@inproceedings{2510ced95fc940cfb561560becec6603,
title = "OpBerg: Discovering Causal Sentences Using Optimal Alignments",
abstract = "The biological literature is rich with sentences that describe causal relations. Methods that automatically extract such sentences can help biologists to synthesize the literature and even discover latent relations that had not been articulated explicitly. Current methods for extracting causal sentences are based on either machine learning or a predefined database of causal terms. Machine learning approaches require a large set of labeled training data and can be susceptible to noise. Methods based on predefined databases are limited by the quality of their curation and are unable to capture new concepts or mistakes in the input. We address these challenges by adapting and improving a method designed for a seemingly unrelated problem: finding alignments between genomic sequences. This paper presents a novel method for extracting causal relations from text by aligning the part-of-speech representations of an input set with that of known causal sentences. Our experiments show that when applied to the task of finding causal sentences in biological literature, our method improves on the accuracy of other methods in a computationally efficient manner.",
keywords = "Causality extraction, Sequence alignments, Zero-shot learning",
author = "Justin Wood and Nicholas Matiasz and Alcino Silva and William Hsu and Alexej Abyzov and Wei Wang",
note = "Publisher Copyright: {\textcopyright} 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.; 24th International Conference on Big Data Analytics and Knowledge Discovery, DaWaK 2022 ; Conference date: 22-08-2022 Through 24-08-2022",
year = "2022",
doi = "10.1007/978-3-031-12670-3_2",
language = "English (US)",
isbn = "9783031126697",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "17--30",
editor = "Robert Wrembel and Johann Gamper and Gabriele Kotsis and Ismail Khalil and Tjoa, {A Min}",
booktitle = "Big Data Analytics and Knowledge Discovery - 24th International Conference, DaWaK 2022, Proceedings",
}