This is the code repository for the query adaptive ontology based information retrieval model combining multiple ontologies in bioinformatics in different ways depending on the query context
Description: As multiple existing ontologies in the biomedical field often contain complementary information, it is crucial to combine them effectively during the search. We propose a deep learnign algorithm to learn factors based on local and global context of a query to utilize ontologies with different weights that are adapative based on the query. Report
Code : Code for data cleaning, data processing and learning weights/factors called "Expansion factor" and "Ontology factor".
expansion_model_revised : deep-learning method for learning one of the adaptive weights.
BM25 results : search ranking results with the BM25 and BM25 + query adaptive ontology guided results.
LC_related_data : word vocabulary, some of the data statistics
By using this source code you agree to the license described in https://github.com/sahitilucky/Query-adaptive-ontology-guided-information-retrieval-for-biomedical-search/blob/master/LICENSE