Property:Has description
Jump to navigation
Jump to search
This is a property of type Text.
A
Quote from the [http://www.personal.psu.edu/rbc4/score.htm software home page] (11/2014): Here is a software tool that can translate written text summaries directly into proximity files (prx) that can be analyzed by [http://interlinkinc.net/KNOT.html Pathfinder KNOT]. It also generates text proposition files that can be imported by [http://cmap.ihmc.us/download/ CMAP Tools] to automatically form concept maps from the text. It should be of use to researchers who want to visualize "text" for various instructional and research-related reasons. Also it should work with different languages.
ALA-Reader contains a rudimentary scoring system. Essentially, this tool converts the written summary into a cognitive map and then scores the cognitive map using an approach that we developed for scoring concept maps. The "score" produced is percent agreement with an expert referent. As I narrow down what algorithms work, then I plan to release updated versions periodically. +
AntConc is a freeware concordance program for Windows, Macintosh OS X, and Linux.
The software includes seven tools:
Concordance Tool: shows search results in a 'KWIC' (KeyWord In Context) format.
Concordance Plot Tool: shows search results plotted as a 'barcode' format. This allows you to see the position where search results appear in target texts.
File View Tool: This tool shows the text of individual files. This allows you to investigate in more detail the results generated in other tools of AntConc.
Clusters/N-Grams: hows clusters based on the search condition. In effect it
summarizes the results generated in the Concordance Tool or Concordance Plot
Tool. The N-Grams Tool, on the other hand, scans the entire corpus for 'N' (e.g. 1
word, 2 words, …) length clusters. This allows you to find common expressions in
a corpus.
Collocates: shows the collocates of a search term. This allows you to investigate non-sequential patterns in language.
Word List: counts all the words in the corpus and presents them in an ordered list. This allows you to quickly find which words are the most frequent in a corpus.
Keyword List: shows the which words are unusually frequent (or infrequent) in the corpus in comparison with the words in a reference corpus. This allows you to identify characteristic words in the corpus, for example, as part of a genre or ESP study. +
According to the [http://mahout.apache.org/ home page] (oct 1 2014):
The Apache Mahout™ project's goal is to build a scalable machine learning library.
Quote: <span style="background-color:#eeeeee" class="citation">“Currently Mahout supports mainly three use cases: Recommendation mining takes users' behavior and from that tries to find items users might like. Clustering takes e.g. text documents and groups them into groups of topically related documents. Classification learns from exisiting categorized documents what documents of a specific category look like and is able to assign unlabelled documents to the (hopefully) correct category.”</span> +
The Apache OpenNLP library is a machine learning based toolkit for the processing of natural language text.
It supports the most common NLP tasks, such as tokenization, sentence segmentation, part-of-speech tagging, named entity extraction, chunking, parsing, and coreference resolution. These tasks are usually required to build more advanced text processing services. OpenNLP also includes maximum entropy and perceptron based machine learning. +
Features
* A rich set of data visualizations
* An easy-to-use interface for exploring and visualizing data
* Create and share dashboards
* Enterprise-ready authentication with integration with major authentication providers (database, OpenID, LDAP, OAuth & REMOTE_USER through Flask AppBuilder)
* An extensible, high-granularity security/permission model allowing intricate rules on who can access individual features and the dataset
* A simple semantic layer, allowing users to control how data sources are displayed in the UI by defining which fields should show up in which drop-down and which aggregation and function metrics are made available to the user
* Integration with most SQL-speaking RDBMS through SQLAlchemy
* Deep integration with Druid.io
This project was originally named Panoramix, was renamed to Caravel in March 2016, and is currently named Superset as of November 2016 +
Unstructured Information Management Architecture (UIMA) is a component framework to analyze unstructured content such as text, audio and video. This is originally developed by IBM.
UIMA enables applications to be decomposed into components, for example “language identification” => “language specific segmentation” => “sentence boundary detection” => Each component implements interfaces defined by the framework and provides self describing metadata via XML descriptor files. Also provides capabilities to wrap components as network services, and can scale to very large volumes by replicating processing pipelines over a cluster of networked nodes. +
B
Real-time system that automatically collects student engagement and attendance & provides analytics tools and dashboards for students, teachers & management.
See :[http://startups.fm/2013/03/25/5-pressing-educational-problems-beestars-location-intelligence-platform-solves.html 5 pressing educational problems Beestar’s Location Intelligence Platform solves] +
Quote from the [http://www.bitext.com/ home page] (11/2014): Bitext provides B2B multilingual semantic engines with “documentably” the highest accuracy in the market. Bitext works for companies in two main markets: Text Analytics (Concept and Entity Extraction, Sentiment Analysis) for Social CRM, Enterprise Feedback Management or Voice of the Customer; and in Natural Language Interfaces for Search Engines. +
C
Cytoscape is an open source software platform for visualizing molecular interaction networks and biological pathways and integrating these networks with annotations, gene expression profiles and other state data. Although Cytoscape was originally designed for biological research, now it is a general platform for complex network analysis and visualization. Cytoscape core distribution provides a basic set of features for data integration, analysis, and visualization.
