Search Results for "using class net.sourceforge.jtds.jdbc.driver"

...; * Memorizing - new knowledge item creation; * Abstraction – building objects representing typical signs of similar objects groups, data mining. KM is not intended to replace human experts, it is built to multiply abilities. Machine should not be responsible for decisions. The IMK is designed to create ready-to-use software applications using simple text files. Any human knowledge can be uploaded to KM by expert not familiar with software coding. Demos present in kit. Good luck!

API and command line utility, written in Python, for querying Elasticsearch exporting result as documents into a CSV file. The search can be done using logical operators or ranges, in combination or alone. The output can be limited to the desired attributes. Also ToT can insert the querying to a Pandas Dataframe or/and save its in a HDF5 container (under development).

This project consists out of a windows based designer application and a library (that can run on multiple platforms, including android) together with several demo applications (including an MVC3 chatbot client and an android application). It is probably best compared to a database management system, but for neural networks instead of relational data. As such, the library is optimized for handling any type of data-size by using advanced streaming and caching algorithms. With the designer, you...

WordNet Browser using SQL database and Hibernate as Object-Relational Mapping

Mandarax is a pure Java implementation of a rule engine. It supports mutiples types of facts and rules based on reflection, databases, EJB etc, supporting XML standards (RuleML 0.8). It provides a J2EE compliant inference engine using backward chaining.

A Prolog expert system supporting querying and extending the knowledge base from a command-line interface using a format oriented on natural language, with the aim of being maintainable by the domain expert (i.e. without requiring programming skills).

A C++ library which finds associations within sets of items, using a fast in-memory algorithm.