Results 151 to 160 of about 1,893,238 (188)

A Hybrid Recommendation Framework Exploiting Linked Open Data and Graph-based Features

Proceedings of the 25th Conference on User Modeling, Adaptation and Personalization, 2017
In this article we propose a hybrid recommendation framework based on classification algorithms as Random Forests and Naive Bayes. We fed the framework with several heterogeneous groups of features, and we investigate to what extent features gathered from the Linked Open Data (LOD) cloud (as the genre of a movie or the writer of a book)) as well as ...
MUSTO, CATALDO, SEMERARO, Giovanni, de GEMMIS, MARCO, LOPS, PASQUALE   +3 more
openaire   +2 more sources

Capturing the Age of Linked Open Data: Towards a Dataset-Independent Framework

2012 IEEE Sixth International Conference on Semantic Computing, 2012
An increasing amount of data are published and consumed on the Web according to the Linked Data paradigm. In such scenario, understanding if the data consumed are up-to-date is crucial. Outdated data are usually considered inappropriate for many crucial tasks, such as make the consumer confident that answers returned to a query are still valid at the ...
RULA, ANISA, PALMONARI, MATTEO LUIGI, MAURINO, ANDREA   +2 more
openaire   +3 more sources

An ETL Framework for Online Analytical Processing of Linked Open Data

2013
Growing amount of data are being published online in machinereadable formats, and LOD (Linked Open Data) has emerged as a way to share such data across Web resources. Since LOD data often contain numerical data, such as statistics, there is a growing demand to make OLAP (Online Analytical Processing) analysis over such data.
Hiroyuki Inoue, Toshiyuki Amagasa, Hiroyuki Kitagawa   +2 more
openaire   +1 more source

CAF-SIAL: Concept aggregation framework for structuring informational aspects of linked open data

2009 First International Conference on Networked Digital Technologies, 2009
Linked Open Data (LOD) is becoming an essential part of the Semantic Web. Although LOD has amassed large quantities of structured data from diverse, openly available data sources, there is still a lack of user-friendly interfaces and mechanisms for exploring this huge resource.
Atif Latif, Muhammad Tanvir Afzal, Anwar Us Saeed, Patrick Hoefler, Klaus Tochtermann   +4 more
openaire   +1 more source

A Framework for Storing and Providing Aggregated Governmental Linked Open Data

2012
The paradigm of publishing governmental data is shifting from data trapped in the private data silos to open data, or even linked open data, bringing the information consumers (citizens, companies) unrestricted access to the data and enabling the agile information aggregation, which has up to now not been possible.
Tomáš Knap, Martin Nečaský, Martin Svoboda   +2 more
openaire   +1 more source

Augmented context-based recommendation service framework using knowledge over the Linked Open Data cloud

Pervasive and Mobile Computing, 2015
This research proposes ACARDS (Augmented-Context bAsed RecommenDation Service) framework that is able to utilize knowledge over the Linked Open Data (LOD) cloud to recommend context-based services to users. To improve the level of user satisfaction with the result of the recommendation, the ACARDS framework implements a novel recommendation algorithm ...
Mye Sohn, Sunghwan Jeong, Jongmo Kim, Hyun Jung Lee   +3 more
openaire   +1 more source

A linked open data framework to enhance the discoverability and impact of culture heritage

Journal of Information Science, 2018
Cultural heritage institutions have recently begun to consider the benefits of sharing their collections using linked open data to disseminate and enrich their metadata. As datasets become very large, challenges appear, such as ingestion, management, querying and enrichment.
Candela, Gustavo, Escobar Esteban, María Pilar, Carrasco, Rafael C., Marco Such, Manuel   +3 more
openaire   +2 more sources

ExpLOD

Proceedings of the 10th ACM Conference on Recommender Systems, 2016
In this paper we present ExpLOD, a framework which exploits the information available in the Linked Open Data (LOD) cloud to generate a natural language explanation of the suggestions produced by a recommendation algorithm. The methodology is based on building a graph in which the items liked by a user are connected to the items recommended through the
Cataldo Musto, Fedelucio Narducci, Pasquale Lops, Marco De Gemmis, Giovanni Semeraro   +4 more
openaire   +1 more source

Data assimilation framework: Linking an open data assimilation library (OpenDA) to a widely adopted model interface (OpenMI)

Environmental Modelling & Software, 2014
Data assimilation optimally merges model forecasts with observations taking into account both model and observational uncertainty. This paper presents a new data assimilation framework that enables the many Open Model Interface (OpenMI) 2.0 .NET compliant hydrological models already available, access to a robust data assimilation library.
Marc E. Ridler, Nils van Velzen, Stef Hummel, Inge Sandholt, Anne Katrine Falk, Arnold Heemink, Henrik Madsen   +6 more
openaire   +1 more source

Feeding a Hybrid Recommendation Framework with Linked Open Data and Graph-Based Features

2017
In this article we propose a hybrid recommendation framework based on classification algorithms such as Random Forests and Naive Bayes, which are fed with several heterogeneous groups of features. We split our features into two classes: classic features, as popularity-based, collaborative and content-based ones, and extended features gathered from the ...
Cataldo Musto, Pasquale Lops, Marco de Gemmis, Giovanni Semeraro   +3 more
openaire   +1 more source