Natural language processing (NLP) is a set of techniques for using computers to detect in human language the kinds of things that humans detect automatically.
NLP is an exciting field of computer science, artificial intelligence, and computational linguistics concerned with the interactions between computers and human (natural) languages. It includes word and sentence tokenization, text classification and sentiment analysis, spelling correction, information extraction, parsing, meaning extraction, and question answering.
In our formative years, we master the basics of spoken and written language. However, the vast majority of us do not progress past some basic processing rules when we learn how to handle text in our applications. Yet unstructured software comprises the majority of the data we see. NLP is the technology for dealing with our all-pervasive product: human language, as it appears in social media, emails, web pages, tweets, product descriptions, newspaper stories, and scientific articles, in thousands of languages and variants.
Many challenges in NLP involve natural language understanding. In other words, computers learn how to determine meaning from human or natural language input, and others involve natural language generation.
Java is one of the most widely used programming languages owing part of its popularity to its extensive ecosystem. Programming in Java provides the access to this ecosystem that consists of several libraries, frameworks, and APIs.
Java runs Python and R close when it comes to NLP. Our recommendations are captured in this ratings chart. Only free and open source software is eligible for inclusion.
Let’s explore the Java based NLP tools at hand. Click the links in the table below to learn more about each tool.
| Java Natural Language Processing Tools | |
|---|---|
| CoreNLP | Annotation-based NLP pipeline that provides core natural language analysis |
| OpenNLP | Machine learning based toolkit |
| Lucene | High-performance, full-featured information retrieval software library |
| UIMA | Open source implementation of the UIMA specification |
| GATE | Full-lifecycle solution for a broad range of NLP tasks |
| MALLET | Statistical natural language processing, document classification and more |
| ReVerb | Automatically identifies and extracts binary relationships from sentences |
| CogComp-NLP | State-of-the-art Natural Language Processing (NLP) tools |
| Tika | Content analysis toolkit |
| NLP4J | NLP framework for JVM languages |
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