Download JAR files tagged by word with all dependencies

The data-mining project contains Peregrine and several supporting modules, e.g. for ontologies and datasets. Peregrine is an indexing engine or tagger: a piece of software that can be used to recognize concepts in human readable text, based on a database (thesaurus) of known terms. Multi-word terms are correctly recognized. If terms can represent multiple concepts, Peregrine will attempt to disambiguate them.

Stanford CoreNLP provides a set of natural language analysis tools which can take raw English language text input and give the base forms of words, their parts of speech, whether they are names of companies, people, etc., normalize dates, times, and numeric quantities, mark up the structure of sentences in terms of phrases and word dependencies, and indicate which noun phrases refer to the same entities. It provides the foundational building blocks for higher level text understanding applications.

The ConvertAPI helps converting various file formats. Creating PDF and Images from various sources like Word, Excel, Powerpoint, images, web pages or raw HTML codes. Merge, Encrypt, Split, Repair and Decrypt PDF files. And many others files manipulations. In just few minutes you can integrate it into your application and use it easily. The ConvertAPI client library makes it easier to use the Convert API from your Java 8 projects without having to build your own API calls.

The bit array data structure is implemented in Java as the BitSet class. Unfortunately, this fails to scale without compression. JavaEWAH is a word-aligned compressed variant of the Java bitset class. It uses a 64-bit run-length encoding (RLE) compression scheme. The goal of word-aligned compression is not to achieve the best compression, but rather to improve query processing time. Hence, we try to save CPU cycles, maybe at the expense of storage. However, the EWAH scheme we implemented is always more efficient storage-wise than an uncompressed bitmap (implemented in Java as the BitSet class). Unlike some alternatives, javaewah does not rely on a patented scheme.

This project is a resource for the JCoRe Linnaeus Annotator. The dictionaries contained herein are used for the recognition of concrete species names in text, e.g. "human", "mouse", "n. furzeri", "c. elegans" etc as well as species hints, i.e. indirect clues to a species like the word "patient" which most likely refers to a human. Additionally to such rather clear proxies, this project also includes a small dictionary containing maximum-frequency-proxies for genus expressions like "Drosophila" which will be mapped to "D. melanogaster". For the task of only finding concrete species names in text, there is the project jcore-linnaeus-species-ae-species-dict.

This module provides a convenient way to convert string case. <h3>Usage</h3> In the editor panel: <ol> <li>Select the text you want to change the case of</li> <li>Right-click to open the contextual menu</li> <li>Open the <code>Convert To...</code> submenu</li> <li>Click on the converter of your choice</li> </ol> Please note that if no text is selected, the menu is disabled. <h3>Available converters</h3> <ul> <li><b>camelCase</b>: first capitalized letter of each word, except for the first letter of the resulting word, no space</li> <li><b>hyphen-case</b>: lower case words separated with an hyphen</li> <li><b>lower case</b>: lower case words</li> <li><b>PascalCase</b>: first capitalized letter of each word, no space</li> <li><b>Sentence case.</b>: first capitalized letter of the first word, ends with a dot (capital letters within the sentence are preserved)</li> <li><b>snake_case</b>: lower case words separated with an underline character</li> <li><b>Title Case</b>: first capitalized letter of each word, one space between words</li> <li><b>UPPER CASE</b>: upper case words</li> </ul>