Text By the Bay 2015: Malcolm Greaves, Relation Extraction using Distant Supervision and SVMs

Scale By the Bay 2019 is held on November 13-15 in sunny Oakland, California, on the shores of Lake Merritt: https://scale.bythebay.io. Join us!
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Why do we want information? So that we can use it? So that our computers can use it? When we have access to rich, structured information we can make advanced applications that solve real-world pain points.

In this talk, I'll present an effective approach for automatically creating knowledge bases: databases of factual, general information. This relation extraction approach centers around the idea that we can use machine learning and natural language processing to automatically recognize information as it exists in real-world, unstructured text.

I'll cover the NLP tools, special ML considerations, and novel methods for creating a successful end-to-end relation extraction system. I will also cover experimental results with this system architecture in both big-data and a search-oriented environments.

Malcolm is a software engineer at Nitro. He works on crafting solutions to large-scale machine learning and natural language processing problems. Practitioner of functional programming practices. Keeps up to date with latest published algorithms and ideas, innovation through hacking novel solutions, and a master bug squasher. Formally, received both my Bachelor's ('13) and Master's ('14) of Computer Science from Carnegie Mellon University. During his undergraduate career, he was a research assistant to both Tom Mitchell and William Cohen. Under their tutelage, I learned the ins-and-outs of machine learning, natural language processing, information extraction, and designing algorithms to effortlessly handle big data. As a graduate student, Professor Cohen advised his Master's thesis on probabilistic relation extraction from unstructured text.