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语料库转换服务：大规模摄取文档的机器学习平台Corpus Conversion Service: A Machine Learning Platform to Ingest Documents at Scale |
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| 课程网址: | http://videolectures.net/kdd2018_staar_corpus_conversion/ |
| 主讲教师: | Peter Staar |
| 开课单位: | IBM苏黎世研究实验室 |
| 开课时间: | 2018-11-23 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | Over the past few decades, the amount of scientific articles and technical literature has increased exponentially in size. Consequently, there is a great need for systems that can ingest these documents at scale and make the contained knowledge discoverable. Unfortunately, both the format of these documents (e.g. the PDF format or bitmap images) as well as the presentation of the data (e.g. complex tables) make the extraction of qualitative and quantitive data extremely challenging. In this paper, we present a modular, cloud-based platform to ingest documents at scale. This platform, called the Corpus Conversion Service (CCS), implements a pipeline which allows users to parse and annotate documents (i.e. collect ground-truth), train machine-learning classification algorithms and ultimately convert any type of PDF or bitmap-documents to a structured content representation format. We will show that each of the modules is scalable due to an asynchronous microservice architecture and can therefore handle massive amounts of documents. Furthermore, we will show that our capability to gather groundtruth is accelerated by machine-learning algorithms by at least one order of magnitude. This allows us to both gather large amounts of ground-truth in very little time and obtain very good precision/recall metrics in the range of 99% with regard to content conversion to structured output. The CCS platform is currently deployed on IBM internal infrastructure and serving more than 250 active users for knowledge-engineering project engagements. |
| 关 键 词: | 科学文章和技术文献; 数量呈指数级增长; PDF格式或位图图像; 异步微服务架构 |
| 课程来源: | 视频讲座网 |
| 数据采集: | 2023-01-28：cyh |
| 最后编审: | 2023-01-28：cyh |
| 阅读次数: | 26 |