Download JAR files tagged by rely with all dependencies

YET ANOTHER IMPLEMENTATION OF LEVENSHTEIN DISTANCE GenericLevenshtein is an implementation of Minimum Edit Distance, also called Levenshtein Distance, written by Ramon Ziai and Niels Ott. This algorithm is very popular and it is often used to compute the similarity of strings. The difference in the presented implementation is that it can operate on sequences of any Java object implementing equals(Object). So no matter if you want to compare genome sequences or sequences of numbers, or just strings, here you go! Furthermore, the costs of the replace, insert, and delete operations can be customized by implementing the simple WeightCalculator<T> interface. In that case it is not a requirement to rely on equals(Object) as your implementation can do whatever you like it to do in oder to compare objects.

JCQL is a tool allowing to generate boilerplate java code from existing cassandra schema. It is intended to be used with Cassandra 2.1+ due to support of UDTs (User Defined Types)/Tuples/Collections. Cassandra's UDTs/Tuples/Collections and an ability to introspect schema through java driver make it possible to automatically generate POJOs and corresponding mappers between database and java models. Properly generated java code saves development efforts and is less error-prone compared to hand coding. Accompanied with proper CI and deployment it can also guarantee consistency between database and java models at any point of application lifecycle from development to production rollout. JCQL does not rely on java reflection or annotations which means all discrepancies between actual cassandra schema and what client code expects it to be will be identified during compilation not at runtime in the middle of the night right after production release. No need to worry about Cassandra client code performance implications due to use of reflection.

Module that defines the HttpChannel API. HttpChannels abstract complex download and upload steps into a simple and easy to use NIO Channel. NIO Channels can be wrapped into an InputStream or OutputStream and used in any way you may find possible to. Aside from that, Channels can be used natively in most next-gen libraries, meaning that you don't even need to wrap anything, just start writing or reading data to or from the channel wth a ByteBuffer. Anyone using the library should try to rely on code from this module only and, only if necessary, on configuration classes that are implementation specific. Relying on any other resource or class is considered an error and should NOT be done. One of the most interesting usages of channels for uploads and download is that you can easily copy data straight from one channel to the other, with less than 10 lines of code! Also, channels allows the implementation of a "tee" mechanism, in which data redden from a single channel can be copied to several other channels on the fly!

DICTIONARY-BASED COMPOUND SPLITTER FOR GERMAN BananaSplit is a compound splitter for German that uses a dictionary resource. The dictionary can be either a simple word list, or a word list equipped with POS values, or an XML based dictionary. The original version was able to use GermaNet as a dictionary. This is useful in applications that rely on GermaNet anyway: no additional lexicon needs to be generated and held in memory. This was also the original purpose of BananaSplit. It served as a compound splitter for a tool called BananaRelation. BananaRelation cannot be published here as it makes heavy use of unpublished code by EML Research, Heidelberg. BananaSplit can either be used as a standalone application or it can be integrated into other Java programs (as a library). This program emerged from the seminar Lexical Semantic Processing in NLP (winter term 2005/2006) taught by Iryna Gurevych at the Seminar für Sprachwissenschaft, Tübingen. Both BananaSplit and BananaRelation were introduced to the seminar participants on 17th of December, 2005. The key algorithm for compound splitting is based on Langer (1998). The program came to use in Müller and Gurevych (2006). Please note that the program splits compounds into two parts only. Details are given in the documents linked below.

The OODT grid services (product and profile services) use CORBA or RMI as their underlying network transport. However, limitations of CORBA and RMI make them inappropriate for large-scale deployments. For one, both are procedural mechanisms, providing a remote interface that resembles a method call. This makes streaming of data from a service impossible, because there are limitations to the sizes of data structures that can be passed over a remote method call. Instead, repeated calls must be made to retrieve each block of a product, making transfer speeds horribly slow compared to HTTP or FTP. (Block-based retrieval of profiles was never implemented, resulting in out of memory conditions for large profile results, which is another problem.) Second, both CORBA and RMI rely on a central name registry. The registry makes an object independent of its network location, enabling a client to call it by name (looking up its last known location in the registry). However, this requires that server objects be able to make outbound network calls to the registry (through any outbound firewall), and that the registry accept those registrations (through any inbound firewall). This required administrative action at institutions hosting server objects and at the institution hosting the registry. Often, these firewall exceptions would change without notice as system adminstrators changed at each location (apparently firewall exceptions are poorly documented everywhere). Further, in the two major deployments of OODT (PDS and EDRN), server objects have almost never moved, nullifying any benefit of the registry. This project, OODT Web Grid Services, avoids the prolems of CORBA and RMI by using HTTP as the transport mechanism for products and profiles. Further, it provides a password-protected mechanism to add new sets of product and profile query handlers, enabling seamless activation of additional capabilities.