.; Dell'Orletta F. | * |
| scopus.differences | scopus.subject.keywords | * |
| scopus.differences | scopus.description.allpeopleoriginal | * |
| scopus.differences | scopus.description.abstracteng | * |
| scopus.document.type | ar | * |
| scopus.document.types | ar | * |
| scopus.identifier.doi | 10.1016/j.wpi.2018.07.006 | * |
| scopus.identifier.pui | 2000991137 | * |
| scopus.identifier.scopus | 2-s2.0-85050819071 | * |
| scopus.journal.sourceid | 15069 | * |
| scopus.language.iso | eng | * |
| scopus.publisher.name | Elsevier Ltd | * |
| scopus.relation.firstpage | 28 | * |
| scopus.relation.lastpage | 38 | * |
| scopus.relation.volume | 54 | * |
| scopus.subject.keywords | Deep learning; Patent analysis; Text mining; User of an invention; | * |
| scopus.title | Automatic users extraction from patents | * |
| scopus.titleeng | Automatic users extraction from patents | * |
| Appare nelle tipologie: | 01.01 Articolo in rivista | |
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