Word Vector Feature Creation

This library creates word vector features for natural language processing projects. It does this using cosine similarity using across the most common words found using the word count calculation function.

While this library is meant to work with the NLP parse library and machine learning library much like the general NLP feature creation library, it doesn't need to. However, it has a dependency on the NLP parse library.

Obtaining

In your project.clj file, add:

Documentation

API documentation.

Usage

Use the similarity-features to create the features used in the model. Again, this piggybacks on the word count calculation, which has to be calculated on two pass cross validation. For example:

(:require [zensols.nlparse.parse :as p]
          [zensols.nlparse.feature.word-count :as wc]
          [zensols.nlparse.feature.word-similarity :as ws])

(defn create-features
  ([panon]
   (create-features panon nil))
  ([panon context]
   (let [{:keys [word-count-stats]} context
         tokens (p/tokens panon)]
     (binding [wc/*word-count-config* wc-config]
       (merge (if word-count-stats
                (wc/label-count-score-features panon word-count-stats))
              (if word-count-stats
                (ws/similarity-features tokens word-count-stats)))))))

See the unit test case.

Building

To build from source, do the folling:

• Install Leiningen (this is just a script)
• Install GNU make
• Install Git
• Download the source: git clone --recurse-submodules https://github.com/plandes/clj-nlp-wordvec && cd clj-nlp-wordvec
• Build the software: make jar
• Build the distribution binaries: make dist

Note that you can also build a single jar file with all the dependencies with: make uber

Citation

If you use this software in your research, please cite with the following BibTeX:

@misc{plandes-clj-nlp-wordvec,
  author = {Paul Landes},
  title = {Word Vector Feature Creation},
  year = {2018},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/plandes/clj-nlp-wordvec}}
}

References

See the general NLP feature creationlibrary for additional references.

@misc{deeplearning4j,
  author = {Eclipse Deeplearning4j Development Team},
  title = {Deeplearning4j: Open-source distributed deep learning for the JVM},
  year = {2018},
  publisher = {Apache Software Foundation License 2.0},
  journal = {GitHub repository},
  howpublished = {\url{https://deeplearning4j.org/}}
}

Changelog

An extensive changelog is available here.

License

Copyright 2018 Paul Landes

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.