Using Data to Automate Knowledge Generation || Ella Bor

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At Twiggle, we learn and understand users' queries and match their relevant products. To that end, we are building our own ontology of the world, and an advanced Natural Language Analyzer which aims to map both queries and products from across the e-commerce domain onto our ontology. Building an ontology is a tedious task which requires both specialized expertise as well as a broad look on the way the world is built. To facilitate that process, we have developed a unique algorithm. The algorithm generates a data-driven ontology by applying Node2Vec and clustering methods on query-to-product clicks along with minimal information about these products. In this talk, we will discuss this algorithm and offer a deep dive into the methods we used.

EVENT:

PyData Tel Aviv 2019

SPEAKER:

Ella Bor

PUBLICATION PERMISSIONS:

PyData provided Coding Tech with the permission to republish PyData talks.

CREDITS:

PyData YouTube channel: https://www.youtube.com/channel/UCOjD18EJYcsBog4IozkF_7w







Tags:
data analysis
research
python
machine learning