Information extraction from social media: A hands-on tutorial on tasks, data, & open source tools
Skip to the content. WWW 2021 Tutorial - Information extraction from social media: A hands-on tutorial on tasks, data, & open source tools Tutorial Home Date: April 14, 2021 Time: 9:00 AM EST (3:00 PM CEST) Venue: 12:00 PM EST (6:00 PM CEST) Tutorial URL: https://theweb.miteam.eu/asset/tJrKgy3y4na4dssWc Slides: PDF PPTX Contact: Shubhanshu Mishra at https://twitter.com/TheShubhanshu Presenters: Sh
Combining knowledge graphs, quickly and accurately
Knowledge graphs are a way of representing information that can capture complex relationships more easily than conventional databases. At Amazon, we use knowledge graphs to represent the hierarchical relationships between product types on amazon.com; the relationships between creators and content on Amazon Music and Prime Video; and general information for Alexa’s question-answering service — amon
Ups and Downs: Modeling the Visual Evolution of Fashion Trends with One-Class Collaborative Filtering
Building a successful recommender system depends on understanding both the dimensions of people's preferences as well as their dynamics. In certain domains, such as fashion, modeling such preferences can be incredibly difficult, due to the need to simultaneously model the visual appearance of products as well as their evolution over time. The subtle semantics and non-linear dynamics of fashion evo
What is the science of inspiration?
What is the science of inspiration? People from around the world regard Pinterest as the place for inspiration. Pinterest is for exploring possibilities when you have a question with more than one right answer. Pinterest Labs is a group dedicated to using Machine Learning to bring inspiration to everyone. We're solving the problem of discovery online, and doing it in an inspiring and inclusive way
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https://dl.acm.org/doi/abs/10.1145/3543507.3583310
https://arxiv.org/pdf/2001.06917.pdf
Expanding Taxonomies with Implicit Edge Semantics (TheWebConf/WWW 2020)
Expanding Taxonomies with Implicit Edge Semantics
Expanding Taxonomies with Implicit Edge Semantics
WebProt\'eg\'e: A Cloud-Based Ontology Editor
https://www.ra.ethz.ch/CDstore/www2010/www/p431.pdf
Optimizing email marketing campaigns in the airline industry using knowledge graph embeddings | EURECOM
WWW 2021 Workshop
https://dl.acm.org/doi/10.1145/3041021.3054199
HumL
Novel Entity Discovery from Web Tables
WWWでの論文採択とA/Bテストを評価地点とする広告AI開発 - Speaker Deck
Innovations in Graph Representation Learning
Pixie: a system for recommending 3+ billion items to 200+ million users in real-time | the morning paper
When Fashion Meets Big Data: Discriminative Mining of Best Selling Clothing Features