Showing 6 open source projects for "recommender"

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  • 1
    Vespa

    Vespa

    The open big data serving engine

    ...You can even combine both approaches efficiently in the same query, something no other engine can do. Recommendation, personalization and targeting involves evaluating recommender models over content items to select the best ones. Vespa lets you build applications which does this online, typically combining fast vector search and filtering with evaluation of machine-learned models over the items. This makes it possible to make recommendations specifically for each user or situation, using completely up to date information.
    Downloads: 2 This Week
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  • 2
    MOA - Massive Online Analysis

    MOA - Massive Online Analysis

    Big Data Stream Analytics Framework.

    A framework for learning from a continuous supply of examples, a data stream. Includes classification, regression, clustering, outlier detection and recommender systems. Related to the WEKA project, also written in Java, while scaling to adaptive large scale machine learning.
    Downloads: 32 This Week
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  • 3
    LibRec

    LibRec

    Leading Java Library for Recommender Systems

    LibRec is a Java library for recommender systems (Java version 1.7 or higher required). It implements a suit of state-of-the-art recommendation algorithms, aiming to resolve two classic recommendation tasks: rating prediction and item ranking.
    Downloads: 0 This Week
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  • 4

    Information Retrieval Service Assessment

    IRSA is a toolkit for Information Retrieval Service Assessment.

    ...It builds upon the Grails Web Framework and is developed at GESIS. It implements two main functionalities: (1) A number of showcases that show the implemented services like a so-called Search Term Recommender and different science-model based ranking mechanisms and (2) an IR assessment module that let's one do an interactive evaluation of the retrieval services. All implemented services are available via well-documented RESTful API. This toolkit is distributed under an Apache License 2.0.
    Downloads: 0 This Week
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  • 5
    The Idealize Recommendation Framework supports the development of recommender systems. We have devised a set of requirements all recommender systems must address, an architecture for those requirements, a technical vocabulary and a production model.
    Downloads: 0 This Week
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  • 6
    The Duine Framework allows one to develop prediction engines for recommender systems. It contains a set of prediction techniques, a way to combine these techniques and a profile manager. The framework has a plug-in architecture, allowing customization.
    Downloads: 0 This Week
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