Abstract
A technology directed to using deep learning to help users in the advertising space, domain name recommendation space, search result generation space, username suggestion space, or any related area is described. The deep learning technique can embed linguistic features of words in a latent space and perform mathematical functions to determine the similarity and/or relatedness between a target word and words that should be avoided in particular target languages. This can be advantageous for individuals in these spaces who are presented with options for good or product names to be used in global markets and/or in markets that are a different language than the user and/or the market that a product is originally launched in. The use of machine learning to make these determinations can be used alone or in combination with a human reviewer that is well versed in a target language. This can decrease cost to the user (e.g., content provider, advertiser, etc.) and increase access to these kinds of comparisons and reviews for a wider range of users (e.g., content providers, advertisers, marketers, etc.).
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
N/A, "Maximizing Linguistic Distance between Good and Bad Product Names when Competing in Global Markets", Technical Disclosure Commons, (April 25, 2022)
https://www.tdcommons.org/dpubs_series/5089