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Sentiment analysis, stemming and lemmatization, part-of-speech tagging and chunking, phrase extraction and named entity recognition.
One API for all your text analysis needs. Sentiment Analysis, Topic Tagging, Lemmatizer, and much more. Various NLP tools all with one plan. Use natural language processing to analyze and understand human sentences.
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...
This API allows you to extract most relevant terms from a text. It is not, like many others, a basic TF-IDF analysis. It compare the text against a very large language model, it uses a probabilistic model to identify candidates, it supports multi-words terms and not only single words. It uses part of speech tagging to clean up the results". In short it is probably the most advanced term extraction out there.
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.
A keyword extractor uses state-of-the-art language models to extract words from a body of text that are considered to be especially representative of the overall meaning of the text. Using a keyword extractor is great for document tagging, navigation and search.
In corpus linguistics, part-of-speech tagging (POS tagging or PoS tagging or POST), also called grammatical tagging is the process of marking up a word in a text (corpus) as corresponding to a particular part of speech, based on both its definition and its context. A simplified form of this is commonly taught to school-age children, in the identification of words as nouns, verbs, adjectives, adverbs, 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.
This service provides detailed linguistic information for a given text in English, Spanish, French, Italian, Portuguese and Catalan. There are three operating modes that cover different aspects of the morphosyntactic and semantic analysis: Lemmatization, which provides the lemmas of the different words in a text; PoS tagging: which provides not only the grammatical category of a word, including semantic information about that word; Syntactic analysis: that provides a thorough syntactic analysis, giving a complete syntactic tree where the leaves represent the most basic elements and their morphological and semantic analyses.
Tools for Azerbaijan language for tokenization, sentence splitting, part-of-speech tagging and named entity recognition.
Imagga is an automated image tagging, image categorization, composition and color analysis API. It's just a matter of making an API call to extract the type of metadata relevant to you. Imagga's deep learning and image recognition technology helps developers to build apps that understand images and companies to make sense of their large-scale image collections.
Refinitiv Intelligent Tagging automatically creates rich, semantic metadata from unstructured text documents, offering a way to link, tag, and discover relationships within content to increase its value and use it gain competitive advantage.
This api includes some popular text analytics tools such as word/sentence similarity, sentiment analysis, and topic tagging.
Unique News Search and Analytics capabilities: search in over 50,000 daily English-language news posts, content quality scoring and clickbait detection, URL links and semantic graph extraction, similar content detection, publisher statistics, geolocation tagging and more. TrustServista is a software solution provided by Zetta Cloud (www.zettacloud.ro). Read more: www.trustservista.com
MateNLP provides you with a broad range of services under one umbrella which includes; POS Tagging, Lemmatization, Named Entity Recognition, Basic, Collapsed & Collapsed CC Processed Dependency parsing and Also Parsed Tree form of text.
A Mashape wrapper for indico's existing text APIs. Current APIS: Sentiment Analysis Political Alignment Detection Language Detection Text Tagging Our image APIs will be along shortly, once the interface is cleaned up a bit. These APIs also have explicit wrappers for a number of languages visible on our Github page: https://github.com/IndicoDataSolutions More documentation as well as docs specific to each of our language can be found here: http://indico.readme.io/v1.0/docs
Moodli provides Real-time sentiment analysis of tweets containing covid19-related keywords + geo-tagging each tweet. So far we only support English tweets. The geojson contains 2000 data points at once. The information is updated every 2 minutes.