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course:acl2010:schedule [2010/06/03 04:50] schtepf created |
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| **Schedule** – | **Schedule** – | ||
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| [[course: | [[course: | ||
| ===== Schedule & handouts ===== | ===== Schedule & handouts ===== | ||
| + | |||
| + | === Part 1 === | ||
| + | |||
| + | [[http:// | ||
| + | |||
| + | * **Introduction** | ||
| + | * motivation and brief history of distributional semantics | ||
| + | * common DSM architectures | ||
| + | * prototypical applications | ||
| + | |||
| + | * **Taxonomy of DSM parameters** including | ||
| + | * size and type of context window | ||
| + | * feature scaling (tf.idf, statistical association measures, ...) | ||
| + | * normalisation and standardisation of rows and/or columns | ||
| + | * distance/ | ||
| + | * dimensionality reduction: feature selection, SVD, random indexing (RI) | ||
| + | |||
| + | * **Usage and evaluation of DSM** | ||
| + | * what to do with DSM distances | ||
| + | * attributional vs. relational similarity | ||
| + | * evaluation tasks & results for attributional similarity | ||
| + | |||
| + | ---- | ||
| + | |||
| + | === Part 2 === | ||
| + | |||
| + | {{: | ||
| + | |||
| + | //Part 2 was not covered in the tutorial session at NAACL-HLT 2010. An extended version of the presentation slides & handout has been superseded by a five-part tutorial presented at [[course: | ||
| + | \\ | ||
| + | \\ | ||
| + | |||
| + | * **Elements of matrix algebra** for DSM | ||
| + | * basic matrix and vector operations | ||
| + | * norms and distances, angles, orthogonality | ||
| + | * projection and dimensionality reduction | ||
| + | |||
| + | * **Making sense of DSMs**: mathematical analysis and visualisation techniques | ||
| + | * nearest neighbours and clustering | ||
| + | * semantic maps: PCA, MDS, SOM | ||
| + | * visualisation of high-dimensional spaces | ||
| + | * supervised classification based on DSM vectors | ||
| + | * understanding dimensionality reduction with SVD and RI | ||
| + | * term-term vs. term-context matrix, connection to first-order association | ||
| + | * SVD as a latent class model | ||
| + | |||
| + | * **Current research topics** and future directions | ||
| + | * overview of current research on DSMs | ||
| + | * evaluation tasks and data sets | ||
| + | * available " | ||
| + | * limitations and key problems of DSMs | ||
| + | * trends for future work | ||