lblb23 / machine-learning-ontology-matching

Applying of Machine Learning Techniques to Combine String-based, Language-based and Structure-based Similarity Measures for Ontology Matching

Ontology Matching with Machine Learning

Applying of Machine Learning Techniques to Combine String-based, Language-based and Structure-based Similarity Measures for Ontology Matching [Paper]

Getting Started

1. Download Word2Vec model and unzip to root folder.
2. Install requirements.
3. Select dataset and machine learning algorithm in config.yml.
4. Create dataset:

python3 create_dataset.py

5. Calculate features:

python3 calculate_features.py

6. Train and evaluate model:

python3 train_evaluate.py

Main requirements

• ngram
• fuzzycomp
• py_stringmatching
• gensim
• nltk
• owlready2

Instal fuzzycomp for python3

1. Clone repo

git clone https://github.com/fuzzycode/fuzzycomp

2. From fuzzycomp/fuzzycomp/fuzzycomp.py delete this line

from exceptions import IndexError, ValueError

3. Install the package

python3 setup.py install