Download JAR files tagged by properties with all dependencies

Graal is a java toolkit dedicated to ontological query answering in the framework of existential rules. We consider knowledge bases composed of data and an ontology expressed by existential rules. The main features of Graal are the following: a basic layer that provides generic interfaces to store and query various kinds of data, forward chaining and query rewriting algorithms, structural analysis of decidability properties of a rule set, a textual format and its parser, and import of OWL 2 files. We describe in more detail the query rewriting algorithms, which rely on original techniques, and report some experiments.

This module contains library classes for accessing the ThreadFix REST API. The ThreadFix IDE plugins use this library to retrieve application and vulnerability marker information, and in the ThreadFix scanner plugins to get endpoint information and upload scans to ThreadFix applications. The easiest way to start using the library is with the PluginClient or ThreadFixRestClient classes. Both have constructors that take a PropertiesManager instance, which holds the ThreadFix API key and url information. The default PropertiesManager implementation stores these properties in threadfix.properties, but the ThreadFix plugins extend the default PropertiesManager class to override this behavior for the target platform.

It helps to quickly make settings for class and its fields of with properties XML. Instead of create a lot of files to describe every class and its fields it use describing by type, by name. E.g. setting "java.lang.Integer"-"INTEGER NOT NULL" will be assigned fo every field of this type. Of course it can be overriden by settings for field name and so on. It is used by beige-web to describe how to render an entity and convert from HTML value. It is used by beige-orm to describe how to map an entity to a DBMS. It make simple settings - Map<String, String>, e.g. "title"-"Beige ORM 1.1", class settings Map<String, Map<String, String>>, e.g. "org.mode.Customer"-["defaultOrder"-"ITSNAME", "wdgFilterOrder"-"filterOrderStd"], fields settings Map<String, Map<String, Map<String, String>>>, e.g. "org.mode.Customer"-["itsId"["wdgNew"-"null", "wdgFilter"-"filterNumber"]]

We propose two efficient algorithms for exploring topic diversity in large document corpora such as user generated content on the social web, bibliographic data, or other web repositories. Analyzing diversity is useful for obtaining insights into knowledge evolution, trends, periodicities, and topic heterogeneity of such collections. Calculating diversity statistics requires averaging over the similarity of all object pairs, which, for large corpora, is prohibitive from a computational point of view. Our proposed algorithms overcome the quadratic complexity of the average pair-wise similarity computation, and allow for constant time (depending on dataset properties) or linear time approximation with probabilistic guarantees.