Python implementation for Multimodal Eigenwords, which extends Eigenwords for multimodal word embedding.
Tested on CentOS7 with the following environments:
- Anaconda3
- numpy >= 1.15.4
- scipy >= 1.1.0
- scikit-learn >= 0.20.1
- h5py >= 2.9.0
- more-itertools >= 4.3.0
- tqdm >= 4.30.0
- dask >= 1.1.1
- gensim >= 3.5.0
- imageio >= 2.4.1
- pybind11 >= 2.2.4
- openbals (suppose it's installed using
conda) - g++ >= 4.8.5
See the demo on mmeigenwords_demo.ipynb. Before you run scripts on the notebook, you need to conduct the following steps.
# compile cpp source
cd src/
make
cd ../data
# download input files (corpus, image features, etc.)
./download_inputs.sh
# download images
# Note that this may take some time, and that some images may have been removed from flickr
./download_images.sh@InProceedings{W17-2405,
author = "Fukui, Kazuki and Oshikiri, Takamasa and Shimodaira, Hidetoshi",
title = "Spectral Graph-Based Method of Multimodal Word Embedding",
booktitle = "Proceedings of TextGraphs-11: the Workshop on Graph-based Methods for Natural Language Processing",
year = "2017",
publisher = "Association for Computational Linguistics",
pages = "39--44",
location = "Vancouver, Canada",
doi = "10.18653/v1/W17-2405",
url = "http://aclweb.org/anthology/W17-2405"
}