LDA to Find User Archetypes for Search and Matching: A Talk by Thomas Levi, Senior Data Scientist at PlentyOfFish.com
Thomas Levi started out with a doctorate in Theoretical Physics and String Theory from the University of Pennsylvania in 2006. His post-doctoral studies in cosmology and string theory, where he wrote 19 papers garnering 700+ citations, took him to NYU and finally UBC. In 2012, he decided to move into industry, and took on the role of Senior Data Scientist at Plenty of Fish. Thomas has been involved in diverse projects such as behaviour analysis, social network analysis, scam detection, Bot detection, matching algorithms, topic modelling and semantic analysis.
This talk will discuss how Plenty of Fish built a system utilizing topic modelling with Latent Dirichlet Allocation (LDA) on a several hundred thousand word vocabulary over ten million+ North American users. This system solves many issues with free text data entry including misspellings, synonyms, and similar entries to offer a deeper archetypal profiling and thematic search system for several million users.
Thursday, Feb. 19
2:30 – 4:00 pm
Room B121 on the Abbotsford UFV Campus
