Cited By
View all- O’Riordan LDoyle MBaruffa FKannan V(2020)A hybrid classical-quantum workflow for natural language processingMachine Learning: Science and Technology10.1088/2632-2153/abbd2e2:1(015011)Online publication date: 8-Dec-2020
Dynamic Content Monitoring and Exploration using Vector Spaces
Author: 
Benyou WangAuthors Info & Claims
Page 1444
Abstract
This doctoral research project investigates using Quantum Theory (QT) to represent language, especially in some dynamic scenarios, e.g. when dealing with dynamic corpora or interactive tasks. The author plans to propose a quantum state driven framework for language problems and generalize it in a high-dimensional tensor space. Dynamics will be modeled by the formalism thereof of quantum evolution governing the update of quantum states. The author argues that this proposal will pave the way towards a new paradigm which may provide some novel insights about how to represent the language and its evolution in dynamic scenarios.
References
[1]
Peter D Bruza, Kirsty Kitto, Douglas McEvoy, and Cathy McEvoy. 2008. Entangling words and meaning. (2008).
[2]
Qiuchi Li, Sagar Uprety, Benyou Wang, and Dawei Song. 2018. Quantum-inspired complex word embedding. arXiv preprint arXiv:1805.11351 (2018).
[3]
Qiuchi Li, Benyou Wang, and Massimo Melucci. 2019. CNM: An Interpretable Complex-valued Network for Matching. arXiv preprint arXiv:1904.05298 (2019).
[4]
Zachary C Lipton. 2016. The mythos of model interpretability. arXiv:1606.03490 (2016).
[5]
Massimo Melucci. 2015. Introduction to information retrieval and quantum mechanics. Vol. 35. Springer.
[6]
Cornelis Joost Van Rijsbergen. 2004. The geometry of information retrieval .Cambridge University Press.
[7]
Benyou Wang, Qiuchi Li, Massimo Melucci, and Dawei Song. 2019. Semantic Hilbert Space for Text Representation Learning. arXiv preprint arXiv:1902.09802 (2019).
[8]
Benyou Wang, Peng Zhang, Jingfei Li, Dawei Song, Yuexian Hou, and Zhenguo Shang. 2016. Exploration of quantum interference in document relevance judgement discrepancy. Entropy, Vol. 18, 4 (2016), 144.
[9]
Peng Zhang, Jiabin Niu, Zhan Su, Benyou Wang, Liqun Ma, and Dawei Song. 2018a. End-to-End Quantum-like Language Models with Application to Question Answering . AAAI. (2018), 5666--5673.
[10]
Peng Zhang, Zhan Su, Lipeng Zhang, Benyou Wang, and Dawei Song. 2018b. A Quantum Many-body Wave Function Inspired Language Modeling Approach. In CIKM. ACM, 1303--1312.
Index Terms
- Dynamic Content Monitoring and Exploration using Vector Spaces
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Please enable JavaScript to view thecomments powered by Disqus.Information & Contributors
Information
Published In
July 2019
1512 pages
ISBN:9781450361729
DOI:10.1145/3331184
- General Chairs:
- Benjamin Piwowarski,
- Max Chevalier,
- Eric Gaussier,
- Program Chairs:
- Yoelle Maarek,
- Jian-Yun Nie,
- Falk Scholer
Copyright © 2019 Owner/Author.
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.
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Association for Computing Machinery
New York, NY, United States
Publication History
Published: 18 July 2019
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Funding Sources
- European Unions Hori-zon 2020 research and innovation programme
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SIGIR '19
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SIGIR '19: The 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval
July 21 - 25, 2019
Paris, France
Acceptance Rates
SIGIR'19 Paper Acceptance Rate 84 of 426 submissions, 20%;
Overall Acceptance Rate 792 of 3,983 submissions, 20%
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View all- O’Riordan LDoyle MBaruffa FKannan V(2020)A hybrid classical-quantum workflow for natural language processingMachine Learning: Science and Technology10.1088/2632-2153/abbd2e2:1(015011)Online publication date: 8-Dec-2020
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