Reading and Analyzing Digital Data Can Help Many Companies Connect with Customers

    Written by admin on . Posted in Named entity recognition, Text analysis software engine, Text extraction tools

    Text enrichment

    Have you ever had a friend who was hard to read? Ever had a spouse whose mood swings could determine the success or failure of the day. Although humans are sometimes difficult to read, the latest artificial intelligence (AI) may be successful In fact, Facebook has recently attempted to use emotion AI to help recognize people who might be suffering from depression and showing signs of suicide. And while this particular use of emotion AI may still be in its infancy, there are many who believe that any attempt to help save a life is worthwhile.
    We live in an amazing time, and while we typically think of technology as a non emotional field, the reality is that the latest semantic extraction software is being used for a variety of purposes. From sentiment analysis to social media data analysis, the use of artificial intelligence continues to expand. And while there are some ways that these processes are already being used, they are many more applications that will likely develop. In fact, the current value of the text analytic market is at an estimated $3 billion and but is forecasted to reach almost $6 billion by the year 2020. And while many companies have found a way to extract digital data, a mere 1% of this data is being used.
    Text Analytics is the process of converting unstructured text data ito measure customer opinions, feedback, product reviews, sentiment analysis, and entity extraction. In an effort to support fact based decision making. text analytics provides meaningful data for corporations wishing to analyze customer data, as well as government agencies and security agencies that are wishing to research people.

    Entity Extraction software analyzes raw text to catalogue and identify unique entities, including dates, people, events, places, and companies. Like other type of analytics, entity extraction involves the four steps in the text mining process, including information retrieval, natural language processing, information extraction, and data mining.
    Sentiment Analysis is the process of analyzing text for negative or positive attitudes. Social media posts, for instance, could be analyzed to discern new product reactions.
    Identity resolution software helps determine when two or more different looking identities, Jane Smith and Janie Smith, for example, are actually describing the same person, even when there are inconsistencies in the data. This process could be used by y governments conducting visa screenings or by corporations analyzing customer data.
    The next time you have a friend or a spouse who is difficult to read, you might look forward to a time when emotion AI and other methods can serve this purpose.

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