Cardiff University | Prifysgol Caerdydd ORCA
Online Research @ Cardiff 
WelshClear Cookie - decide language by browser settings

Semantic retrieval of trademarks based on conceptual similarity

Anuar, Fatahiyah Mohd, Setchi, Rossitza ORCID: https://orcid.org/0000-0002-7207-6544 and Lai, Yu-Kun ORCID: https://orcid.org/0000-0002-2094-5680 2016. Semantic retrieval of trademarks based on conceptual similarity. IEEE Transactions on Systems Man and Cybernetics: Systems 46 (2) , pp. 220-233. 10.1109/TSMC.2015.2421878

[thumbnail of SETCHI - Semantic retrieval of Trademarks.pdf]
Preview
PDF - Accepted Post-Print Version
Download (1MB) | Preview

Abstract

Trademarks are signs of high reputational value. Thus, they require protection. This paper studies conceptual similarities between trademarks, which occurs when two or more trademarks evoke identical or analogous semantic content. This paper advances the state-of-the-art by proposing a computational approach based on semantics that can be used to compare trademarks for conceptual similarity. A trademark retrieval algorithm is developed that employs natural language processing techniques and an external knowledge source in the form of a lexical ontology. The search and indexing technique developed uses similarity distance, which is derived using Tversky's theory of similarity. The proposed retrieval algorithm is validated using two resources: a trademark database of 1400 disputed cases and a database of 378,943 company names. The accuracy of the algorithm is estimated using measures from two different domains: the R-precision score, which is commonly used in information retrieval and human judgment/collective human opinion, which is used in human-machine systems.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Computer Science & Informatics
Engineering
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Publisher: IEEE
ISSN: 2168-2216
Date of First Compliant Deposit: 30 March 2016
Date of Acceptance: 14 March 2015
Last Modified: 14 Feb 2024 17:39
URI: https://orca.cardiff.ac.uk/id/eprint/73641

Citation Data

Cited 17 times in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item Edit Item

Downloads

Downloads per month over past year

View more statistics