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Online appendix for the SIGIR 2021 short paper titled "Entity Ranking Using Fine-Grained Entity Aspects".

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Entity Retrieval Using Fine-Grained Entity Aspects

Shubham Chatterjee and Laura Dietz. 2021. Entity Retrieval Using Fine-Grained Entity Aspects. In Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR ’21).

This repository contains code associated with this paper and the instructions on how to execute the code. For detailed instructions on how to run the code, read the documentation.

Shield: CC BY-SA 4.0

All data associated with this work is licensed and released under a Creative Commons Attribution-ShareAlike 4.0 International License.

CC BY-SA 4.0

Acknowledgement

This material is based upon work supported by the National Science Foundation under Grant No. 1846017. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.

Cite

@inproceedings{chatterjee2021entity,
  author = {Chatterjee, Shubham and Dietz, Laura},
  title = {Entity Retrieval Using Fine-Grained Entity Aspects},
  year = {2021},
  publisher = {Association for Computing Machinery},
  address = {New York, NY, USA},
  url = {https://doi.org/10.1145/3404835.3463035},
  doi = {10.1145/3404835.3463035},
  booktitle = {Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval},
  numpages = {5},
  location = {Virtual Event, Canada},
  series = {SIGIR '21}
}

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If you have any questions, please contact Shubham Chatterjee at [email protected] or [email protected].

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Online appendix for the SIGIR 2021 short paper titled "Entity Ranking Using Fine-Grained Entity Aspects".

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