imi_mug support code and resources from our participation at the TREC 2017 Precision Medicine Track
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Updated
Jun 12, 2019 - Java
imi_mug support code and resources from our participation at the TREC 2017 Precision Medicine Track
Trec Evaluation of ranked documents retrieved by searching on ElasticSearch Index
Advanced IR Experiments with SBERT, Elasticsearch and trec_eval
Recommendation-oriented version of trec_eval with more metrics
The goal of this project is to implement various IR models, evaluate the IR system and improve the search result based on our understanding of the models, the implementation and the evaluation.
Support code and resources for participation at the TREC Precision Medicine Track (TREC-PM)
Information Retrieval Kit - Utilities for IR in python
imi_mug support code and resources from our participation at the TREC 2017 Precision Medicine Track
Microblog information retrieval system. Implementing an Information Retrieval (IR) system based on a collection of documents (Twitter messages).
The projects are a part of the course CSE-535: Information Retrieval, that I had taken up for Fall 2022 at the University at Buffalo.
Saas tool for developing and testing solutions for TREC PM. Includes built in trec_eval, Elasticsearch and Terrier
Search Engine based on an inverted index developed by Stefano Bianchettin, Matteo Mugnai and Filippo Puccini for Multimedia Information Retrieval course at University of Pisa during academic year 2022/2023.
A multi-phase Information Retrieval system built for IR2025, exploring query expansion techniques using BM25, WordNet, and Word2Vec. Includes full evaluation using TREC metrics (MAP, avgPre@k) and implemented in Python with Elasticsearch, Gensim, and NLTK.
The projects are a part of the course CSE-535: Information Retrieval, that I had taken up for Fall 2019 at the University at Buffalo.
Search engine that queries for information to find the best results based on custom analysers and indexing techniques.
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