A search engine that ranks documents by relevance to a query using a weighting scheme, tokenization, stop word removal, and stemming
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Updated
Jan 18, 2024 - Python
A search engine that ranks documents by relevance to a query using a weighting scheme, tokenization, stop word removal, and stemming
Assignment Submission for course Information Retrieval (CS F469)
IR implemented by using TF-IDF method
TinyBERT-based bi-encoder, cross-encoder, and poly-encoder trained on MS MACRO for passage re-ranking
Probabilistic Reasoning and Bayes Rule; Text Data Analysis; Document Ranking and Evaluation.
Galago related homeworks of Information Retrieval Course
Implement the Pivoted Normalization and BM25 Retrieval Functions
An information retrieval system for document ranking. Implementation and evaluation of Okapi BM25, Cosine Similarity, and Language Models for document ranking and retrieval. Includes precision-recall evaluation metrics and a detailed project report.
Scikit-learn implementation of co-occurrence word graph based semantic query search using machine learning and vector space similarity measures.
This repo contains mini projects in Information Retrieval. Covers indexing, document ranking, web crawling, page ranking, and evaluating different models
🔝 HW1 of Intelligent Information Retrieval MSc Course ECE@UT
😷 Attempt on deep learning track challenge in TREC 2019 - https://microsoft.github.io/TREC-2019-Deep-Learning/
ir_explain: a Python Library of Explainable IR Methods
EE448 Big Data Mining Project: Query Expansion with Rocchio Algorithm & Document Ranking with BM25 Score
Fine-Grained Relevance Annotations for Multi-Task Document Ranking and Question Answering
Pytorch implementation of CACM (WSDM'20)
The Tensorflow implementation of accepted ACL 2018 paper "A deep relevance model for zero-shot document filtering", Chenliang Li, Wei Zhou, Feng Ji, Yu Duan, Haiqing Chen, http://aclweb.org/anthology/P18-1214
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