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Pdf2Dom is a PDF parser that converts the documents to a HTML DOM representation. The obtained DOM tree may be then serialized to a HTML file or further processed. The inline CSS definitions contained in the resulting document are used for making the HTML page as similar as possible to the PDF input. A command-line utility for converting the PDF documents to HTML is included in the distribution package. Pdf2Dom may be also used as an independent Java library with a standard DOM interface for your DOM-based applications or as an alternative parser for the CSSBox rendering engine in order to add the PDF processing capability to CSSBox.

MulTEx is a simple, but powerful framework for organizing exceptions and messages in a multi-tier Java software system. It offers the key features: Causal chains/trees as a means to capture low-level error information. Redundancy-free stack traces and message chains in the case of indirectly caused exceptions. Internationalized message texts and parameters for exceptions. Services for reporting an exception chain/tree onto streams and dialogs. A standard way for writing method bodies with regard to exceptions. A collection of utilities for centralized exception reporting.

HotSpot learns a set of rules (displayed in a tree-like structure) that maximize/minimize a target variable/value of interest. With a nominal target, one might want to look for segments of the data where there is a high probability of a minority value occuring (given the constraint of a minimum support). For a numeric target, one might be interested in finding segments where this is higher on average than in the whole data set. For example, in a health insurance scenario, find which health insurance groups are at the highest risk (have the highest claim ratio), or, which groups have the highest average insurance payout.

This is a simple Web Service Client library to call wide variety of web service behind HTTP. In theory it can support any interface or payload. On the request side, to convert java object to HTTP request components (URL, headers, body), templating is used which allows it to call XML, JSON, SOAP, REST or anyother custom interface. On the response side, it uses pluggable parser and a mapper to only extract the fields that are of interest for the client program. The parser currently supports JSON and XML and returns a collections tree.

This is an open source library for parsing text-based inputs. PARSER makes use of context-free grammars to validate and parse sentences. Having specified such a grammar, the library takes care of parsing text-based inputs and returns a tree of nodes that represents the parsed sentence. Furthermore, it provides ways for interpreting and refining the returned tree of nodes. In essence, the library aims to remove the pain of parsing and instead allow focusing on processing and interpreting parsed results.

ELKI is an open source (AGPLv3) data mining software written in Java. The focus of ELKI is research in algorithms, with an emphasis on unsupervised methods in cluster analysis and outlier detection. In order to achieve high performance and scalability, ELKI offers many data index structures such as the R*-tree that can provide major performance gains. ELKI is designed to be easy to extend for researchers and students in this domain, and welcomes contributions in particular of new methods. ELKI aims at providing a large collection of highly parameterizable algorithms, in order to allow easy and fair evaluation and benchmarking of algorithms.