PropertyRecommenderEvaluator | Evaluation Framework for Property Recommender Systems
kandi X-RAY | PropertyRecommenderEvaluator Summary
kandi X-RAY | PropertyRecommenderEvaluator Summary
PropertyRecommenderEvaluator is a Python library. PropertyRecommenderEvaluator has no bugs, it has no vulnerabilities, it has a Weak Copyleft License and it has low support. However PropertyRecommenderEvaluator build file is not available. You can download it from GitHub.
The PropertyRecommenderEvaluator is a python framework for the evaluation of property recommender systems which aim at supporting users in adding information in collaborative environments based on the triple format (subject, property, object). Consider a user on Wikidata who is currently in the process of editing the subject „Innsbruck“ (a city in Austria) and has already entered values for the properties mayor and the number of inhabitants. A recommender system may assist the user in recommending further properties which might also be suitable for the given subject (e.g., about the founding year of the city). These recommendations are traditionally derived from similar subjects (in regards to the properties used) which contain properties that are not yet used on the given subject.
The PropertyRecommenderEvaluator is a python framework for the evaluation of property recommender systems which aim at supporting users in adding information in collaborative environments based on the triple format (subject, property, object). Consider a user on Wikidata who is currently in the process of editing the subject „Innsbruck“ (a city in Austria) and has already entered values for the properties mayor and the number of inhabitants. A recommender system may assist the user in recommending further properties which might also be suitable for the given subject (e.g., about the founding year of the city). These recommendations are traditionally derived from similar subjects (in regards to the properties used) which contain properties that are not yet used on the given subject.
Support
Quality
Security
License
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Support
PropertyRecommenderEvaluator has a low active ecosystem.
It has 1 star(s) with 1 fork(s). There are 2 watchers for this library.
It had no major release in the last 6 months.
There are 1 open issues and 0 have been closed. There are no pull requests.
It has a neutral sentiment in the developer community.
The latest version of PropertyRecommenderEvaluator is current.
Quality
PropertyRecommenderEvaluator has no bugs reported.
Security
PropertyRecommenderEvaluator has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
License
PropertyRecommenderEvaluator is licensed under the LGPL-3.0 License. This license is Weak Copyleft.
Weak Copyleft licenses have some restrictions, but you can use them in commercial projects.
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PropertyRecommenderEvaluator releases are not available. You will need to build from source code and install.
PropertyRecommenderEvaluator has no build file. You will be need to create the build yourself to build the component from source.
Installation instructions are not available. Examples and code snippets are available.
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Currently covering the most popular Java, JavaScript and Python libraries. See a Sample of PropertyRecommenderEvaluator
PropertyRecommenderEvaluator Key Features
No Key Features are available at this moment for PropertyRecommenderEvaluator.
PropertyRecommenderEvaluator Examples and Code Snippets
No Code Snippets are available at this moment for PropertyRecommenderEvaluator.
Community Discussions
No Community Discussions are available at this moment for PropertyRecommenderEvaluator.Refer to stack overflow page for discussions.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install PropertyRecommenderEvaluator
You can download it from GitHub.
You can use PropertyRecommenderEvaluator like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
You can use PropertyRecommenderEvaluator like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
Support
Eva Zangerle, Martin Pichl, Wolfgang Gassler Databases and Information Systems Department of Computer Science University of Innsbruck firstname.lastname@uibk.ac.at http://dbis-informatik.uibk.ac.at.
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