Sentiment Analysis is a procedure used to determine if a chunk of text is positive, negative or neutral. In text analytics, natural language processing (NLP) and machine learning (ML) techniques are combined to assign sentiment scores to the topics, categories or entities within a phrase.
It’s a true story that Germans love their long words. However, this fact may not be so loved for text processing procedures. The lack of NLP libraries in Python adapted to German makes it difficult to properly analyze this kind of words. Let us share with you our NLP tool to split word compounds. It will transform the AI market.
While a picture may be worth a thousand words – a thousand words may be worth thousands of dollars. Never thought how valuable all your company unstructured data would be? This heterogeneous knowledge can turn out to be quite useful for companies, however, there is still much to be learned.
Predictive Analytics Today is one of the must-read sites when it comes to provide review, comparison, research, commentary and analysis of enterprise software. It helps IT decision makers to identify the appropriate technology that fulfills their needs. The site has over 400,000 monthly users, and over 36,000 newsletter subscribers.
In previous posts, we have outlined the crucial role of Machine Learning for Analytics (in Machine Learning & Deep Linguistic Analysis in Text Analytics), and the implications of using Machine Learning for analyzing and structuring text (in What are the limitations of Machine Learning for Text Analysis?).