====== Courses and Tutorials on DSM  ======

[[course:esslli2009:start|ESSLLI '09]] –
[[course:acl2010:start|NAACL-HLT 2010]] –
[[course:esslli2018:start|ESSLLI '16 & '18]] –
**Software & data sets** –
[[course:bibliography|Bibliography]]


===== Software for the course =====

Practical examples and exercises for these courses and tutorials are based on the user-friendly software package [[http://wordspace.r-forge.r-project.org/|wordspace]] for the interactive statistical computing environment [[http://www.r-project.org/|R]].  If you want to follow along, please bring your own laptop and set up the required software as follows:

  - Install up-to-date versions of [[https://cran.r-project.org/banner.shtml|R]] and the [[https://www.rstudio.com/products/rstudio/download/#download|RStudio]] GUI
  - Use the installer built into RStudio (or the standard R GUI) to install the following packages from the CRAN archive: 
    * ''sparsesvd'' (v0.2)
    * ''wordspace'' (v0.2-5)
    * optional: ''tm'', ''quanteda'', ''Rtsne'', ''uwot'', ''wordcloud'', ''shiny'', ''corpustools'', ''spacyr'', ''udpipe'' (don't worry if some of these fail to install)
  - During the course, you will be asked to install a further package with additional evaluation tasks (''wordspaceEval'') from a password-protected Web page:
    * ''wordspaceEval'' v0.1: [[http://www.collocations.de/data/protected/wordspaceEval_0.1.tar.gz|Source/Linux]] – [[http://www.collocations.de/data/protected/wordspaceEval_0.1.tgz|MacOS]] – [[http://www.collocations.de/data/protected/wordspaceEval_0.1.zip|Windows]] (login required)
    * download a suitable version and select “Install from: Package Archive File” in RStudio
  - Download the sample data files listed below
  - Download one or more of the pre-compiled DSMs listed below

/* -- doesn't apply at the moment -- 
==== Getting the latest & greatest ====

During the course, you may be asked to install a new version of ''wordspace'' that hasn't been submitted to CRAN yet.  In this case, please follow these instructions:

  - Use the installer built into RStudio (or the standard R GUI) to install the following packages from the CRAN archive: 
    * ''sparsesvd''
    * ''iotools''
    * ''Rcpp'' (needed on Linux only)
  - Download an appropriate version of the package for your platform:
    * ''wordspace'' v0.2-0: [[http://wordspace.r-forge.r-project.org/downloads/wordspace_0.2-0.tar.gz|Source/Linux]] – [[http://wordspace.r-forge.r-project.org/downloads/wordspace_0.2-0.tgz|MacOS]] – [[http://wordspace.r-forge.r-project.org/downloads/wordspace_0.2-0.zip|Windows]]
  - In the RStudio installer, select “Install from: Package Archive File”

You can also check the [[http://wordspace.r-forge.r-project.org/|wordspace homepage]] for new releases and installation instructions.

*/

===== Example data sets =====

  * ''[[http://www.collocations.de/data/verb_dep.txt.gz|verb_dep.txt.gz]]'' (21.6 MB)
  * ''[[http://www.collocations.de/data/adj_noun_tokens.txt.gz|adj_noun_tokens.txt.gz]]'' (8.3 MB)
  * ''[[http://www.collocations.de/data/delta_de_termdoc.txt.gz|delta_de_termdoc.txt.gz]]'' (18.4 MB)
  * ''[[http://www.collocations.de/data/potter_l2r2.txt.gz|potter_l2r2.txt.gz]]'' (51.3 MB)
  * ''[[http://www.collocations.de/data/potter_lemmas.txt.gz|potter_lemmas.txt.gz]]'' (1.1 MB) 

===== Pre-compiled DSMs =====

Pre-compiled DSMs for use with the ''wordspace'' package for R. Each model is contained in an ''.rda'' file, which can be loaded into R with the command ''load("model.rda")'' and creates an object with the same name (''model'').

==== DSMs based on the English Wikipedia ====

These models were compiled from ''WP500'', a 200-million word subset of the Wackypedia corpus comprising the first 500 words of each article. Each model covers a vocabulary of the 50,000 most frequent content words (lemmatized) in the corpus and has at least 50,000 feature dimensions. The latent SVD dimensions are based on log-transformed sparse simple-ll scores with L2-normalization. Power scaling with Caron $P = 0$ (i.e. equalization of the latent dimensions) has been applied, but the reduced vectors are not re-normalized. 

