DATA MINING PRODUCT

Brand Owner (click to sort) Address Description
MISCELLANEOUS DESIGN Caesius Software, Inc. 2300 Elliott Avenue, Suite 514 Seattle WA 98121 Data mining product, namely, computer software that provides a search engine with the capability to extract and organize selected data from a wide variety of sources on a global computer network; the computer software being provided as a product on a computer-readable media, namely, ROM, RAM, EEPROM, flash memory, magnetic storage devices, CD-ROM, DVD, optical storage devices, magnetic tape, magnetic tape cassettes, magnetic hard disk storage and floppy disks and the computer software being provided as a product over a communications media via a global computer network, namely, wired network, direct wired connection, and wireless network, namely, acoustic, radio frequency and infrared technologies;computer services, namely, providing computer searches for obtaining data on a global computer network;
WE'RE YOUR DATA Caesius Software, Inc. 2300 Elliott Avenue, Suite 514 Seattle WA 98121 Data mining product, namely, computer search engine software and downloadable computer search engine software;Computer services, namely, creating indexes of information, sites, and other resources available on computer networks, and computer services, namely, providing search engines for obtaining data on a global computer network;
 

Where the owner name is not linked, that owner no longer owns the brand

    
Technical Examples
  1. A system, method, and computer program product for in-database clustering provides the capability to perform cluster analysis and provides improved performance in model building and data mining, good integration with the various databases throughout the enterprise, and flexible specification and adjustment of the models being built, but which provides data mining functionality that is accessible to users having limited data mining expertise and which provides reductions in development times and costs for data mining projects. A database management system for in-database clustering, comprises a first data table and a second data table, each data table including a plurality of rows of data, means for building a clustering model using the first data table, and means for applying the clustering model using the second data table to generate apply output data.