Linking socially contributed media with events
Abstract Recent years have witnessed the blooming of Web 2.0 content such as Flickr and YouTube, etc. How we can benefit from such rich media resources is still an open and challenging question. In this paper, we present a method combining semantic inferencing and visual analysis for automatically f...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Liu, Xueliang [verfasserIn] |
|---|
| Format: |
Artikel |
|---|---|
| Sprache: |
Englisch |
| Erschienen: |
2014 |
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| Schlagwörter: |
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| Anmerkung: |
© Springer-Verlag Berlin Heidelberg 2014 |
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| Übergeordnetes Werk: |
Enthalten in: Multimedia systems - Springer Berlin Heidelberg, 1993, 22(2014), 4 vom: 04. Nov., Seite 433-442 |
|---|---|
| Übergeordnetes Werk: |
volume:22 ; year:2014 ; number:4 ; day:04 ; month:11 ; pages:433-442 |
| Links: |
|---|
| DOI / URN: |
10.1007/s00530-014-0436-3 |
|---|
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OLC2071073398 |
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| 520 | |a Abstract Recent years have witnessed the blooming of Web 2.0 content such as Flickr and YouTube, etc. How we can benefit from such rich media resources is still an open and challenging question. In this paper, we present a method combining semantic inferencing and visual analysis for automatically finding media (photos and videos) illustrating events. We report on experiments validating our heuristic for mining media sharing platforms and large event directories in order to mutually enrich the descriptions of the content they host. Our overall goal is to design a Web-based environment that allows users to explore and select events, to inspect associated media, and to discover meaningful, surprising or entertaining connections between events, media and people participating in events. We present a large dataset composed of semantic descriptions of events, photos and videos interlinked with the larger Linked Open Data cloud and we show the benefits of using semantic Web technologies for integrating multimedia metadata. | ||
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Abstract Recent years have witnessed the blooming of Web 2.0 content such as Flickr and YouTube, etc. How we can benefit from such rich media resources is still an open and challenging question. In this paper, we present a method combining semantic inferencing and visual analysis for automatically finding media (photos and videos) illustrating events. We report on experiments validating our heuristic for mining media sharing platforms and large event directories in order to mutually enrich the descriptions of the content they host. Our overall goal is to design a Web-based environment that allows users to explore and select events, to inspect associated media, and to discover meaningful, surprising or entertaining connections between events, media and people participating in events. We present a large dataset composed of semantic descriptions of events, photos and videos interlinked with the larger Linked Open Data cloud and we show the benefits of using semantic Web technologies for integrating multimedia metadata. © Springer-Verlag Berlin Heidelberg 2014 |
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Abstract Recent years have witnessed the blooming of Web 2.0 content such as Flickr and YouTube, etc. How we can benefit from such rich media resources is still an open and challenging question. In this paper, we present a method combining semantic inferencing and visual analysis for automatically finding media (photos and videos) illustrating events. We report on experiments validating our heuristic for mining media sharing platforms and large event directories in order to mutually enrich the descriptions of the content they host. Our overall goal is to design a Web-based environment that allows users to explore and select events, to inspect associated media, and to discover meaningful, surprising or entertaining connections between events, media and people participating in events. We present a large dataset composed of semantic descriptions of events, photos and videos interlinked with the larger Linked Open Data cloud and we show the benefits of using semantic Web technologies for integrating multimedia metadata. © Springer-Verlag Berlin Heidelberg 2014 |
| abstract_unstemmed |
Abstract Recent years have witnessed the blooming of Web 2.0 content such as Flickr and YouTube, etc. How we can benefit from such rich media resources is still an open and challenging question. In this paper, we present a method combining semantic inferencing and visual analysis for automatically finding media (photos and videos) illustrating events. We report on experiments validating our heuristic for mining media sharing platforms and large event directories in order to mutually enrich the descriptions of the content they host. Our overall goal is to design a Web-based environment that allows users to explore and select events, to inspect associated media, and to discover meaningful, surprising or entertaining connections between events, media and people participating in events. We present a large dataset composed of semantic descriptions of events, photos and videos interlinked with the larger Linked Open Data cloud and we show the benefits of using semantic Web technologies for integrating multimedia metadata. © Springer-Verlag Berlin Heidelberg 2014 |
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Linking socially contributed media with events |
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