Autonomously Computable Information Extraction-Reference-Cited by-同舟云学术

Autonomously Computable Information Extraction

Published:2023-06 Issue:10 Volume:16 Page:2431-2443
ISSN:2150-8097
Container-title:Proceedings of the VLDB Endowment
language:en
Short-container-title:Proc. VLDB Endow.

Author:

Kassaie Besat¹,Tompa Frank Wm.¹

Affiliation:

1. Cheriton School of Computer Science, University of Waterloo, Waterloo, ON, Canada

Abstract

Most optimization techniques deployed in information extraction systems assume that source documents are static. Instead, extracted relations can be considered to be materialized views defined by a language built on regular expressions. Using this perspective, we can provide an efficient verifier (using static analysis) that can be used to avoid the high cost of re-extracting information after an update. In particular, we propose an efficient mechanism to identify updates for which we can autonomously compute an extracted relation. We present experimental results that support the feasibility and practicality of this mechanism in real world extraction systems.

Publisher

Association for Computing Machinery (ACM)

Subject

General Earth and Planetary Sciences,Water Science and Technology,Geography, Planning and Development

Link

https://dl.acm.org/doi/pdf/10.14778/3603581.3603585

Reference32 articles.

1. Maintaining knowledge about temporal intervals

2. Antoine Amarilli , Pierre Bourhis , Stefan Mengel , and Matthias Niewerth . 2019 . Constant-Delay Enumeration for Nondeterministic Document Spanners . In Proc. 22nd International Conference on Database Theory, ICDT (LIPIcs), Pablo Barceló and Marco Calautti (Eds.) , Vol. 127 . Schloss Dagstuhl - Leibniz-Zentrum für Informatik, Lisbon, 22:1--22:19. Antoine Amarilli, Pierre Bourhis, Stefan Mengel, and Matthias Niewerth. 2019. Constant-Delay Enumeration for Nondeterministic Document Spanners. In Proc. 22nd International Conference on Database Theory, ICDT (LIPIcs), Pablo Barceló and Marco Calautti (Eds.), Vol. 127. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, Lisbon, 22:1--22:19.

3. Updating derived relations: detecting irrelevant and autonomously computable updates

4. Efficiently updating materialized views

5. Amit Chandel , P. C. Nagesh , and Sunita Sarawagi . 2006 . Efficient Batch Top-k Search for Dictionary-based Entity Recognition . In Proc. 22nd International Conference on Data Engineering, ICDE, Ling Liu, Andreas Reuter, Kyu-Young Whang, and Jianjun Zhang (Eds.). IEEE Computer Society, Atlanta, 28:1--28:10 . Amit Chandel, P. C. Nagesh, and Sunita Sarawagi. 2006. Efficient Batch Top-k Search for Dictionary-based Entity Recognition. In Proc. 22nd International Conference on Data Engineering, ICDE, Ling Liu, Andreas Reuter, Kyu-Young Whang, and Jianjun Zhang (Eds.). IEEE Computer Society, Atlanta, 28:1--28:10.