SE 305: Topics in Web-scale Knowledge Harvesting (3:1), Aug 2014

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SE 305: Topics in Web-scale Knowledge Harvesting

 

Course Flyer: https://sites.google.com/site/se3052014/SE305_Flyer.pdf

 

Instructor:   Partha Pratim Talukdar [ppt@serc, http://talukdar.net]

Time:         TTh 2pm – 3:30pm [first class: Aug 5, 2014 (Tue)]

Location:   SERC 202

Number:     SE 305

Credits:     3:1

Term:         Aug – Dec 2014

Homepage: https://sites.google.com/site/se3052014/

 

Topics

This is a research-focused course where we shall read papers to understand and extend state-of-the-art statistical machine learning techniques for various problems in web-scale knowledge base (KB) construction, e.g., entity categorization and resolution, relation extraction, distant supervision, KB inference, curriculum learning, learning from limited supervision in KB, representation learning for knowledge harvesting, etc.

Particular emphasis will be given to techniques that can scale to large datasets, preferably using distributed frameworks such as Hadoop.

 

Evaluation

Students will be evaluated based on their presentation and participation in class, and also a synthesis report or project (as preferred by the student) to be submitted at the end of the semester. Given the interdisciplinary nature of the topic, interested students from all backgrounds are welcome to participate.

 

Pre-requisites

Interest in any of the following: machine learning, natural language processing, large-data processing. Necessary background will be provided.