Knowledge Graphs

As a team of research scientists and engineers, we develop methods and systems to extract, organize and enrich information about entities. Particularly, we extract information about entities from various sources of structured and unstructured data, integrate this information into large normalized knowledge graphs that contain billions of facts about millions of interconnected entities, and utilize these resulting knowledge graphs to create or enhance products and services across Yahoo, particularly for Web Search and Commerce use cases.

Publications

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November 9, 2021
Engineering Applications of Artificial Intelligence

Transfer-Based Taxonomy Induction Over Concept Labels

Paper
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August 11, 2021
ACM Multimedia 2021 (Industrial Track)

Distantly Supervised Semantic Text Detection and Recognition for Broadcast Sports Videos Understanding

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May 28, 2021

An Evaluation and Annotation Methodology for Product Category Matching in E-Commerce

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November 13, 2020
AAAI 2021

Empirical Best Practices on Using Product-Specific Schema.org

Paper
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November 12, 2020
ASONAM 2020

Locally Constructing Product Taxonomies from Scratch Using Representation Learning

Paper
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February 4, 2020
Wiki Workshop 2020/ WWW2020

Layered Graph Embedding for Entity Recommendation Using Wikipedia in the Yahoo! Knowledge Graph

Paper
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January 10, 2020
WWW 2020

Learning from Cross-Modal Behavior Dynamics with Graph-Regularized Neural Contextual Bandit

Paper
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January 1, 2019
Scientific Report

Community Detection on Networks with Ricci Flow