Abstract
How do we surface the large amount of information present in HTML documents on the Web, from news articles to Rotten Tomatoes pages to tables of sports scores? Such information can enable a variety of applications including knowledge base construction, question answering, recommendation, and more. In this tutorial, we present approaches for information extraction (IE) from Web data that can be differentiated along two key dimensions: 1) the diversity in data modality that is leveraged, e.g. text, visual, XML/HTML, and 2) the thrust to develop scalable approaches with zero to limited human supervision.
Author supplied keywords
Cite
CITATION STYLE
Dong, X. L., Hajishirzi, H., Lockard, C., & Shiralkar, P. (2020). Multi-modal Information Extraction from Text, Semi-structured, and Tabular Data on the Web. In Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (pp. 3543–3544). Association for Computing Machinery. https://doi.org/10.1145/3394486.3406468
Register to see more suggestions
Mendeley helps you to discover research relevant for your work.
