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metadata language: German

Data from the Paper: Entities as Topic Labels - Combining Entity Linking and Labeled LDA to Improve Topic Interpretability and Evaluability.

Version
1
Resource Type
Dataset
Creator
  • Lauscher, Anne
  • Nanni, Federico
  • Ruiz Fabo, Pablo
  • Ponzetto, Simone Paolo
Publication Date
2016
Description
  • Abstract

Data and File Information
  • Unit Type: Other
    Number of Units: 1
    • File Name: readme.txt
      File Format: text/plain
      File Size: 910
      Data Fingerprint: 269c7da1d042754c8b30daec7b4910da
      Method Fingerprint: MD5
  • Unit Type: Other
    Number of Units: 1
    • File Name: europarl.sql
      File Format: text/plain
      File Size: 89576396
      Data Fingerprint: b8924ff93a0f028b9a627610c994724a
      Method Fingerprint: MD5
  • Unit Type: Other
    Number of Units: 1
    • File Name: enron.sql
      File Format: text/plain
      File Size: 34426093
      Data Fingerprint: 5cdc52bf306f5784bc3ba52ce632c392
      Method Fingerprint: MD5
  • Unit Type: Other
    Number of Units: 1
    • File Name: clinton.sql
      File Format: text/plain
      File Size: 50488196
      Data Fingerprint: bca10a2275f55ee8290342344b2116e5
      Method Fingerprint: MD5
Availability
Unknown

Update Metadata: 2019-01-15 | Issue Number: 2 | Registration Date: 2019-01-15

Lauscher, Anne; Nanni, Federico; Ruiz Fabo, Pablo; Ponzetto, Simone Paolo (2016): Data from the Paper: Entities as Topic Labels - Combining Entity Linking and Labeled LDA to Improve Topic Interpretability and Evaluability.. Version: 1. Universitätsbibliothek Mannheim. Dataset. https://doi.org/10.7801/238