Download JAR files tagged by data with all dependencies

The project provides an implementation of REPOSITORY PATTERN using HIBERNATE for data access. The goal of this project is to provide an EASY TO USE API that allows to write most of CRUD operations you need in development of end user applications in ONE LINE OF CODE even for developers who are unfamiliar with Hibernate. We provide a well tested set of CRUD operations which were assembled in more than 4 years of refactoring of projects of our clients. Instead of writing same code over and over again we encourage you to try this API on your own project and see how many lines of code YOU can replace with JUST ONE LINE.

JSON is a light-weight, language independent, data interchange format. See http://www.JSON.org/ The files in this package implement JSON encoders/decoders in Java. It also includes the capability to convert between JSON and XML, HTTP headers, Cookies, and CDL. This is a reference implementation. There is a large number of JSON packages in Java. Perhaps someday the Java community will standardize on one. Until then, choose carefully. The license includes this restriction: "The software shall be used for good, not evil." If your conscience cannot live with that, then choose a different package. The package compiles on Java 1.2 thru Java 1.4.

Jadex XML is an XML data binding framework for Java and also for other representations. The main idea of Jadex XML is that neither the XML-Schema on the one side nor the Java classes on the other side should define the binding. Instead, a separate mapping between both is used as a mediation. This allows designing the XML representation independent of the Java side but still being able to connect both as desired. This idea was first put forward by the JiBX data binding framework. Jadex XML pushes it further by combining it with the configuration by exception principle. The framework can detect obvious correspondences between both sides automatically and only needs configuration information when translations are necessary. The configuration information is currently specified directly in form of Java configuration classes.

This is an endorsed version of the original Deployment Client for Oracle GlassFish Open Source Edition. The purpose of the endorsement is to provide a shaded JAR which has the OSGI meta data removed because it causes the original Deployment Client to fail when used within a module running within a GlassFish container due to some class loader configuration conflicts between the container and the deployed module. This issue has been reported to the GlassFish project at https://java.net/jira/browse/GLASSFISH-20856 . It is hoped that it can get fixed so that this workaround project can get deprecated soon.

Reco4j is an open source project aims at developing a recommendation framework based on graph data sources. We choose graph databases for several reasons. They are NoSQL databases, so "schemaless". This means that it is possible to extend the basic data structure with intermediate information, i.e. similarity value between item and so on. Moreover, since every information is expressed with properties, nodes and relations, the recommendation process can be customized to work on every graph. Reco4j can be used on every graph where "user" and "item" is represented by node and the preferences are modelled as relationship between them. Current implementation leverage on Neo4j as first graph database integrated in our framework.

A filter that applies the LOF (Local Outlier Factor) algorithm to compute an outlier score for each instance in the data. Can use multiple cores/cpus to speed up the LOF computation for large datasets. Nearest neighbor search methods and distance functions are pluggable. For more information, see: Markus M. Breunig, Hans-Peter Kriegel, Raymond T. Ng, Jorg Sander (2000). LOF: Identifying Density-Based Local Outliers. ACM SIGMOD Record. 29(2):93-104.

A simple templating system for java codegen. This library includes an object-oriented, fluent source writing api, for a chained, intuitive codegen api. It also includes a template processor which can take java source files formatted with "magic comments", to allow simple mapping of GeneratorClass#generatorMethod() to inject dynamic source content. //@generateWith(GeneratorClass)// -Sets the current generator. You may use as many as you please //generatorMethod(arbitrary-string-data-you-may-want-to-parse)// -invokes the named method on the current injector, with any text (between brackets) sent as a string This allows you to markup default source with hooks where you may want to inject arbitrary code. It is especially useful for generating super-source in gwt compiles; changes to the default class are propagated to overrides.

This metaclassifier makes its base classifier cost-sensitive using the method specified in Pedro Domingos: MetaCost: A general method for making classifiers cost-sensitive. In: Fifth International Conference on Knowledge Discovery and Data Mining, 155-164, 1999. This classifier should produce similar results to one created by passing the base learner to Bagging, which is in turn passed to a CostSensitiveClassifier operating on minimum expected cost. The difference is that MetaCost produces a single cost-sensitive classifier of the base learner, giving the benefits of fast classification and interpretable output (if the base learner itself is interpretable). This implementation uses all bagging iterations when reclassifying training data (the MetaCost paper reports a marginal improvement when only those iterations containing each training instance are used in reclassifying that instance).

The biblio transformation engine is a java framework developed by the Hellenic National Documentation Centre (EKT, www.ekt.gr) and consists of programmatic APIs for filtering and modifying records that are retrieved from various types of data sources (eg. databases, files, legacy data sources) as well as for outputing them in appropriate standards formats (eg. database files, txt, xml, Excel). The framework includes independent abstract modules that are executed seperately, offering in many cases alternative choices to the user depending of the input data set, the transformation workflow that needs to be executed and the output format that needs to be generated.