Tools

Natural Language Processing

Stanford NLP Group: Stanford Phrasal

Stanford Phrasal is a a free Java implementation for phrase-based machine translation. It provides an easy to use API for implementating new decoding model features and supports unique capabilities such as translating using phrases that include gaps and conditional extraction of phrase-tables and lexical reordering models.

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Natural Language Processing

Stanford NLP Group: Stanford Tokenizer

Stanford Tokenizer is a free Java implementation for diving an English text into tokens such as words, and a part of the Stanford Natural Language Processing toolset. This tool is not available on its own, but is bundled with other tools in the same set, including Stanford Parser, Stanford Part-of-Speech Tagger, Stanford Named Entity Recognizer, and Stanford CoreNLP.

Rated 0.0 out of 5.

Natural Language Processing

Stanford NLP Group: Stanford Topic Modelling Toolbox

Stanford Topic Modelling Toolbox is a free collection of topic modelling tools, and a part of the Stanford Natural Language Processing toolset. It is designed for social scientists and other users who need to analyze datasets with a substantial textual component. This tool can accept and generate tab-separated and comma-separated values, and is designed to work in combination with spreadsheet programs like Excel.

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Search

Stanford NLP Group: Stanford Tregex and Tsurgeon

Stanford Tregex and Tsurgeon is a bundled pair of tools from the Stanford Natural Language Processing toolset. Tregex is a utility for using tree relationships and regular expressions to match patterns in trees, while Tsurgeon is a tree transformation language.

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Visualization

d3.js - Data Driven Documents

D3.js is a free, open source JavaScript library for manipulating documents with data utilizing HTML5, SVG and CSS3. It is designed to create visualizations that work with current web standards to make the best possible use of the most recent browsers without requiring a proprietary framework. This tool allows users to bind data to an Document Object Model (DOM) and apply data-driven transformations to the document.

Rated 0.0 out of 5.

Analysis

Stanford Vis Group: Data Wrangler

Data Wrangler is free web-based tool for interactive data cleaning and transformation. It takes raw data and transforms it into data tables for further analysis and cleaning. The results can be exported in a variety of data table formats, including Excel, R, Tableau and Protovis.

Rated 0.0 out of 5.

Visualization

Stanford Vis Group: Protovis

Protovis is a free, open source tool for composing custom views of data from simple elements such as bars or dots. Marks are defined through dynamic properties to allow inheritance, scales and layouts for simplified visualization construction. This tool uses JavaScript and SVG in order to ensure web-native visualizations. Protovis is no longer under active construction; many of the concepts used in its development have been implemented in its successor, D3.js.

Rated 0.0 out of 5.

Visualization

TagCrowd

TagCrowd is a tool for generating a frequency-based word cloud from a source text, with a free browser version available through the TagCrowd website. A commercial version may also be purchased, subject to a creative commons license.

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Visualization

TextArc

TextArc is a free visualization tool that represents an entire text on a single page. It has elements of an index, concordance and summary all in one place, encouraging the viewer to use its juxtapositions to uncover meaning. The web-based applet is preloaded with thousands of text collected from Project Gutenberg. Note: TextArc was designed for browsers circa 2002 and requires Java SE 6 to run.

Rated 5.0 out of 5.

Visualization

University of Maryland HCI Group: FeatureLens

FeatureLens is a free tool for visualizing and exploring patterns in text collections. This tool integrates the results of text-mining algorithms, and can assist in finding frequent words or ngrams, enabling the discovery of fuzzy repetition patterns. In addition, the tool will recommend features based on particular pattern types identified in the text.

Rated 0.0 out of 5.