Modest doubt: enabling discovery across maritime heritage records.

Jack Pink, Shrikriti Singh, Adriane Chapman, Fraser Sturt
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引用次数: 0

Abstract

The United Kingdom's Maritime Heritage records hold vital information on heritage assets and archaeological contexts key to addressing current research priorities. These records stand alone, rarely connecting, demanding an arduous and time-consuming process of investigation and cross-referencing for synthesis to occur. Challenges intensify due to the qualities of this data; they stem partly from legacy information not initially intended for heritage recording purposes. Complications also arise from the varied methods of recording, storing, and disseminating this information deployed over time. However, archaeologists now possess Named Entity Recognition (NER) and Natural Language Processing (NLP) tools with the potential to organize and search such fragmented databases. This paper explores a method to enhance and enrich these datasets by employing Few Shot learning techniques to perform Multiclass Text Classification. The Welsh National Monuments Record (NMR), a glimpse into the U.K.'s maritime heritage, has been utilized to test these approaches.

适度怀疑:通过海洋遗产记录进行发现。
英国的海洋遗产记录保存着关于遗产资产和考古背景的重要信息,这些信息对解决当前的研究重点至关重要。这些记录是独立的,很少有联系,需要一个艰巨而耗时的调查和交叉参考过程才能进行综合。由于这些数据的质量,挑战加剧;它们部分源于遗产信息,最初并非用于遗产记录目的。随着时间的推移,记录、存储和传播这些信息的各种方法也会产生复杂性。然而,考古学家现在拥有命名实体识别(NER)和自然语言处理(NLP)工具,它们有可能组织和搜索这些碎片化的数据库。本文探索了一种利用Few Shot学习技术进行多类文本分类的方法,以增强和丰富这些数据集。威尔士国家古迹记录(NMR),一瞥英国的海洋遗产,已被用来测试这些方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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