Another Word For It Patrick Durusau on Topic Maps and Semantic Diversity

October 19, 2011

Rapid-I: Report the Future

Filed under: Analytics,Data Mining,Document Classification,Prediction — Patrick Durusau @ 3:15 pm

Rapid-I: Report the Future

Source of:

RapidMiner: Professional open source data mining made easy.

Analytical ETL, Data Mining, and Predictive Reporting with a single solution

RapidAnalytics: Collaborative data analysis power.

No 1 in open source business analytics

The key product for business critical predictive analysis

RapidDoc: Webbased solution for document retrieval and analysis.

Classify text, identify trends as well as emerging topics

Easy to use and configure

From About Rapid-I:

Rapid-I provides software, solutions, and services in the fields of predictive analytics, data mining, and text mining. The company concentrates on automatic intelligent analyses on a large-scale base, i.e. for large amounts of structured data like database systems and unstructured data like texts. The open-source data mining specialist Rapid-I enables other companies to use leading-edge technologies for data mining and business intelligence. The discovery and leverage of unused business intelligence from existing data enables better informed decisions and allows for process optimization.

The main product of Rapid-I, the data analysis solution RapidMiner is the world-leading open-source system for knowledge discovery and data mining. It is available as a stand-alone application for data analysis and as a data mining engine which can be integrated into own products. By now, thousands of applications of RapidMiner in more than 30 countries give their users a competitive edge. Among the users are well-known companies as Ford, Honda, Nokia, Miele, Philips, IBM, HP, Cisco, Merrill Lynch, BNP Paribas, Bank of America, mobilkom austria, Akzo Nobel, Aureus Pharma, PharmaDM, Cyprotex, Celera, Revere, LexisNexis, Mitre and many medium-sized businesses benefitting from the open-source business model of Rapid-I.

Data mining/analysis is the first part of any topic map project, however large or small. These tools, which I have not (yet) tried, are likely to prove useful in such projects. Comments welcome.

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