Additional features are available as Apps (formerly called Plugins). Apps are available for network and molecular profiling analyses, new layouts, additional file format support, scripting, and connection with databases. They may be developed by anyone using the Cytoscape open API based on Java™ technology and App community development is encouraged. Most of the Apps are freely available from Cytoscape App Store.
See [http://apps.cytoscape.org/ Cytoscape App store] +
D
'''DataMelt is a software environment for numeric calculations, statistics and data analysis '''
DataMelt, or DMelt, is an environment for numeric computation, data analysis and data visualization. DMelt is designed for analysis of large data volumes ("big data"), data mining, statistical analyses and math computations. The program can be used in many areas, such as natural sciences, engineering, modeling and analysis of financial markets.
DMelt is a computational platform: It can be used with different programming languages on different operating systems. Unlike other statistical programs, DataMelt is not limited by a single programming language. Data analysis and statistical computations can be done using high-level scripting languages (Python/Jython, Groovy, etc.), as well as a lower-level language, such as JAVA. It incorporates many open-source JAVA packages into a coherent interface using the concept of dynamic scripting.
DMelt creates high-quality vector-graphics images (SVG, EPS, PDF etc.) that can be included in LaTeX and other text-processing systems.
The program runs on Windows, Linux, Mac OS. +
According to the official [http://vialab.science.uoit.ca/docuburst/help.php help page] (3(2014), DocuBurst is an online document visualization tool, and can be used for:
* Uploading your own text documents
* Creating interactive visual summaries of documents
* Exploring keywords to uncover document themes or topics
* Investigating intra-document word patterns, such as character relationships
* Comparing documents
* Commenting, annotating and sharing visualizations with others +
The Dragon Toolkit is a Java-based development package for academic use in information retrieval (IR) and text mining (TM, including text classification, text clustering, text summarization, and topic modeling). It is tailored for researchers who work on large-scale IR and TM and prefer Java programming. Moreover, different from Lucene and Lemur, it provides built-in supports for semantic-based IR and TM. The dragon toolkit seamlessly integrates a set of NLP tools, which enable the toolkit to index text collections with various representation schemes including words, phrases, ontology-based concepts and relationships. ([dragon.ischool.drexel.edu/], retrieved March 2014) +
G
GATE is over 15 years old and is in active use for all types of computational task involving human language. GATE excels at text analysis of all shapes and sizes. From large corporations to small startups, from €multi-million research consortia to undergraduate projects, our user community is the largest and most diverse of any system of this type, and is spread across all but one of the continents ([http://gate.ac.uk/overview.html
GATE: a full-lifecycle open source solution for text processing]) +
Quote from the [http://radimrehurek.com/gensim/about.html about page] (12/2016): Gensim started off as a collection of various Python scripts for the Czech Digital Mathematics Library dml.cz in 2008, where it served to generate a short list of the most similar articles to a given article (gensim = “generate similar”). I also wanted to try these fancy “Latent Semantic Methods”, but the libraries that realized the necessary computation were not much fun to work with.
By now, gensim is—to my knowledge—the most robust, efficient and hassle-free piece of software to realize unsupervised semantic modelling from plain text. It stands in contrast to brittle homework-assignment-implementations that do not scale on one hand, and robust java-esque projects that take forever just to run “hello world”. +
Welcome to Gephi! Gephi is an open-source software for visualizing and analysing large networks graphs. Gephi uses a 3D render engine to display graphs in real-time and speed up the exploration. You can use it to explore, analyse, spatialise, filter, cluterize, manipulate and export all types of graphs. +
GISMO is a graphical interactive monitoring tool that provides visualization of students' activities in online courses to instructors. Instructors can examine various aspects of distance students, such as the attendance to courses, reading of materials, submission of assignments. Users of Moodle may benefit from GISMO for their teaching activities. With respect to the standard reports provided by Moodle (which basically allow teachers to see if an individual student has viewed a specific resource or participated on a specific activity on a specific day), GISMO provides comprehensive visualizations that gives an overview of the whole class, not only a specific student or a particular resource.
GISMO is available for Moodle 1.9.x. and Moodle 2.x. +
I
A website where you can visualise data such as numbers, text and geographic information. You can create a range of visualisations including unusual ones such as “treemaps” and “phrase nets”. All the charts made in Many Eyes are interactive, so you can change what data is shown and how it is displayed.
