https://github.com/julian-risch/JCDL2018

Code for our JCDL 2018 Paper on Entropy-Based Topic Modeling
https://github.com/julian-risch/JCDL2018

Last synced: about 1 year ago
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Code for our JCDL 2018 Paper on Entropy-Based Topic Modeling

• Host: GitHub
• URL: https://github.com/julian-risch/JCDL2018
• Owner: julian-risch
• Created: 2020-03-24T23:10:09.000Z (about 6 years ago)
• Default Branch: master
• Last Pushed: 2020-09-25T18:42:48.000Z (over 5 years ago)
• Last Synced: 2025-04-03T11:47:00.924Z (about 1 year ago)
• Language: Java
• Homepage:
• Size: 946 KB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

Awesome Lists containing this project

• awesome-topic-models - Entropy-Based Topic Modeling - Java implementation of Entropy-Based Topic Modeling on Multiple Domain-Specific Text Collections (Models / Miscellaneous topic models)

README

          
# JCDL2018

Here, we publish source code of our entropy-based cross-collection topic model. This code is a reference implementation of our paper our paper [**My Approach = Your Apparatus? Entropy-Based Topic Modeling on Multiple Domain-Specific Text Collections**](https://hpi.de/fileadmin/user_upload/fachgebiete/naumann/people/risch/risch2018entropy.pdf) at the ACM/IEEE Joint Conference on Digital Libraries 2018.

## Citation

If you use our work, please cite our paper as follows:

    @inproceedings{risch2018approach,

    author = {Risch, Julian and Krestel, Ralf},

    booktitle = {Proceedings of the Joint Conference on Digital Libraries (JCDL)},

    pages = {283-292},

    title = {My Approach = Your Apparatus? Entropy-Based Topic Modeling on Multiple Domain-Specific Text Collections},

    year = {2018}

    }

Please also note our earlier short paper [**What Should I Cite? Cross-Collection Reference Recommendation of Patents and Papers**](https://hpi.de/fileadmin/user_upload/fachgebiete/naumann/people/risch/risch2017what.pdf) on a related topic published at the International Conference on Theory and Practice of Digital Libraries (TDPL).

## Implementation

* `TopicModelCcLDA.java` implements entity-based cross-collection latent Dirichlet allocation

* `RunTopicModel.java` starts the training of the topic model and the following evalution

* `CorpusBlogPostsFromFile.java` loads a corpus from a file.

* `CorpusToy.java` loads a small example corpus of a few documents defined in the code.