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dc.contributor.author Kosem, Iztok
dc.contributor.author Čibej, Jaka
dc.contributor.author Ljubešić, Nikola
dc.contributor.author Krek, Simon
dc.contributor.author Gantar, Polona
dc.contributor.author Arhar Holdt, Špela
dc.contributor.author Logar, Nataša
dc.contributor.author Laskowski, Cyprian
dc.contributor.author Klemenc, Bojan
dc.contributor.author Dobrovoljc, Kaja
dc.contributor.author Gorjanc, Vojko
dc.contributor.author Pori, Eva
dc.date.accessioned 2021-05-07T13:17:33Z
dc.date.available 2021-05-07T13:17:33Z
dc.date.issued 2020-10-26
dc.identifier.uri http://hdl.handle.net/11356/1425
dc.description The Orange Workflow for Observing Collocation Clusters ColEmbed 1.0 ColEmbed is a workflow (.OWS file) for Orange Data Mining (an open-source machine learning and data visualization software: https://orangedatamining.com/) that allows the user to observe clusters of collocation candidates extracted from corpora. The workflow consists of a series of data filters, embedding processors, and visualizers. As input, the workflow takes a tab-separated file (.TSV/.TAB) with data on collocations extracted from a corpus, along with their relative frequencies by year of publication and other optional values (such as information on temporal trends). The workflow allows the user to select the features which are then used in the workflow to cluster collocation candidates, along with the embeddings generated based on the selected lemmas (either one lemma or both lemmas can be selected, depending on our clustering criteria; for instance, if we wish to cluster adjective+noun candidates based on the similarities of their noun components, we only select the second lemma to be taken into account in embedding generation). The obtained embedding clusters can be visualized and further processed (e.g. by finding the closest neighbors of a reference collocation). The workflow is described in more detail in the accompanying README file. The entry also contains three .TAB files that can be used to test the workflow. The files contain collocation candidates (along with their relative frequencies per year of publication and four measures describing their temporal trends; see http://hdl.handle.net/11356/1424 for more details) extracted from the Gigafida 2.0 Corpus of Written Slovene (https://viri.cjvt.si/gigafida/) with three different syntactic structures (as defined in http://hdl.handle.net/11356/1415): 1) p0-s0 (adjective + noun, e.g. rezervni sklad), 2) s0-s2 (noun + noun in the genitive case, e.g. ukinitev lastnine), and 3) gg-s4 (verb + noun in the accusative case, e.g. pripraviti besedilo). It should be noted that only collocation candidates with absolute frequency of 15 and above were extracted. Please note that the ColEmbed workflow requires the installation of the Text Mining add-on for Orange. For installation instructions as well as a more detailed description of the different phases of the workflow and the measures used to observe the collocation trends, please consult the README file.
dc.publisher Centre for Language Resources and Technologies, University of Ljubljana
dc.rights Apache License 2.0
dc.rights.uri https://opensource.org/licenses/Apache-2.0
dc.rights.label PUB
dc.source.uri https://www.cjvt.si/kolos/
dc.subject collocations
dc.subject clustering
dc.subject word embeddings
dc.subject temporal trends
dc.title The Orange workflow for observing collocation clusters ColEmbed 1.0
dc.type toolService
metashare.ResourceInfo#ContentInfo.detailedType tool
metashare.ResourceInfo#ResourceComponentType#ToolServiceInfo.languageDependent false
has.files yes
branding CLARIN.SI data & tools
contact.person Iztok Kosem iztok.kosem@cjvt.si Centre for Language Resources and Technologies, University of Ljubljana
sponsor ARRS (Slovenian Research Agency) J6-8255 Collocations as a basis for language description: semantic and temporal perspectives nationalFunds
sponsor ARRS (Slovenian Research Agency) J6-8256 New grammar of contemporary standard Slovene: sources and methods nationalFunds
sponsor ARRS (Slovenian Research Agency) P6-0411 Language Resources and Technologies for Slovene nationalFunds
files.count 1
files.size 90517674


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