This Scientific Text Analytics And Annotators market study offers a comprehensive analysis of the business models, key strategies, and respective market shares of some of the most prominent players in this landscape. Along with an in-depth commentary on the key influencing factors, market statistics in terms of revenues, segment-wise data, region-wise data, and country-wise data are offered in the full study. This study is one of the most comprehensive documentation that captures all the facets of the evolving Scientific Text Analytics And Annotators market.
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.
There are varied application of text analytics which are listed below:
- Sentiment analysis
- Search access of unstructured data
- Email spam filters
- Automated AD placement
- Social media monitoring
- Competitive intelligence
- Enterprise business intelligence and data mining
- E-discovery, records management
- National security and intelligence
- Competitive intelligence
- Scientific discovery
Few of them which are commonly used are:
- Sentiment Analysis: Suppose there is an online portal for garments. There is an online submission form for customers to send in their feedback regarding their purchase. The owner would like to find out the response (positive and negative) of all its customers. In this case they can make use of text analytics tool to find out the sentiment of the customer; whether they are satisfied or dissatisfied with the product.
- Topic modeling: It is a technique for finding out most commonly used (discussed) themes from a vast array of topics. It is mostly used by legal firms for digging out information regarding a high profile case.
- Named entity recognition: It basically tries to recognize nouns which could be a person’s name, country, organization, date, monetary amounts, or the likes of it.
Scientific Text Analytics and Annotators Market: Drivers and Challenges
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.
Key Market Players
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.
The report covers exhaustive analysis on:
Scientific Text Analytics and Annotators Market Segments
- Scientific Text Analytics and Annotators Market Dynamics
- Historical Actual Market Size, 2013 - 2015
- Scientific Text Analytics and Annotators Market Size & Forecast 2016 to 2026
- Value Chain
- Scientific Text Analytics and Annotators Market Current Trends/Issues/Challenges
- Competition & Companies involved
- Scientific Text Analytics and Annotators Market Drivers and Restraints
Regional analysis for Scientific Text Analytics and Annotators Market includes development of these systems in the following regions:
- North America
- Latin America
- Rest of Latin America
- Asia Pacific
- Australia and New Zealand (A&NZ)
- Rest of Asia Pacific
- The Middle East and Africa
- GCC Countries
- North Africa
- South Africa
- Rest of MEA
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.
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Scientific Text Analytics and Annotators Market: Segmentation
Segmentation On The Basis Of Deployment Type:
Segmentation On The Basis Of Application:
- Marketing and Customer Experience Management
- Data analysis and forecasting
- Enterprise Information Management
- Other industry specific applications
Segmentation On The Basis Of End-User:
- Financial services and Insurance
- military and defense
- IT and telecom
- entertainment and media
- Others (Transportation, Hospitality, Automotive)
- Detailed overview of parent market
- Changing market dynamics in the industry
- In-depth market segmentation
- Historical, current and projected market size in terms of volume and value
- Recent industry trends and developments
- Competitive landscape
- Strategies of key players and products offered
- Potential and niche segments, geographical regions exhibiting promising growth
- A neutral perspective on market performance
- Must-have information for market players to sustain and enhance their market footprint
Frequently Asked Questions
What research methodology is used to develop the Scientific Text Analytics And Annotators Market report?
- FMI utilizes three branched methods to derive market measurements used to compile any report study (data derivation, triangulation and validation).
- These approaches include accumulating data from both primary and secondary sources
- Primary research involves interviews with industry operators and FMI's network of contacts spanning the world's value chain of the Scientific Text Analytics And Annotators Market. This is supported by a comprehensive literature analysis of information gathered through secondary sources
- Analysis of several middle market stakeholders for country-wise data
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In addition to up-to-date market figures and customized of the Scientific Text Analytics And Annotators Market, FMI offer consulting services to help businesses within industry navigate challenges and take well-informed decisions amidst the breakneck competition.
How do you define competitors based on market structure? What aspects about a competitor are included in the company profile section?
- Most of the competitors are segregated according to their market share in 'Tier' wise statures.
- Global market participants are scrutinized and global competition metrics are included with numerous competitor profiles referring to their business background and go-to market strategies.