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course:esslli2018:schedule [2018/08/07 22:10]
schtepf [Distributional Semantics – A Practical Introduction (ESSLLI 2016 & 2018)] 		course:esslli2018:schedule [2021/08/08 13:22] (current)
schtepf [Distributional Semantics – A Practical Introduction (ESSLLI 2016 & 2018)]
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 [[course:bibliography|Bibliography]] [[course:bibliography|Bibliography]]
  
 +<!--
 {{:icon_star.png?24 }} {{:icon_star.png?24 }}
-  * small corrections to part 1 slides \\ +  * extended version of part 2 practice: //input formats// (26.05.2019) 
-  * final version of part 2 slides + R code + practice+-->
 ===== Schedule & handouts ===== ===== Schedule & handouts =====
  
 === Day 1: Introduction === === Day 1: Introduction ===
  
-{{:course:esslli2018:dsm_tutorial_part1.slides.pdf|Presentation slides}} (PDF, 0.9MiB) – {{:course:esslli2018:dsm_tutorial_part1.handout.pdf|handout}} (PDF, 1.0 MiB) – {{:course:esslli2018:part1_examples.R|R code}}+{{:course:esslli2018:dsm_tutorial_part1.slides.pdf|Presentation slides}} (PDF, 1.1 MB) – {{:course:esslli2018:dsm_tutorial_part1.handout.pdf|handout}} (PDF, 0.9 MB) – {{:course:esslli2018:part1_examples.R|R code}}
  
   * motivation and brief history of distributional semantics   * motivation and brief history of distributional semantics
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 === Day 2: The parameters of a DSM === === Day 2: The parameters of a DSM ===
  
-{{:course:esslli2018:dsm_tutorial_part2.slides.pdf|Presentation slides}} (PDF, 1.0MiB) – {{:course:esslli2018:dsm_tutorial_part2.handout.pdf|handout}} (PDF, 1.2 MiB)+{{:course:esslli2018:dsm_tutorial_part2.slides.pdf|Presentation slides}} (PDF, 1.3 MB) – {{:course:esslli2018:dsm_tutorial_part2.handout.pdf|handout}} (PDF, 1.0 MB) – {{:course:esslli2018:part2_examples.R|R code}} – {{:course:esslli2018:part2_input_formats.R|practice: input formats}} – {{:course:esslli2018:part2_exercise.R|exercise (DSM parameters)}} 
  
   * taxonomy of DSM parameters: context representation, feature scaling, normalization and standardization, distance/similarity measures, dimensionality reduction   * taxonomy of DSM parameters: context representation, feature scaling, normalization and standardization, distance/similarity measures, dimensionality reduction
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 === Day 3: Applications and evaluation === === Day 3: Applications and evaluation ===
 +
 +{{:course:esslli2018:dsm_tutorial_part3.slides.pdf|Presentation slides}} (PDF, 2.0 MB) – {{:course:esslli2018:dsm_tutorial_part3.handout.pdf|handout}} (PDF, 1.8 MB) – {{:course:esslli2018:part3_examples.R|R code}} – {{:course:esslli2018:part3_exercise.R|exercise (evaluation)}}
  
   * attributional and relational similarity, clustering and semantic categorization, multiple-choice tasks   * attributional and relational similarity, clustering and semantic categorization, multiple-choice tasks
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 === Day 4: Elements of matrix algebra === === Day 4: Elements of matrix algebra ===
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 +{{:course:esslli2018:dsm_tutorial_part4.slides.pdf|Presentation slides}} (PDF, 0.7 MB) – {{:course:esslli2018:dsm_tutorial_part4.handout.pdf|handout}} (PDF, 0.6 MB) – {{:course:esslli2018:part4_examples.R|R code}} – {{:course:esslli2018:schuetze1998.R|bonus practice: Schütze-style WSD}} – {{:course:esslli2018:part4_exercise.R|exercise (roll your own DSM)}}
  
   * basic matrix and vector operations, orthogonal projection & dimensionality reduction   * basic matrix and vector operations, orthogonal projection & dimensionality reduction

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