Search Results for "recommender"
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Showing 15 open source projects for "recommender"
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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. -
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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. -
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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. -
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easyrec is a recommender system that aims for easy integration of recommendations into web applications. It has a web based admin tool, and its recommendation engine is accessible through a REST API, providing methods like 'other users also bought'
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MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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ReSPARQL - RecSPARQL
SPARQL extension for recommendations
SPARQL, a declarative query language for querying RDF-graphs, supports retrieval of data exclusively based on facts; in contrast Recommender Systems aim to predict the taste of a user towards a set of not consumed items. However, predictions or suggestions are entities that cannot be explicitly retrieved. ReSPARQL is an extension of SPARQL that fills the gap between this two paradigms and enables a generic and flexible approach for recommendations over arbitrary RDF-graphs. -
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iTEC SDE
A recommender system for Educational Resources (iTEC Project)
The SDE is a software system based on semantic technologies that manages its own information models expressed as RDF triples. The SDE is a software package whose services are transparently integrated with the ones offered by the iTEC Composer (iTEC Project - http://itec.eun.org) to extend its functionality by providing recommendations to support the selection of resources. Therefore, the SDE does not provide an actual user interface, as other components in the iTEC Cloud will manage the... -
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This is a privacy preserving URL Recommender Application Client Software. It can be used by students of IIT Kharagpur only, as the server side part is hosted inside IIT Kharagpur.
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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. -
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Game recommender
A game recommender engine in Java.
Built in 2007 with I.Argyropoulos. Rule based, 1st order relational logic. -
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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.
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This is a university project - a mobile city guide using a recommender system in order to create tours for a user, based on his/her likes/dislikes. The user can rate all the POI visited and by this mean provide information to the recommender.
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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.
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The Open Education Resource Recommender (oerrecommender) is specifically designed to assist in locating other educational resources. A Greasemonkey script is also used to allow loading of dynamic resources.
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Debommender is a recommender system for Debian packages, making it easier for its users to find packages which are relevant to their specific needs.
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Gusto will provide the next generation of engines for recommender systems based on collaborative filtering and semantic web.
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