LightSide

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Lightside research title.png


LightSide Researcher's Workbench

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Developed by: Carnegie Mellon University’s Language Technologies Institute
License: GPL / GNU General Public License
Web page : Tool homepage
Tool type : Application software

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The last edition of this page was on: 2014/09/22

The Completion level of this page is : Low


SHORT DESCRIPTION

[[has description::“The open-source LightSide platform, including the machine-learning and feature-extraction core as well as the researcher's workbench UI, has been and continues to be funded in part through Carnegie Mellon University, in particular by grants from the National Science Foundation and the Office of Naval Research.” (LightSide home page, sept. 2014).]]


TOOL CHARACTERISTICS

Usability

Authors of this page consider that this tool is somewhat difficult to use.

Tool orientation

This tool is designed for general purpose analysis.

Data mining type

This tool is made for Text mining.

Manipulation type

This tool is designed for Data analysis.

IMPORT FORMAT :

EXPORT FORMAT :


Tool objective(s) in the field of Learning Sciences

Analysis & Visualisation of data
Predicting student performance
Student modelling
Social Network Analysis (SNA)
Constructing courseware

Providing feedback for supporting instructors:
Recommendations for students
Grouping students:
Developing concept maps:
Planning/scheduling/monitoring
Experimentation/observation

Tool can perform:

  • Data extraction of type:
  • Transformation of type:
  • Data analysis of type: Data mining methods and algorithms
  • Data visualisation of type: (These visualisations can be interactive and updated in "real time")



ABOUT USERS

Tool is suitable for:

Students/Learners/Consumers
Teachers/Tutors/Managers
Researchers
Developers/Designers
Organisations/Institutions/Firms
Others

Required skills:

STATISTICS: Basic

PROGRAMMING: Basic

SYSTEM ADMINISTRATION: Basic

DATA MINING MODELS: Medium



FREE TEXT


Tool version : LightSide Researcher's Workbench
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Developed by : Carnegie Mellon University’s Language Technologies Institute
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Tool Web page : http://ankara.lti.cs.cmu.edu/side/
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Tool type : Application software
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License:GPL / GNU General Public License

No image.png

SHORT DESCRIPTION


“The open-source LightSide platform, including the machine-learning and feature-extraction core as well as the researcher's workbench UI, has been and continues to be funded in part through Carnegie Mellon University, in particular by grants from the National Science Foundation and the Office of Naval Research.” (LightSide home page, sept. 2014).

TOOL CHARACTERISTICS


Tool orientation Data mining type Usability
This tool is designed for general purpose analysis. This tool is designed for Text mining. Authors of this page consider that this tool is somewhat difficult to use.
Data import format Data export format
. .
Tool objective(s) in the field of Learning Sciences

☑ Analysis & Visualisation of data
☑ Predicting student performance
☑ Student modelling
☑ Social Network Analysis (SNA)
☑ Constructing courseware

☑ Providing feedback for supporting instructors:
☑ Recommendations for students
☑ Grouping students:
☑ Developing concept maps:
☑ Planning/scheduling/monitoring
Experimentation/observation

Can perform data extraction of type:

Can perform data transformation of type:


Can perform data analysis of type:
Data mining methods and algorithms


Can perform data visualisation of type:
(These visualisations can be interactive and updated in "real time")


ABOUT USER


Tool is suitable for:
Students/Learners/Consumers:☑ Teachers/Tutors/Managers:☑ Researchers:☑ Organisations/Institutions/Firms:☑ Others:☑
Required skills:
Statistics: BASIC Programming: BASIC System administration: BASIC Data mining models: MEDIUM

OTHER TOOL INFORMATION


No screenshot.jpg
Lightside research title.png
LightSide Researcher's Workbench
GPL / GNU General Public License
Free&Open source
Carnegie Mellon University’s Language Technologies Institute
http://ankara.lti.cs.cmu.edu/side/
[[has description::“The open-source LightSide platform, including the machine-learning and feature-extraction core as well as the researcher's workbench UI, has been and continues to be funded in part through Carnegie Mellon University, in particular by grants from the National Science Foundation and the Office of Naval Research.” (LightSide home page, sept. 2014).]]
General analysis
Researchers
Basic
Basic
Basic
Medium
Application software
Text mining
Data analysis
Data mining methods and algorithms
somewhat difficult to use
Low

Manuals and Download

Short how to

Lightside is based on machine learning algorightms that can learn to extract features (e.g. tag text) based on training examples entered by humans.

Below is a longer, slightly modified quote from the [http://ankara.lti.cs.cmu.edu/side/LightSide_Researchers_Manual.pdf Manual (feb 2014):

“LightSide is divided into a series of six tabs following the entire process of machine learning. In the first, Extract Features, training documents are converted into feature tables. Next, in Restructure Plugins, we have built several tools which allow users to manually adjust the resulting feature tables. In Build Model, the third tab, modern algorithms are used to discover latent patterns in that feature table. The classifier that results is able to reproduce human annotation.”

“The next three tabs allow users to explore those trained models and use them to annotate new data. In the fourth tab, Explore Results, offers error analysis tools that allow researchers to understand what their models do well and why they fail in some cases. The fifth, Compare Results, allows users to look at specific differences between two different trained models to understand both gaps in performance as a whole and individually. The final tab, Predict Labels, allows us to use the resulting trained models to annotate new data that no humans have labeled.”

“The simplest workflow, for those with basic machine learning needs, comes from the first and third tabs. In each case we progress from an input data structure to an output data structure: Documents → Extract Features → Feature Table → Build Model → Trained Model

The training file is in CSV format. The first line contains the data fields, e.g. class and text. Each row contains an example.

Other products:

On the basis of LightSide Researcher's benchmark, there are two commercial products: