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Developer(s)Megaputer Intelligence
Stable release
  • Data science
  • machine learning
  • predictive analytics

Polyanalyst is a data science software platform developed by Megaputer Intelligence that provides an environment for text mining, data mining, machine learning, and predictive analytics. It is used by Megaputer to design custom tools for clients in health care, business management, insurance, and other industries. PolyAnalyst has also been used for COVID-19 pandemic forecasting.


File:Convolutional-neural-network-polyanalyst-flowchart-example.png|thumb|A screenshot of a PolyAnalyst flowchart showing the use of a convolutional neural network node.|

PolyAnalyst's graphical user interface contains various nodes, each of which performs a different function. The nodes can be linked into a flowchart to perform an analysis. The software provides nodes for data import, Data pre-processing|data preparation, data visualization, data analysis, and data export.[1] PolyAnalyst can import data from database management systems, from all common file formats, and from previously created PolyAnalyst projects. It can also import web pages directly into the program to be used as data sources for web mining.[2]

PolyAnalyst supports text analytics through nodes that rely on machine learning algorithms and a proprietary programming language called PDL (Pattern Definition Language).[3] PolyAnalyst's text analytics features include nodes for text clustering, sentiment analysis, extraction of facts, Keyword extraction|keywords, and entity extraction|entities, and the creation of Taxonomy (general)|taxonomies and Ontology (information science)|ontologies. Polyanalyst also contains nodes for the analysis of structured data and to execute code in Python (programming language)|Python and R (programming language)|R.[4][5] As of 2020, the software supports text analysis in 16 languages.[6]

After analysis is complete, the result may be exported to a file or published to a web report. PolyAnalyst is typically used by Megaputer to build custom tools for businesses. It uses a client–server model and is licensed under a software as a service model.[7]



PolyAnalyst was used to build a subrogation prediction tool which can assist in identifying subrogatable insurance claims. The tool determines the probability that a claim is subrogatable, and if so, the amount that is expected to be recovered. It is used by insurance companies to reduce the need for manual review of insurance claims and to increase the accuracy of subrogation predictions.[8] PolyAnalyst is also used to detect insurance fraud.

Business Management

Two case studies have used PolyAnalyst to demonstrate the value of data mining to the hotel industry, concluding that it is capable of improving hotel management and customer service.PolyAnalyst is also used to analyze product review data, warranty claims, customer comments, and other textual data.[9] In one case, PolyAnalyst was used to improve a company's system for evaluating its associates conversations with customers by building a tool which rated messages for factors such as professionalism, empathy, and correctness of response. According to Forrester Research, the new tool saved the company around $11.8 million annually while increasing customers' likelihood to recommend.[10]

Health care

PolyAnalyst is used by pharmaceutical companies to assist in pharmacovigilance. The software was used to design a tool that matches descriptions of adverse events to their proper MedDRA codes, determines if side-effects are serious or non-serious, and to set up cases for ongoing monitoring if needed.[11] PolyAnalyst has also been applied to Drug repositioning|discover new uses for existing drugs by text mining ClinicalTrials.gov[12] and to forecast the spread of the COVID-19 pandemic|COVID-19 virus in the United States and Russia.[13][14]

In the media



  1. Apicella, Mario (July 3, 2000). "Info World". PolyAnalyst 4.1 digs through data for gold.{{cite news}}: CS1 maint: url-status (link)
  2. Zhang, Qingyu; Segall, Richard S. (2008-12-01). "Web mining: a survey of current research, techniques, and software". International Journal of Information Technology & Decision Making. 07 (04): 683–720. doi:10.1142/S0219622008003150. ISSN 0219-6220.
  3. Bourlai, Elli (2020-02-12). "Combining the Best of Both Worlds: Machine Learning & Rule-Based Approach". Megaputer Intelligence. Retrieved 2020-10-03.
  4. Zhang, Qingyu; Segall, Richard S. (2010-01-01). "Review of data, text and web mining software". Kybernetes. 39 (4): 625–655. doi:10.1108/03684921011036835. ISSN 0368-492X.
  5. Zhang, Qingyu; Segall, Richard S. (2010), Maimon, Oded; Rokach, Lior (eds.), "Commercial Data Mining Software", Data Mining and Knowledge Discovery Handbook, Boston, MA: Springer US, pp. 1245–1268, doi:10.1007/978-0-387-09823-4_65, ISBN 978-0-387-09823-4, retrieved 2020-10-03
  6. "PolyAnalyst for Text Software". Megaputer Intelligence. Retrieved 2020-09-28.
  7. Halper, Fern (2011). "Predictive Analytics: The Hurwitz Victory Index Report" (PDF). Retrieved 28 September 2020.{{cite web}}: CS1 maint: url-status (link)
  8. "Megaputer Intelligence". big-data.insuranceciooutlook.com. Retrieved 2020-09-21.
  9. "Market Guide for Text Analytics". 31 August 2020.{{cite web}}: CS1 maint: url-status (link)
  10. Evelson, Boris (November 10, 2015). "Vendor Landscape: Big Data Text Analytics". Forrester.{{cite news}}: CS1 maint: url-status (link)
  11. "Life sciences: Increasing speed-to-insight in pharma". www.kmworld.com. Retrieved 2020-09-22.
  12. Su, Eric Wen; Sanger, Todd M. (2017-03-23). "Systematic drug repositioning through mining adverse event data in ClinicalTrials.gov". PeerJ. 5: e3154. doi:10.7717/peerj.3154. ISSN 2167-8359.
  13. Codingest (2020-04-29). "COVID-19: Megaputer provides interactive geo-map to forecast peak of active cases in U.S." thegeospatial. Retrieved 2020-09-30.
  14. "В России представили модели пика заболеваемости COVID-19 в регионах". РБК (in русский). Retrieved 2020-09-24.

External links

Official website

This article "PolyAnalyst" is from Wikipedia. The list of its authors can be seen in its historical. Articles taken from Draft Namespace on Wikipedia could be accessed on Wikipedia's Draft Namespace.