Many Eyes is also an online community where users can create topical groups to organise, share and discuss data visualisations. You can sign up to receive notifications when there are new visualisations or data on topics you are interested in.
Only being able to use Many Eyes if your data and the visualisations can be shared publicly on the Internet. +
A website where you can visualise data such as numbers, text and geographic information. You can create a range of visualisations including unusual ones such as “treemaps” and “phrase nets”. All the charts made in Many Eyes are interactive, so you can change what data is shown and how it is displayed.
Many Eyes is also an online community where users can create topical groups to organise, share and discuss data visualisations. You can sign up to receive notifications when there are new visualisations or data on topics you are interested in.
Only being able to use Many Eyes if your data and the visualisations can be shared publicly on the Internet. +
IRaMuTeQ stands for "Interface de R pour les Analyses Multidimensionnelles de Textes et de Questionnaires", in English, "interface of R for multi-dimensional text and questionnaire analysis".
Iramutec is built on top of [[R]]
As of oct 2014, there is only a french Interface, but the software can deal with English texts. +
J
Online tools to assist in the conversion of JSON to CSV. +
Quote from the [http://www.juxtasoftware.org/about/ About Page] (11/2014): <span style="background-color:#eeeeee" class="citation">“Juxta is an open-source tool for comparing and collating multiple witnesses to a single textual work. Originally designed to aid scholars and editors examine the history of a text from manuscript to print versions, Juxta offers a number of possibilities for humanities computing and textual scholarship. [...] As a standalone desktop application, Juxta allows users to complete many of the necessary operations of textual criticism on digital texts (TXT and XML). With this software, you can add or remove witnesses to a comparison set, switch the base text at will. Once you’ve collated a comparison, Juxta also offers several kinds of analytic visualizations. By default, it displays a heat map of all textual variants and allows the user to locate — at the level of any textual unit — all witness variations from the base text. Users can switch to a side by side collation view, which gives a split frame comparison of a base text with a witness text. A histogram of Juxta collations is particularly useful for long documents; this visualization displays the density of all variation from the base text and serves as a useful finding aid for specific variants.”</span> +
K
KEEL (Knowledge Extraction based on Evolutionary Learning) is an open source (GPLv3) Java software tool which empowers the user to assess the behavior of evolutionary learning and Soft Computing based techniques for different kinds of DM problems: regression, classification, clustering, pattern mining and so on.
See a complete description on [http://sci2s.ugr.es/keel/description.php KEEP website] +
KH Coder is an application for quantitative content analysis, text mining or corpus linguistics. It can handle Japanese, English, French, German, Italian, Portuguese and Spanish language data. By inputting the raw texts the searching and statistical analysis functionalities like KWIC, collocation statistics, co-occurrence networks, self-organizing map, multidimensional scaling, cluster analysis and correspondence analysis can be utilized. +
Quote from the [http://interlinkinc.net/KNOT.html software home page] (11(2014):
<div style="padding:2px;border-style:dotted;border-width:thin;margin-left:1em;margin-right:1em;margin-top:0.5ex;margin-bottom:0.5ex;">
The Knowledge Network Organizing Tool (KNOT) is built around the Pathfinder network generation algorithm. There are also several other components (see below). Pathfinder algorithms take estimates of the proximities between pairs of items as input and define a network representation of the items. The network (a PFNET) consists of the items as nodes and a set of links (which may be either directed or undirected for symmetrical or non-symmetrical proximity estimates) connecting pairs of the nodes. The set of links is determined by patterns of proximities in the data and parameters of Pathfinder algorithms. For details on the method and its applications see R. Schvaneveldt (Editor), Pathfinder Associative Networks: Studies in Knowledge Organization. Norwood, NJ: Ablex, 1990.
The Pathfinder software includes several programs and utilities to facilitate Pathfinder network analyses of proximity data. The system is oriented around producing pictures of the solutions, but representations of networks and other information are also available in the form of text files which can be used with other software. The positions of nodes for displays are computed using an algorithm described by Kamada and Kawai (1989, Information Processing Letters, 31, 7-15).</div> +
KNIME is a user-friendly graphical workbench for the entire analysis process: data access, data transformation, initial investigation, powerful predictive analytics, visualisation and reporting. The open integration platform provides over 1000 modules (nodes).
The open source version [http://www.knime.org/knime claims to implement] a very rich platform: <span style="background-color:#eeeeee" class="citation">“The KNIME Analytics Platform incorporates hundreds of processing nodes for data I/O, preprocessing and cleansing, modeling, analysis and data mining as well as various interactive views, such as scatter plots, parallel coordinates and others. It integrates all of the analysis modules of the well known [[Weka]] data mining environment and additional plugins allow R-scripts to be run, offering access to a vast library of statistical routines.”</span> +