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Harness the power of next-generation AI to extract more from text in 27 languages: detect bigotry, sexual harassment, cyberbullying, extract topics, and find not only whether, but also why the customer is happy or unhappy with your product or service. Our applications and components are accessible via a public cloud on a subscription basis (SaaS), can be installed on premises, or embedded in 3rd party applications for seamless integration and security.
The supported languages are: English, Chinese (Simplified and Traditional), Arabic, Danish, German, Spanish, Persian, Finnish, French, Hebrew, Indonesian, Italian, Japanese, Korean, Malay, Dutch, Norwegian, Polish, Pashto, Portuguese, Russian, Swedish, Thai, Turkish, Urdu, Vietnamese.
We offer several ways to use our components, from a generous free plan (not just a limited trial) to enterprise-grade plans and on prem installation options. Whether you're a small startup, an independent developer, or an enterprise, we can work together.
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TextAnalysis API provides customized Text Analysis,Text Mining and Text Processing Services like Text Summarization, Language Detection, Text Classification, Sentiment Analysis, Word Tokenize, Part-of-Speech(POS) Tagging, Named Entity Recognition(NER), Stemmer, Lemmatizer, Chunker, Parser, Key Phrase Extraction(Noun Phrase Extraction), Sentence Segmentation(Sentence Boundary Detection), Grammar Checker and other Text Analysis Tasks. It stands on the giant shoulders of NLP Tools, such as NLTK, TextBlob, Pattern, MBSP and etc. You can test the services on our demo website TextAnalysisOnline and use the TextAnalysis API on Mashape. If you have any questions or want any customized text analysis services, you can contact us by email: [email protected]
Our Natural Language Processing API contains all the necessary text processing tools one might expect from an NLP API, including tokenization, sentence splitting, part-of-speech tagging and named entity recognition. In addition to these NLP tools, our API features many advanced Deep Learning classification models to extract a rich representation from unstructured texts, including speech acts, questions, emotions, sarcasm, sentiment, date resolution, and tasks.
Related APIs in Category: Natural Language Processing
Since we understand the recipe – ingredients, diets, allergies, nutrition, taste, techniques & more. We can connect your users with the best recipes available for their unique food preferences. Search over 2 million recipes - Search our large recipe database. We add new sites and recipes continuously. - You will also get access to over 5000 top web recipe sources - Our search algorithm returns the most relevant recipes from the most popular and best recipes sources on the web. We order recipes by their cookability and quality so your customer can always count on getting the best recipes! Semantically organized database - The recipes in our database are normalized and can be filtered in the search by calorie and diet preferences. Full nutrition for each recipe - We have the most accurate automated nutrition analysis on the web powered by our proprietary Natural Language Processing (NLP) engine. Customers get detailed nutrition breakdown of each recipe with 25+ nutrients and appropriateness for all major diets. - Filter by calories, diet or allergy restrictions - Edamam has developed over 35 diet and health filters for your customers to use. Now you can develop applications for virtually any popular diet or major health condition. Recipe caching - Edamam may allow caching for those customer on custom plans.
Text Summarization API provides professional text summarizer service which is based on advanced Natural Language Processing and Machine Learning technologies. It can be used to summarize short important text from the URL or document that user provided. If you want test our automatic text summarization service, you can use our free automaticText Summarizer online demo: http://textsummarization.net/text-summarizer
This API provides you with tools to find nutrition and diet data for generic foods, packaged foods and restaurant meals. In addition it employs NLP (Natural Language Processing) which allows for extraction of food entities from unstructured text. Covered Use Cases: Search for a food by keyword, food name or UPC/Barcode Sourcing of nutrition facts for a given food, including: macro and micro nutrients, allergen labels, lifestyle and health labels Search for a food by given nutrient quantity for 28 nutrients Seach for foods within a given brand With the build in food-logging context it allows for NLP requests for chat bots and natural language calorie counters
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