LKE/KDSL Advanced Tutorial

LKE/KDSL is hosting an Advanced Tutorial by Dr. Judith Eckle-Kohler and Silvana Hartmann on Tuesday 13 January 2015, at 11:00 in S2|02 B002.

Title: Semi-supervised learning for semantic text processing- an introductory overview

Abstract: Machine Learning methods that are able to learn from both labeled and unlabeled data are commonly subsumed under the term semi-supervised learning. Semi-supervised learning is a very important approach for many practical applications in text processing, like relation extraction and sentiment analysis.

The first part of the tutorial reviews the most important methods for semi-supervised learning in the context of semantic text processing. Topics include bootstrapping methods, self-learning, distant supervision and their usage for various NLP tasks (e.g. sentiment analysis).

The second part of the tutorial will be organized as a mini-workshop: participants discuss in small groups, which semi-supervised methods would be best suited for their particular tasks and how they could be applied. Each group will then summarize the outcome of their discussion briefly in a 3-minute slot, leading to a plenary discussion and identification of topics relevant for further study.