Related APIs in Category: Semantics
The spoonacular Nutrition, Recipe, and Food API allows you to access over 365,000 recipes and 86,000 food products. Our food ontology and semantic recipe search engine makes it possible to search for recipes using natural language queries, such as "gluten free brownies without sugar" or "low fat vegan cupcakes." You can automatically calculate the nutritional information for any recipe, analyze recipe costs, visualize ingredient lists, find recipes for what's in your fridge, find recipes based on special diets, nutritional requirements, or favorite ingredients, classify recipes into types and cuisines, convert ingredient amounts, or even compute an entire meal plan. With our powerful API, you can create many kinds of food and especially nutrition apps. Special diets/dietary requirements currently available include: vegan, vegetarian, pescetarian, gluten free, grain free, dairy free, high protein, low sodium, low carb, Paleo, Primal, ketogenic, FODMAP, and Whole 30. We will soon be adding Weight Watcher points, too.
This API allows you to extract User Intents from text. Example: API extracts bread making intent from flour yeast water text. Online Demo: https://1.fr/m Input: any text in French. Output: List of the most probable User Intents, with a score indicating how strong that probability is. Technology: TextOptimizer.com is the leader in User Intent extraction. This is based on advanced Natural Language Processing and Semantic analysis. Thousands of writers use our technology daily (manually on TextOptimizer.com).
Shape what comes next with the Oxford Dictionaries API. The OED is the unsurpassed guide to the meaning, history, usage and pronunciation of more than 600,000 words – past and present – from across the English-speaking world. Its historical record of the English language is traced through more than 3.5 million quotations and covers words and senses including rare, obscure, and obsolete terms, as well as terms that are used in modern English. The OED prototype API endpoints return three main data types: • words: data for each OED lemma (headwords and sublemmas), including date range, etymological information, syntactic information, and pronunciations; • senses: data for each word meaning listed in the OED, including date range, definitions, and semantic classifications; • quotations: data for each quotation provided in the OED as an illustrative example, including date, source, and quotation text. Whether you’d like to focus your search on a particular historical period to create a Tudor Word of the Day app, integrate authorial quotations into your project, look up rare and obsolete terms, or offer word histories, this is the resource for you. Try it out and let us know what you think: https://developer.oxforddictionaries.com/our-data
This API can extract important topics from any given text or URL and suggests all relevant Wikipedia Pages related to those topics. You can use it in your application or product for a recommendation system, personalization, semantic analysis, etc. It can take any type of text as input and will perform best on URLs corresponding to news, blog, content, etc.
This API provides text analysis for Tone, Sentiment, Summarization, Personality Analysis, and more. This API can be used for: Part of Speech Tagging Named Entity Recognition Sentence Disambiguation KeyWord Extraction Summarization and Sentence Significance Sentiment Analysis Alliteration Detection Word Sense Disambiguation Clustering Logistic Regression Scoring Prominence Tagging for Latent Semantic Indexing Tagging for Singular Value Decomposition Phonetic Decomposition Reading Difficulty Modeling Technical Difficulty Modeling Spelling Correction String Comparison and Plagiarism Detection Author Profiling Psychographic Modeling Fact and Statistic Extraction Ism Extraction Character Language Modeling It is also useful in the creation of ChatBots, SearchEngines, and KnolExtraction for Automated Documentation.
Topics Extraction tags locations, people, companies, dates and many other elements appearing in a text written in Spanish, English, French, Italian, Portuguese or Catalan. This detection process is carried out by combining a number of complex natural language processing techniques that allow to obtain morphological, syntactic and semantic analyses of a text and use them to identify different types of significant elements.
Human-Like (Deeper than aspect-based) Sentiment Analysis focused on Hotel Reviews and other user generated content. Next-generation NLP API. It is not a tool, it is ready-to-use API, simple to understand. There are 124 semantic models (designed for Hotel Reviews) inside this API. Very high Accuracy! Precission (>95%) and Recall (>75%)