Search Results for "java text area"

Make AI-driven decisions using your data, in real-time. At any scale, with unbeatable performance. Vespa is a full-featured text search engine and supports both regular text search and fast approximate vector search (ANN). This makes it easy to create high-performing search applications at any scale, whether you want to use traditional techniques or a modern vector-based approach. You can even combine both approaches efficiently in the same query, something no other engine can do....

...With a familiar interface easily create line, bar, stacked area, pie, horizontal bar, donut, scatter, and table charts. Add them then to your DataDoc to complete your data narrative.

http://lc.kubagro.ru/ http://lc.kubagro.ru/aidos/index.htm http://lc.kubagro.ru/aidos/_Aidos-X.htm On the IBM PC, the Eidos system started working in 1992. MS Windows has been running since 2012. Implemented in Alaska+Express. I want to try to translate some modes, and maybe all of them, to the Harbor. The full source text in a single file is here: http://lc.kubagro.ru/__AIDOS-X.txt Responsible Secretary Kubgau scientific journal, Professor of computer science Department Kubgau...

DSTK - DataScience ToolKit is an opensource free software for statistical analysis, data visualization, text analysis, and predictive analytics. Newer version and smaller file size can be found at: https://sourceforge.net/projects/dstk3/ It is designed to be straight forward and easy to use, and familar to SPSS user. While JASP offers more statistical features, DSTK tends to be a broad solution workbench, including text analysis and predictive analytics features.

...In this direction, we implement iCubing project with several multidimensional data cube approaches for cube indexing, querying, updating and mining. There are also several cube types, i.e. alphanumeric cubes, text cubes with unstructured data and geo cube with geo types, dimensions, measures and hierarchies, so the OLAP area continues a hard challenge after more than 20 years of the seminal paper of Jim Gray et al. in 1997. Our team has more than 15 years of experience in developing OLAP kernels.