Download JAR files tagged by standard with all dependencies

Our first work is to create a set of tools to help in the adoption drools in our local companies. Those tools are here to make drools "enterprise ready "by adopting an industrial approach : we want to put in common a standard library that we shall all use in our drools project. This tools are of course open source and we use a friendly apache licence. Indeed, drools like any other jboss framework is a swiss knife that offers all possibilities. Our framework implements the best practices that we implemented in real projects that goes from how to monitor, report and supervise the use of drools. We hope you will enjoy our work and invite you to contact us in case of trouble. But do not forget we are a community !

The UnboundID LDAP SDK for Java is a fast, comprehensive, and easy-to-use Java API for communicating with LDAP directory servers and performing related tasks like reading and writing LDIF, encoding and decoding data using base64 and ASN.1 BER, and performing secure communication. This package contains the Minimal Edition of the LDAP SDK, which is a stripped-down version of the Standard Edition that includes full support for the LDAP protocol and LDIF parsing, but omits a number of optional elements, like many of the controls and extended operations, the LDAP persistence framework, and LDAP listener framework. The Minimal Edition is primarily intended for use in space-constrained and/or memory-constrained environments, like in Android apps or embedded systems.

The UnboundID LDAP SDK for Java is a fast, comprehensive, and easy-to-use Java API for communicating with LDAP directory servers and performing related tasks like reading and writing LDIF, encoding and decoding data using base64 and ASN.1 BER, and performing secure communication. This package contains the Commercial Edition of the LDAP SDK, which includes all of the general-purpose functionality contained in the Standard Edition, plus additional functionality specific to UnboundID server products.

In some data processing tasks we need to use huge maps or sets that are bigger than available JVM heap space or they are loading too slow to standard Java or Scala Maps. We use TSV format (text file with tab separated columns) for persist this kind of Maps or Sets. Some columns are used as a key and rest of columns as a value. Idea of this library is simple. We can prepare these maps once (sort by key), store it to file and then use it as memory mapped file. Searching key in sorted file has log(n) complexity. If more processes uses the same memory mapped file, it exists in memory just once (on Linux). This file can be loaded lazy by OS.

In some data processing tasks we need to use huge maps or sets that are bigger than available JVM heap space or they are loading too slow to standard Java or Scala Maps. We use TSV format (text file with tab separated columns) for persist this kind of Maps or Sets. Some columns are used as a key and rest of columns as a value. Idea of this library is simple. We can prepare these maps once (sort by key), store it to file and then use it as memory mapped file. Searching key in sorted file has log(n) complexity. If more processes uses the same memory mapped file, it exists in memory just once (on Linux). This file can be loaded lazy by OS.

Information extraction is the process of identifying specified classes of entities, relations, and events in natural language text – creating structured data from unstructured input. JET, the Java Extraction Toolkit, developed at New York University over the past fifteen years, provides a rich set of tools for research and education in information extraction from English text. These include standard language processing tools such as a tokenizer, sentence segmenter, part-of-speech tagger, name tagger, regular-expression pattern matcher, and dependency parser. Also provided are relation and event extractors based on the specifications of the U.S. Government's ACE [Automatic Content Extraction] program. The program is provided under an Apache 2.0 license.

The Universal Java Matrix Package (UJMP) is an open source library for dense and sparse matrix computations and linear algebra in Java. In addition to the basic operations like matrix multiplication, matrix inverse or decomposition methods, it also supports visualization, JDBC import/export and many other useful functions such as mean, correlation, standard deviation, mutual information, or the replacement of missing values. It's a swiss army knife for data processing in Java, tailored to machine learning applications.