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.
Natural language processing (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.
Here’s our verdict on the best C++ NLP tools. We only feature free and open source software here.
Let’s explore the C++ based NLP tools at hand. Click the links in the table below to learn more about each tool.
| C++ Natural Language Processing Tools | |
|---|---|
| MITIE | MIT Information Extraction |
| text2vec | Framework with API for text analysis and natural language processing |
| Moses | Statistical machine translation system |
| TiMBL | Tilburg Memory-Based Learner |
| MeTA | Modern C++ data sciences toolkit |
| CRF++ | Yet Another CRF toolkit |
| BLLIP Parser | Statistical natural language parser |
| Colibri Core | Efficient n-gram & skipgram modelling on text corpora |
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That’s an extensive list of NLP tools. Really thankful for the list.