The Text Analytics API is a suite of text analytics web services built with best-in-class Microsoft machine learning algorithms. The API can be used to analyze unstructured text for tasks such as sentiment analysis, key phrase extraction and language detection. No training data is needed to use this API; just bring your text data. This API uses advanced natural language processing techniques to deliver best in class predictions.
AYLIEN Text API is a package of Natural Language Processing, Information Retrieval and Machine Learning tools that allow developers to extract meaning and insights from documents with ease.
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@example.com
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.
Sentiment analysis, stemming and lemmatization, part-of-speech tagging and chunking, phrase extraction and named entity recognition.
Ujeebu (formerly Lexper) provides tools for content extraction and text analysis and classification.
Built by Basis Technology, the Rosette API is a cloud-hosted RESTful web service that provides a wealth of powerful text analysis, from pure linguistics to entity, name, and sentiment centric analysis in Asian, European, and Middle Eastern languages.
Document Similarity API is based on advanced Natural Language Processing and Machine Learning technologies, and it belongs to text analysis and can be used to analysis the semantic similarity of two text document that user provided. The result is cosine similarity from 0 to 1, 0 means absolute different, 1 means absolute same.
Generate word & n-gram counts, compute text similarity, extract topics (keywords) from text , cluster sentences, extract text from HTML pages, summarize opinions.
This api includes some popular text analytics tools such as word/sentence similarity, sentiment analysis, and topic tagging.
This calculates the similarity between two texts in percentage. It is an implementation as described in Programming Classics: Implementing the World's Best Algorithms by Ian Oliver). Note that this implementation does not use a stack as in Oliver's pseudo code, but recursive calls which may or may not speed up the whole process. Note also that the complexity of this algorithm is O(N**3) where N is the length of the longest string. For more details: https://en.wikipedia.org/wiki/Approximate_string_matching
Sentiment analysis. Classifies as positive or negative. Trained with multiple data sets (IMDB, Twitter etc).
Analysing text sentiment by passing text or paragraphs, in single line or multiple lines, and get back with the sentiment analysis report, to get how many of lines be analysed, how many positive, negative, middle sentiment for the lines of text.
Summarization is MeaningCloud's solution to extract a summary for a given document, selecting the most relevant sentences in it to try to sum up what it is about. This process does not take into account the language when it evaluates the importance of a sentence, which means that it's language independent and can be applied to documents in any language.
Deep Categorization is MeaningCloud's solution for in-depth rule-based categorization. It assigns one or more categories to a text, using a very detailed rule-based language that allows you to identify very specific scenarios and patterns using a combination of morphological, semantic and text rules.
Text Clustering is MeaningCloud's solution for automatic document clustering, i.e., the task of grouping a set of texts in such a way that texts in the same group (called a cluster) are more similar to each other than to those in other clusters.
Multilingual sentiment analysis of texts from different sources (blogs, social networks,...). Besides polarity at sentence and global level, Sentiment Analysis uses advanced natural language processing techniques to also detect the polarity associated to both entities and concepts in the text. Sentiment Analysis also gives the user the possibility of detecting the polarity of user-defined entities and concepts, making the service a flexible tool applicable to any kind of scenario. Additionally, Sentiment Analysis detects if the text processed is subjective or objective and if it contains irony marks [beta], both at global and sentence level, giving the user additional information about the reliability of the polarity obtained from the sentiment analysis.
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.
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
Our new approach to summarization won't miss any important details from your text.
The Next-generation of Sentiment Analysis, Keywords, Topics and Categories. 124 Semantic models designed especially for hotel reviews. With this unique approach, we cover more than 90% of information/facts contained within the review. Testing it on hundreds of thousands of reviews, we achieved very high accuracy (precision=95%) We call it Human-like Analysis because with these parameters we achieve the same quality as detected by skilled analysts (humans). It opens up a lot of new functionalities that can be easily combined with your product without any post-processing, additional training or configuration to your data. To learn more what can be done with this technology, visit our webiste: http://unicornnlp.com/?solutions-in-travel
NLP and text analytics have come a long way. Software today can not only read text but also extract entities, relationships, facts and even detect emotions. Imagine the applications you can build with powerful text analysis. With Rakuten RapidAPI's text analysis APIs your app can easily implement text mining, text classification, language detection, text comparison, text summarization, sentiment analysis, and entity extraction without any expenditure on machine learning infrastructure.
Top Text Analytics APIs - Rakuten RapidAPI Blog
API Tutorial: Explore the Aylien Text Analysis API - Rakuten RapidAPI Blog