Exploring Relevance Judgement Inspired by Quantum Weak Measurement

Tianshu Wang, Yuexian Hou, Panpan Wang, Xiaolei Niu

AAAI 2018 pp. 8171-8172

doi:10.1609/AAAI.V32I1.12167 /aaai/2018/wang2018aaai-exploring/

Abstract

Quantum Theory (QT) has been applied in a number of fields outside physics, e.g. Information Retrieval (IR). A series of pioneering works have verified the necessity to employ QT in IR user models. In this paper, we explore the process of relevance judgement from a novel perspective of the two state vector quantum weak measurement (WM) by considering context information in time domain. Experiments are carried out to verify our arguments.

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Cite

Text

Wang et al. "Exploring Relevance Judgement Inspired by Quantum Weak Measurement." AAAI Conference on Artificial Intelligence, 2018. doi:10.1609/AAAI.V32I1.12167

Markdown

[Wang et al. "Exploring Relevance Judgement Inspired by Quantum Weak Measurement." AAAI Conference on Artificial Intelligence, 2018.](https://mlanthology.org/aaai/2018/wang2018aaai-exploring/) doi:10.1609/AAAI.V32I1.12167

BibTeX

@inproceedings{wang2018aaai-exploring,
  title     = {{Exploring Relevance Judgement Inspired by Quantum Weak Measurement}},
  author    = {Wang, Tianshu and Hou, Yuexian and Wang, Panpan and Niu, Xiaolei},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {2018},
  pages     = {8171-8172},
  doi       = {10.1609/AAAI.V32I1.12167},
  url       = {https://mlanthology.org/aaai/2018/wang2018aaai-exploring/}
}