Keyword Extraction API can easily be integrated in your project, and it is wise to select and subscribe to the correct engine depending on your data. Keyword Extraction (or keyword detection, keyword analysis or wordsfinder extraction) is an approach to analyse text from data obtained automatically from text data. Whether they are words or phrases, it helps gauge the content of reviews and identify the main topics. By means of ML (Machine Learning) and NLP (Natural Language processing) this approach scours human language to comprehend and interpret messages and meta-messages.
An accessory tool is Text Analytics API. This is a service that using AI (Artificial Intelligence) it processes advanced NLP over unstructured text, and performs sentiment analysis, key phrase extraction, entity recognition and language detection. There are several Keyword Extraction platforms, more or less complex to set up and use, and demanding some expertise in data science. You select the one that fits best to your organization, requirements, purpose and cost.
An efficient API will provide NLU (Natural Language Understanding) solutions to allow large organizations to monitor and extract texts automatically, so as to analyse key information from any kind of text data. AI and the contributions of Neurosciences optimize such services. The relevance of words, meaning and meta-messages contributes to get positive, neutral or negative insights, and even irony, sarcasm and indifference. The use of Wordsfinder Extractor API and Relevant words Extractor API complete the suite of tools for word detection. It can even chop the long text into chunks (Key Chunk Extractor API).
Zyla Labs offers a useful and comprehensive Keyword Extraction API for software developers; it uses a complete suite of APIs for sentiment analysis and emotion detection, among others, with guaranteed accuracy of results. By means of NLP it extracts content from data set. It processes any text files in structured and unstructured texts. It identifies entities, key phrases, language, sentiments and other useful elements from text data.
ParallelDots is a comprehensive set of document classification and NLP APIs. It offers NLP models which are trained on countless documents to provide outstanding accuracy in detection, recognition and extraction of sentiments and emotions. It also supplies disambiguation and linking, keyphrase extraction, topic tagging and classification.
Yonder Labs supplies data science services through NLP, ML and Multimedia Analysis. It allows to extract relevant information from text documents and collections of texts. It also renders text comparison, clustering and data mining. Sentiment analysis, entity extraction, semantic tagging are performances of this API as well.
IBM Natural Language Understanding is a suite of APIs for text analysis by means of NLP. The API collection can scour text to aid in understanding concepts, entities, keywords, sentiment, emotion, etc. Likewise, it allows to build up a custom model so as to get specific results tailored to your needs.
MonkeyLearn is a platform for text analysis with ML, which offers automated scanning of text data, saving time and expenses. By means of pre-built NLP platforms it provides various services, namely entity extraction, sentiment analysis, text classification and others. It can be tailored to output ML models to draw topic, sentiment, intent, keywords, etc.
The above mentioned APIs combine NLP techniques with ML and a comprehensive knowledgebase of actual facts, to get the most from documents, judgement in social media sites, forums or web pages. It is up to you to select the one that best adapts to your needs, purpose and budget. The results will guide the manufacturer or services supplier to pulse consumers` opinion so as to make the right decisions in implementing appropriate adjustments and improvements to get satisfaction from the market.