Metadata-Version: 2.1
Name: efficient-first-stage-retrieval
Version: 0.0.36
Summary: Master Thesis with the L3S at Lebniz University Hannover
Home-page: https://github.com/real-tesco/efficient_first_stage_retrieval/tree/master/
Author: Jesco Brandt
Author-email: luca-brandt@web.de
License: Apache Software License 2.0
Description: # Efficient First Stage Retrieval using Dense Representations and KNN
        > Summary description here.
        
        
        This file will become your README and also the index of your documentation.
        > test
        
        ## Install
        
        `pip install efficient_first_stage_retrieval`
        
        ## How to use
        
        Use calculate_score to calculate MAP and MRR from actual qrels in fn_qrels and from predictions in prediction
        
        ```python
        calculate_score(fn_qrels='data/robust/qrels.robust2004.txt', prediction="score.txt")
        ```
        
        Use do_run to calculate predictions from 'searcher' and queries 'topic' and used time and store it in file and 'time-' + file
        
        ```python
        do_run(file, topics, searcher)
        ```
        
Keywords: efficient first stage retrieval information
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Requires-Python: >=3.6
Description-Content-Type: text/markdown
