TradeMarker - Artificial Intelligence Based Trademarks Similarity Search Engine

Idan Mosseri, Matan Rusanovsky, Gal Oren

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Scopus citations


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 languageEnglish
Title of host publicationHCI International 2019 - Posters - 21st International Conference, HCII 2019, Proceedings
EditorsConstantine Stephanidis
PublisherSpringer Verlag
Number of pages9
ISBN (Print)9783030235246
StatePublished - 2019
Externally publishedYes
Event21st International Conference on Human-Computer Interaction, HCI International 2019 - Orlando, United States
Duration: 26 Jul 201931 Jul 2019

Publication series

NameCommunications in Computer and Information Science
ISSN (Print)1865-0929
ISSN (Electronic)1865-0937


Conference21st International Conference on Human-Computer Interaction, HCI International 2019
Country/TerritoryUnited States

Bibliographical note

Publisher Copyright:
© Springer Nature Switzerland AG 2019.


  • Artificial intelligence
  • Computer vision
  • Deep learning
  • Image search
  • Trademark


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