Part 3: How to bootstrap with Machine Learning: Natural Language Processing and Text Analysis

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In the 2 previous posts we have discussed a list of API services that could be helpful for quickly starting with Making Data-Based Prediction and Image-related analysis, such as Face Recognition or Pattern Recognition.

This is my favorite topic as I’m involved into building PocketConfidant, a 24/7 counselling technology, powered by AI and psycho-linguistics. Now my purpose is to share a list of services that could help in

Text Analysis, Natural Language Processing and Sentiment Analysis.

Machine Learning API for

Text Analysis, Natural Language Processing and Sentiment Analysis

  • AlchemyAPI Keyword Extraction: extracts topic keywords from text, HTML, or posted web-based content. This API normalizes the targeted text, removing ads, navigation links, and other unnecessary content, then extracts topic keywords.
  • Calais:  Using natural language processing, machine learning and other methods, Calais categorizes and links your document with entities (people, places, organizations, etc.), facts (person “x” works for company “y”), and events (person “z” was appointed chairman of company “y” on date “x”).
  • Semantic Biomedical Tagger: has a built-in capability to recognize 133 biomedical entity types and semantically link them to the knowledge base systems.
  • Free Natural Language Processing Service: sentiment analysis, content extraction, and language detection.
  • nlpTools: decodes online news sources for sentiment analysis and textual classification. In order to analyze the sentiment or classify of a line of text, developers may use this API to receive a return of a category label and a conditionality on the piece ranging from positive, neutral, to negative sentiment.
  • Skyttle: Market Sentinel’s text mining engine, which analyses text for topical keywords and phrase-level sentiment. Languages supported are English, French, German, Russian.
  • AlchemyAPI: AlchemyAPI offers artificial intelligence as a service. Currently available text analysis functions include entity extraction, sentiment analysis, keyword extraction, concept tagging, relation extraction, text categorization, author extraction, language detection, text extraction, microformats parsing and RSS/ATOM feed detection.
  • RxNLP – Cluster Sentences and Short Texts: a Text Mining and Natural Language Processing service.  One of RxNLP’s API’s, The ClusterSentences API, can group sentences (such as sentences from multiple news articles) or short texts (such as posts from Twitter or Facebook Status Updates) into logical groups.
  • Speech2Topics: analyzes audio and video to extrapolate big data, using natural language processing and speech recognition.
  • Hutoma: AIs are powered by a deep learning network and can be trained to understand specific topics by simply submitting a text file containing examples of conversations. Creates & Deploys Siri like interfaces.
  • Bitext Sentiment Analysis: a suite of multilingual semantic services. Currently four semantic service are available: entity and concept extraction, sentiment analysis and text categorization.
  • TweetSentiments: performs semantic analysis of tweets using a Support Vector Machines algorithm. Doing so, it is able to determine whether tweets are positive, negative or neutral in sentiment.
  • Diffbot Analyze: provides developers tools that can identify, analyze, and extract the main content and sections from any web page.
  • Text Processing: provides  functions that include summarizing documents, tagging documents, stemming words to their base forms, removing stopwords, tagging parts of speech (POS), translating from Bahasa Indonesia to English, and retrieving word definitions.
  • MeaningCloud: It features APIs for information extraction, text classification and clustering, sentiment analysys, user profiling and more. Use its plug-ins to easily perform text analytics in your spreadsheet, graphically customize its text classification and sentiment analysis functionalities to your specific domain to obtain unparalleled accuracy, and embed semantic analysi s into your applications without risk through its pay-per-use web-based APIs.

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