  * dependency-filtered: ''[[http://corpora.linguistik.uni-erlangen.de/data/wordspace/WP500_DepFilter_Lemma.rda|WP500_DepFilter_Lemma.rda]]'' (31.1 MB) – 500 latent SVD dimensions: ''[[http://corpora.linguistik.uni-erlangen.de/data/wordspace/WP500_DepFilter_Lemma_svd500.rda|WP500_DepFilter_Lemma_svd500.rda]]'' (179.3 MB)
  * dependency-structured: ''[[http://corpora.linguistik.uni-erlangen.de/data/wordspace/WP500_DepStruct_Lemma.rda|WP500_DepStruct_Lemma.rda]]'' (31.6 MB) – 500 latent SVD dimensions: ''[[http://corpora.linguistik.uni-erlangen.de/data/wordspace/WP500_DepStruct_Lemma_svd500.rda|WP500_DepStruct_Lemma_svd500.rda]]'' (180.3 MB)
  * L2/R2 surface span: ''[[http://corpora.linguistik.uni-erlangen.de/data/wordspace/WP500_Win2_Lemma.rda|WP500_Win2_Lemma.rda]]'' (51.8 MB) – 500 latent SVD dimensions: ''[[http://corpora.linguistik.uni-erlangen.de/data/wordspace/WP500_Win2_Lemma_svd500.rda|WP500_Win2_Lemma_svd500.rda]]'' (177.1 MB)
  * L5/R5 surface span: ''[[http://corpora.linguistik.uni-erlangen.de/data/wordspace/WP500_Win5_Lemma.rda|WP500_Win5_Lemma.rda]]'' (103.9 MB) – 500 latent SVD dimensions: ''[[http://corpora.linguistik.uni-erlangen.de/data/wordspace/WP500_Win5_Lemma_svd500.rda|WP500_Win5_Lemma_svd500.rda]]'' (179.9 MB)
  * L30/R30 surface span: ''[[http://corpora.linguistik.uni-erlangen.de/data/wordspace/WP500_Win30_Lemma.rda|WP500_Win30_Lemma.rda]]'' (311.4 MB) – 500 latent SVD dimensions: ''[[http://corpora.linguistik.uni-erlangen.de/data/wordspace/WP500_Win30_Lemma_svd500.rda|WP500_Win30_Lemma_svd500.rda]]'' (182.8 MB)
  * term-document model: ''[[http://corpora.linguistik.uni-erlangen.de/data/wordspace/WP500_TermDoc_Lemma.rda|WP500_TermDoc_Lemma.rda]]'' (105.1 MB) – 500 latent SVD dimensions: ''[[http://corpora.linguistik.uni-erlangen.de/data/wordspace/WP500_TermDoc_Lemma_svd500.rda|WP500_TermDoc_Lemma_svd500.rda]]'' (162.5 MB)
  * type contexts (L1+R1): ''[[http://corpora.linguistik.uni-erlangen.de/data/wordspace/WP500_Ctype_L1R1_Lemma.rda|WP500_Ctype_L1R1_Lemma.rda]]'' (55.8 MB) – 500 latent SVD dimensions: ''[[http://corpora.linguistik.uni-erlangen.de/data/wordspace/WP500_Ctype_L1R1_Lemma_svd500.rda|WP500_Ctype_L1R1_Lemma_svd500.rda]]'' (157.0 MB)
  * type contexts (L2+R2): ''[[http://corpora.linguistik.uni-erlangen.de/data/wordspace/WP500_Ctype_L2R2_Lemma.rda|WP500_Ctype_L2R2_Lemma.rda]]'' (33.1 MB) – 500 latent SVD dimensions: ''[[http://corpora.linguistik.uni-erlangen.de/data/wordspace/WP500_Ctype_L2R2_Lemma_svd500.rda|WP500_Ctype_L2R2_Lemma_svd500.rda]]'' (64.3 MB)
  * type contexts (L2+R2 POS tags): ''[[http://corpora.linguistik.uni-erlangen.de/data/wordspace/WP500_Ctype_L2R2pos_Lemma.rda|WP500_Ctype_L2R2pos_Lemma.rda]]'' (56.1 MB) – 500 latent SVD dimensions: ''[[http://corpora.linguistik.uni-erlangen.de/data/wordspace/WP500_Ctype_L2R2pos_Lemma_svd500.rda|WP500_Ctype_L2R2pos_Lemma_svd500.rda]]'' (175.3 MB)
  * word forms L2/R2: ''[[http://corpora.linguistik.uni-erlangen.de/data/wordspace/WP500_Win2_Word.rda|WP500_Win2_Word.rda]]'' (63.9 MB) – 500 latent SVD dimensions: ''[[http://corpora.linguistik.uni-erlangen.de/data/wordspace/WP500_Win2_Word_svd500.rda|WP500_Win2_Word_svd500.rda]]'' (185.5 MB)
  * word forms L2/R2 with non-lemmatized features: ''[[http://corpora.linguistik.uni-erlangen.de/data/wordspace/WP500_Win2_Word_WF.rda|WP500_Win2_Word_WF.rda]]'' (68.9 MB) – 500 latent SVD dimensions: ''[[http://corpora.linguistik.uni-erlangen.de/data/wordspace/WP500_Win2_Word_WF_svd500.rda|WP500_Win2_Word_WF_svd500.rda]]'' (185.9 MB)

==== Neural word embeddings ====

Some publicly available pre-trained neural embeddings, converted into ''.rda'' format for use with the ''wordspace'' package.

  * word2vec: ''[[http://corpora.linguistik.uni-erlangen.de/data/wordspace/GoogleNews300_wf200k.rda|GoogleNews300_wf200k.rda]]'' (129.2 MiB) 

===== Web interfaces =====

  * Web interface for several pre-trained **[[http://clic.cimec.unitn.it/infomap-query/|Infomap models]]** (CIMeC, U Trento)
  * Explore **[[https://corpora.linguistik.uni-erlangen.de/shiny/wordspace/word2vec/|word2vec embeddings]]** (FAU Erlangen-Nürnberg)
  * Explore **[[https://corpora.linguistik.uni-erlangen.de/shiny/wordspace/WP500/|DSMs based on Wikipedia]]** (FAU Erlangen-Nürnberg)
