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Distributional Semantics – A Practical Introduction (ESSLLI 2016 & 2018)
Start page – Schedule – Software & data sets – Bibliography
- small corrections to part 1 slides
- final version of part 2 slides + R code + practice
Schedule & handouts
Day 1: Introduction
Presentation slides (PDF, 0.9MiB) – handout (PDF, 1.0 MiB) – R code
- motivation and brief history of distributional semantics
- common DSM architectures & prototypical applications
- first practical exercises with the
wordspace
package
Day 2: The parameters of a DSM
Presentation slides (PDF, 1.0MiB) – handout (PDF, 1.2 MiB)
- taxonomy of DSM parameters: context representation, feature scaling, normalization and standardization, distance/similarity measures, dimensionality reduction
- overview of common parameter settings & best-practice recommendations
- practical exercises: building DSMs and exploring their parameters
Day 3: Applications and evaluation
- attributional and relational similarity, clustering and semantic categorization, multiple-choice tasks
- insights from recent parameter evaluation studies
- practical exercises: implementation and evaluation of selected tasks
Day 4: Elements of matrix algebra
- basic matrix and vector operations, orthogonal projection & dimensionality reduction
- singular value decomposition (SVD)
- practical exercises: roll your own DSM with matrix operations
Day 5: Making sense of DSMs
- mathematical properties of and relations between different types of DSM
- singular value decomposition (SVD) as a latent class model
- comparison with neural vector embeddings