Abstract
A trademark is a mark used by a company or a private human for the purpose of marking products or services that they manufacture or trade in. A restriction on the use of the trademark is necessary to enable sellers and manufacturers to build a reputation for themselves, to differentiate themselves from their competitors and thereby promote their businesses. In addition, the restriction also serves consumers and prevents their misuse by a name similar to another product. This restriction is done through the formal examination and approval of the trademarks. This process entails trademark examination against other approved trademarks which is currently a long manual process performed by experienced examiners. Current state-of-the-art trademark similarity search systems attempt to provide a single metric to quantify trademark similarities to a given mark [6–11]. In this work we introduce a new way to carry out this process, by simultaneously conducting several independent searches on different similarity aspects - Automated content similarity, Image/pixel similarity, Text similarity, and Manual content similarity. This separation enables us to benefit from the advantages of each aspect, as opposed to combining them into one similarity aspect and diminishing the significance of each one of them.
Original language | English |
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Title of host publication | HCI International 2019 - Posters - 21st International Conference, HCII 2019, Proceedings |
Editors | Constantine Stephanidis |
Publisher | Springer Verlag |
Pages | 97-105 |
Number of pages | 9 |
ISBN (Print) | 9783030235246 |
DOIs | |
State | Published - 2019 |
Externally published | Yes |
Event | 21st International Conference on Human-Computer Interaction, HCI International 2019 - Orlando, United States Duration: 26 Jul 2019 → 31 Jul 2019 |
Publication series
Name | Communications in Computer and Information Science |
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Volume | 1034 |
ISSN (Print) | 1865-0929 |
ISSN (Electronic) | 1865-0937 |
Conference
Conference | 21st International Conference on Human-Computer Interaction, HCI International 2019 |
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Country/Territory | United States |
City | Orlando |
Period | 26/07/19 → 31/07/19 |
Bibliographical note
Publisher Copyright:© Springer Nature Switzerland AG 2019.
Funding
This work was supported by Google, Israel Ministry of Justice, National Digital Israel Initiative and the Lynn and William Frankel Center for Computer Science. Patent Pending, “Similarity Search Engine for a Digital Visual Object”, IL/18-ORP/38222, Request No. 262220.
Funders | Funder number |
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Israel Ministry of Justice | |
Lynn and William Frankel Center for Computer Science | |
National Digital Israel Initiative | |
Keywords
- Artificial intelligence
- Computer vision
- Deep learning
- Image search
- Trademark