Distributional Semantics – A Practical Introduction (ESSLLI 2016 & 2018)

Start page – Schedule – Software & data sets – Bibliography

Presentation slides (PDF, 1.1 MB) – handout (PDF, 0.9 MB) – R code

• motivation and brief history of distributional semantics
• common DSM architectures & prototypical applications
• first practical exercises with the wordspace package

Presentation slides (PDF, 1.3 MB) – handout (PDF, 1.0 MB) – R code – practice: input formats – exercise (DSM parameters)

• 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

Presentation slides (PDF, 2.0 MB) – handout (PDF, 1.8 MB) – R code – exercise (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

Presentation slides (PDF, 0.7 MB) – handout (PDF, 0.6 MB) – R code – bonus practice: Schütze-style WSD – exercise (roll your own DSM)

• basic matrix and vector operations, orthogonal projection & dimensionality reduction
• singular value decomposition (SVD)
• practical exercises: roll your own DSM with matrix operations

• mathematical properties of and relations between different types of DSM
• singular value decomposition (SVD) as a latent class model
• comparison with neural vector embeddings