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首页Spark NLP:大规模企业级自然语言处理解决方案
Spark-NLP是一个基于Apache Spark的机器学习库,专注于大规模自然语言处理(NLP)。该库的设计初衷是为了提供简单、高效且准确的NLP标注,使其能够轻松地适应分布式环境中的机器学习管道。Spark-NLP的优势在于其丰富的预训练管道和模型,总计超过1100种,覆盖了192多种语言,几乎涵盖了所有可以无缝应用于集群的NLP任务和模块。 它的功能强大,不仅包括常见的文本理解应用,如问答系统、文本重写或概括、情感分析以及自然语言商务智能,还支持深度学习技术,如TensorFlow,这使得它在处理复杂语言问题时表现出色。自2020年1月以来,Spark-NLP的下载量超过270万次,并实现了9倍的增长,显示出其在企业界的广泛接纳度。尤其在医疗保健领域,Spark-NLP被54%的组织采用,成为全球企业中最广泛使用的NLP库。 Spark-NLP的成功源于其与Spark框架的高度集成,这使得开发者能够在处理大量数据时充分利用Spark的大数据处理能力。通过其用户友好的API和模块化设计,无论是初学者还是专业开发者都能快速上手并构建定制化的NLP解决方案。然而,Spark-NLP并不仅仅局限于企业级应用,它也适用于各种规模的数据科学项目,从学术研究到在线客服,都能看到其身影。 Spark-NLP是一个集成了深度学习和大规模数据处理能力的NLP工具,它极大地简化了复杂自然语言处理任务的实现,促进了人工智能在各行各业的广泛应用。随着技术的不断迭代和更新,Spark-NLP有望在未来继续保持其在自然语言处理领域的领先地位。
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Spark NLP: Natural Language Understanding at Scale
Veysel Kocaman, David Talby
John Snow Labs Inc.
16192 Coastal Highway
Lewes, DE , USA 19958
{veysel, david}@johnsnowlabs.com
Abstract
Spark NLP is a Natural Language Processing (NLP) library built on top of
Apache Spark ML. It provides simple, performant & accurate NLP annotations
for machine learning pipelines that can scale easily in a distributed environment.
Spark NLP comes with 1100+ pretrained pipelines and models in more than 192+
languages. It supports nearly all the NLP tasks and modules that can be used seam-
lessly in a cluster. Downloaded more than 2.7 million times and experiencing 9x
growth since January 2020, Spark NLP is used by 54% of healthcare organizations
as the world’s most widely used NLP library in the enterprise.
Keywords: spark, natural language processing, deep learning, tensorflow, cluster
1. Spark NLP Library
Natural language processing (NLP) is a key component in many data science
systems that must understand or reason about a text. Common use cases include
question answering, paraphrasing or summarising, sentiment analysis, natural
language BI, language modelling, and disambiguation. Nevertheless, NLP is
always just a part of a bigger data processing pipeline and due to the nontrivial
steps involved in this process, there is a growing need for all-in-one solution to ease
the burden of text preprocessing at large scale and connecting the dots between
various steps of solving a data science problem with NLP. A good NLP library
should be able to correctly transform the free text into structured features and
let the users train their own NLP models that are easily fed into the downstream
machine learning (ML) or deep learning (DL) pipelines with no hassle.
Spark NLP is developed to be a single unified solution for all the NLP tasks
and is the only library that can scale up for training and inference in any Spark
cluster, take advantage of transfer learning and implementing the latest and greatest
Preprint submitted to Software Impacts January 27, 2021
arXiv:2101.10848v1 [cs.CL] 26 Jan 2021
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