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Neural-IR-Explorer: A Content-Focused Tool to Explore Neural Re-Ranking Results [article]

Sebastian Hofstätter, Markus Zlabinger, Allan Hanbury
2019 arXiv   pre-print
We present the content-focused Neural-IR-Explorer, which empowers users to browse through retrieval results and inspect the inner workings and fine-grained results of neural re-ranking models.  ...  In this paper we look beyond metrics-based evaluation of Information Retrieval systems, to explore the reasons behind ranking results.  ...  Conclusion We presented the content-focused Neural-IR-Explorer to complement metric based evaluation of retrieval models.  ... 
arXiv:1912.04713v1 fatcat:lpa5xj3vbbcyfaew3anrm7cgza

Neural-IR-Explorer: A Content-Focused Tool to Explore Neural Re-ranking Results [chapter]

Sebastian Hofstätter, Markus Zlabinger, Allan Hanbury
2020 Lecture Notes in Computer Science  
We present the content-focused Neural-IR-Explorer, which empowers users to browse through retrieval results and inspect the inner workings and fine-grained results of neural re-ranking models.  ...  In this paper we look beyond metrics-based evaluation of Information Retrieval systems, to explore the reasons behind ranking results.  ...  In this paper we present the Neural-IR-Explorer: a system to explore the output of neural re-ranking models.  ... 
doi:10.1007/978-3-030-45442-5_58 fatcat:gcqhxe5y3vaphdj3ix5qqmmmgm