Recommender System Based on Linked Data.
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| Title: | Recommender System Based on Linked Data. |
|---|---|
| Description: | Linked Data principles have led to semantically interlink and connect different resourcesat data level regardless the structure, authoring, location etc. Data available on the Web using Linked Data has resulted in a global data space called the Web of Data. Moreover, thanks to the efforts of the scientific community and the W3C Linked Open Data (LOD) project, more and more data have been published on the Web of Data, helping its growth and evolution. This book studies Recommender Systems that use LInked Data as a source for generating recommendations exploiting the large amount of available resources and the relationships between them. Firts, a comprehensive state of the art is preseted in order to indetify and study frameworks and algorithms for RS that rely on Linked Data. Second a framework named AlLied taht makes available implementations of the most used algortihms for resource recommendation based on Linked Data is described. This framework is inteded to use and test the recommendation algorithms in various domains and contexts, and to analyze their behavior under different conditions. Accordingly the framework is suitable to compare the results of these algorithms both in performance and relevance, and to enable the development of innovative applications on top of it. |
| Authors: | Figueroa, Cristhian, Corrales, Juan Carlos, Morisio, Maurizio |
| Resource Type: | eBook. |
| Subjects: | Application software--Development, Data structures (Computer science), Algorithms, Linked data |
| Categories: | COMPUTERS / General |
| Database: | eBook Collection (EBSCOhost) |
| FullText | Links: – Type: ebook-pdf Text: Availability: 0 |
|---|---|
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| Items | – Name: Title Label: Title Group: Ti Data: Recommender System Based on Linked Data. – Name: Abstract Label: Description Group: Ab Data: Linked Data principles have led to semantically interlink and connect different resourcesat data level regardless the structure, authoring, location etc. Data available on the Web using Linked Data has resulted in a global data space called the Web of Data. Moreover, thanks to the efforts of the scientific community and the W3C Linked Open Data (LOD) project, more and more data have been published on the Web of Data, helping its growth and evolution. This book studies Recommender Systems that use LInked Data as a source for generating recommendations exploiting the large amount of available resources and the relationships between them. Firts, a comprehensive state of the art is preseted in order to indetify and study frameworks and algorithms for RS that rely on Linked Data. Second a framework named AlLied taht makes available implementations of the most used algortihms for resource recommendation based on Linked Data is described. This framework is inteded to use and test the recommendation algorithms in various domains and contexts, and to analyze their behavior under different conditions. Accordingly the framework is suitable to compare the results of these algorithms both in performance and relevance, and to enable the development of innovative applications on top of it. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Figueroa%2C+Cristhian%22">Figueroa, Cristhian</searchLink><br /><searchLink fieldCode="AR" term="%22Corrales%2C+Juan+Carlos%22">Corrales, Juan Carlos</searchLink><br /><searchLink fieldCode="AR" term="%22Morisio%2C+Maurizio%22">Morisio, Maurizio</searchLink> – Name: TypePub Label: Resource Type Group: TypPub Data: eBook. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Application+software--Development%22">Application software--Development</searchLink><br /><searchLink fieldCode="DE" term="%22Data+structures+%28Computer+science%29%22">Data structures (Computer science)</searchLink><br /><searchLink fieldCode="DE" term="%22Algorithms%22">Algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Linked+data%22">Linked data</searchLink> – Name: SubjectBISAC Label: Categories Group: Su Data: <searchLink fieldCode="ZK" term="%22COMPUTERS+%2F+General%22">COMPUTERS / General</searchLink> |
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| RecordInfo | BibRecord: BibEntity: Classifications: – Code: 005.1 Scheme: ddc Type: prePub Languages: – Code: eng Text: English Subjects: – SubjectFull: Application software--Development Type: general – SubjectFull: Data structures (Computer science) Type: general – SubjectFull: Algorithms Type: general – SubjectFull: Linked data Type: general Titles: – TitleFull: Recommender System Based on Linked Data. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Figueroa, Cristhian – PersonEntity: Name: NameFull: Corrales, Juan Carlos – PersonEntity: Name: NameFull: Morisio, Maurizio – PersonEntity: Name: NameFull: Figueroa, Cristhian – PersonEntity: Name: NameFull: Corrales, Juan Carlos – PersonEntity: Name: NameFull: Morisio, Maurizio IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 01 Type: published Y: 2019 – D: 25 M: 08 Type: profile Y: 2022 Identifiers: – Type: isbn-print Value: 9789587323801 – Type: isbn-electronic Value: 9789587323818 Titles: – TitleFull: Recommender System Based on Linked Data. Type: main |
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