Scientific text analytics refers to the process of analyzing unstructured raw data, extracting relevant information from it and transforming it into useful business information. An annotator is something that can supply or furnish critical or explanatory notes or comments.
Text analytics and annotators combined together can help companies in fetching relevant information from a large amount of data by capturing certain keywords, phrases, classifications or entities which help them in determining the sentiments of user.
The various steps that are carried out in text analytics is text identification, text mining, text categorization, text clustering, search access, entity/relation modeling, link analysis, sentiment analysis, summarization and visualization.
The scientific text analytics and annotators market is expected to rise in the future as solution providers are merging big data with text analytics which can be used across various sectors such as healthcare, finance, banking, retail, government, and many more.
Organizations can benefit by getting a competitive edge over their competitors, or understand their current target market in a better way; for example – through social media tracking, a retail company can find out whether its customers are satisfied with its new product by tracking certain keywords or phrases.
Also, cloud-based text analytics solutions are rapidly growing in the market as companies are themselves going through a transformation (due to digitization). Also, many small and medium scale enterprises find cloud-based solutions to be more economical as they require less storage space and lower maintenance cost.
Another market driver is that text analytics tool can break the language barrier. The emergence of multilingual text analytical tools has helped multi-national companies in gathering data and interpreting information in a more efficient manner. Also, every business has its own set of requirements and applications. There is an increase in industry-specific text analytics tools which has led to many companies adopting this solution.
One of the challenges faced is sometimes a customer tends to be sarcastic while commenting on social media platform, or during a customer service call, they seem to be agitated (the reason could be altogether different), the text analytics and annotator tool might not be able to capture the true sentiment of the customer. This is due to lack of such level of advancement in the solution which can lead to wrong interpretations.
The major players active in the Global Scientific text analytics and annotators market include SAS Institute Inc., IBM Corporation, SAP SE, MeaningCloud LLC, Smartlogic, Lexalytics, Provalis Research, OpenText Corporation, Pingar, AlchemyAPI and RapidMiner, Inc..
Currently Scientific Text Analytics and Annotators industry is being dominated by North America followed by Europe. Asia-Pacific region is picking up pace in this market, and is expected to have the highest growth rate in the forecasted period, especially India and China.
Scientific Text Analytics and Annotators Market Segments
The report is a compilation of first-hand information, qualitative and quantitative assessment by industry analysts, inputs from industry experts and industry participants across the value chain. The report provides in-depth analysis of parent market trends, macro-economic indicators and governing factors along with market attractiveness as per segments. The report also maps the qualitative impact of various market factors on market segments and geographies.
Segmentation On The Basis Of Deployment Type:
Segmentation On The Basis Of Application:
Segmentation On The Basis Of End-User:
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Scientific Text Analytics And Annotators Market
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