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https://github.com/raduionescu/vlawe-boswe
Code for VLAWE [Ionescu et al., NAACL 2019] and BOSWE [Butnaru et al., KES 2017] representations.
https://github.com/raduionescu/vlawe-boswe
Last synced: 3 months ago
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Code for VLAWE [Ionescu et al., NAACL 2019] and BOSWE [Butnaru et al., KES 2017] representations.
- Host: GitHub
- URL: https://github.com/raduionescu/vlawe-boswe
- Owner: raduionescu
- License: gpl-3.0
- Created: 2019-04-29T12:13:19.000Z (over 5 years ago)
- Default Branch: master
- Last Pushed: 2019-04-29T22:10:56.000Z (over 5 years ago)
- Last Synced: 2024-05-18T17:53:28.299Z (6 months ago)
- Language: MATLAB
- Size: 3.03 MB
- Stars: 10
- Watchers: 3
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: COPYING.TXT
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README
# Code for VLAWE and BOSWE
Code for computing VLAWE [Ionescu et al., NAACL 2019] and BOSWE [Butnaru et al., KES 2017] representations.
### 1. License agreement
Copyright (C) 2019 Radu Tudor Ionescu, Andrei M. Butnaru
This package contains free software: you can redistribute it and/or modify it under
the terms of the GNU General Public License as published by the Free Software
Foundation, either version 3 of the License, or any later version.
This program is distributed in the hope that it will be useful, but WITHOUT ANY
WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A
PARTICULAR PURPOSE. See the GNU General Public License for more details.
You should have received a copy of the GNU General Public License along with this
program (see COPYING.txt package file). If not, see .
### 2. Citation
Please cite the corresponding works [1,2] if you use this software (or a modified version of it) in any scientific
work:
[1] Radu Tudor Ionescu, Andrei M. Butnaru. Vector of Locally-Aggregated Word Embeddings (VLAWE): A Novel Document-level Representation. In Proceedings of NAACL, 2019.
[2] Andrei M. Butnaru, Radu Tudor Ionescu. From Image to Text Classification: A Novel Approach based on Clustering Word Embeddings. In Proceedings of KES, 2017.
Bibtex:
```
@inproceedings{ Ionescu-NAACL-2019,
author = {{Radu Tudor} Ionescu and Andrei Butnaru},
title = "{Vector of Locally-Aggregated Word Embeddings (VLAWE): A Novel Document-level Representation}",
booktitle = {Proceedings of NAACL},
year = {2019},
}
@inproceedings{ Butnaru-KES-2017,
author = {Andrei Butnaru and {Radu Tudor} Ionescu},
title = "{From Image to Text Classification: A Novel Approach based on Clustering Word Embeddings}",
booktitle = {Proceedings of KES},
year = {2017},
pages = {1784--1793},
}
```
### 3. Usage
This MATLAB code can be used to reproduce the results from the works [1,2] from above. Before running the code, you need to install the following dependencies:
- VLFeat: http://www.vlfeat.org (place the library in the "code/vlfeat" subfolder)
- PQ Kernel: http://pq-kernel.herokuapp.com (place files directly in the "code" subfolder)
- LibSVM: https://www.csie.ntu.edu.tw/~cjlin/libsvm/ (after installation, add the corresponding path so that the functions ```svmtrain``` and ```svmpredict``` become available from everywhere in MATLAB)
- GloVe: https://nlp.stanford.edu/projects/glove/ (can be installed and used independently)
After installing the above frameworks, proceed as following:
1. Extract the GloVe word vectors from each text document and save the results in the "code/data" subfolder. The output for each text document should be written in a different .txt file. The output file should contain comma separated values with one word vector per line.
2. Run the following script in MATLAB:
```
>> runAll
```
### 4. Feedback and suggestions
Send an e-mail to: raducu[dot]ionescu{at}gmail[dot].com