Building Knowledge Bases from the Web

Channel:
Microsoft Research
Subscribers:
344,000
Published on ● Video Link: https://www.youtube.com/watch?v=w3ggjhABk0M


Duration: 47:17
47 views
1

The web is a vast repository of human knowledge. Extracting structured data from web pages can enable applications like comparison shopping, and lead to improved ranking and rendering of search results. In this talk, I will describe a technique that exploits machine learning models to automatically extract records from web pages without human supervision. Specifically, we use Markov Logic Networks (MLNs) to capture content and structural features in a single unified framework, and devise a fast graph-based approach for MLN inference.



Other Videos By Microsoft Research


2016-08-11Summer Number Theory Day; Session 3
2016-08-11Annotating Images with Words, Phrases and Sentences
2016-08-11A Historical View of Large Margin Optimization Methods
2016-08-11Component Based Models: Graphical Models, Sparsity, Low-rank, and all of that Sort of Thing
2016-08-11Adaptive Sampling for Ranking and Clustering
2016-08-11Program Verification via SVMs
2016-08-11Monte Carlo Methods for Bayesian Reinforcement Learning and POMDP
2016-08-11Faculty Summit 2012 - Design Expo
2016-08-11Statistical Consistency and Regret Bounds for Ranking
2016-08-11Achieving High Data Rates in a Distributed MIMO System
2016-08-11Building Knowledge Bases from the Web
2016-08-11Random Graph Models of Kidney Exchange
2016-08-11Useful Spatio-Temporal Abstractions in Reinforcement Learning?
2016-08-11Markov Logic for Statistical Relational Learning
2016-08-11Supervised Dimension Reduction
2016-08-11Scalable Inference of Attributes in Entity-Relationship Graphs
2016-08-11Making SVMs Robust to Uncertainty in Kernel Matrices
2016-08-11Weakness Can Be Quarantined!
2016-08-11Noisy, Missing and Corrupted Data
2016-08-11Semi-Supervised Structured Output Learning
2016-08-11Functional Programming in the Wild


Tags:
microsoft research