Matches in ScholarlyData for { ?s ?p ?o. }
- 482 hasAuthorList authorList.
- 482 hasTopic World_Wide_Web.
- 482 isPartOf proceedings.
- 482 keyword "Fuzzy Ontology".
- 482 keyword "Fuzzy SPARQL".
- 482 keyword "Lightweight Ontology Language".
- 482 keyword "Scalable Query Answering".
- 482 keyword "Semantic Web".
- 482 title "Scalable Querying Services over Fuzzy Ontologies".
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- item-1 hasContent jeff-z-pan.
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- item-2 hasContent giorgos-stamou.
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- 485 creator like-liu.
- 485 creator long-hao-wang.
- 485 creator xing-xie.
- 485 creator yu-zheng.
- 485 type InProceedings.
- 485 label "Learning Transportation Mode from Raw GPS Data for Geographic Applications on the Web".
- 485 sameAs 485.
- 485 abstract "Geographic information has boomed a lot of novel applications on the Web, and global positioning system (GPS) plays important roles in bridging these Web applications and end users. Learning knowledge from users’ raw GPS data can provide rich context information for both geographic and mobile applications on the Web. However, so far, raw GPS data are still used directly without much understanding. In this paper, an approach based on supervised learning is proposed to automatically infer transportation mode from raw GPS data. The transportation mode, such as walking, driving etc, implied in a user’s GPS data can provide us valuable knowledge to understand the user. Our approach has been evaluated using the GPS data collected by 45 users over a period of six months. As a result, independent of information from geographic maps and other sensors, the proposed approach can not only accurately infer the transportation modes of each track but also correctly detect transitions between different transportation modes. The approach proposed in this paper has been deployed to our GeoLife system to help users understand GPS tracks and perform route recommendation for both Web/mobile users. It can also improve user experience on mobile devices by rendering information with different map scales based on the user’s present transportation mode.".
- 485 hasAuthorList authorList.
- 485 hasTopic World_Wide_Web.
- 485 isPartOf proceedings.
- 485 keyword "Classification".
- 485 keyword "GPS".
- 485 keyword "Geographic Applications".
- 485 keyword "Transportation Mode".
- 485 keyword "User Interface".
- 485 title "Learning Transportation Mode from Raw GPS Data for Geographic Applications on the Web".
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- item-1 hasContent yu-zheng.
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- 497 creator angelo-di-iorio.
- 497 creator fabio-vitali.
- 497 creator stefano-zacchiroli.
- 497 type InProceedings.
- 497 label "Wiki Content Templating for (lowercase) semantic web".
- 497 sameAs 497.
- 497 abstract "Wiki content templating enables reuse of content structures among wiki pages. In this paper we present a thorough study of this widespread feature, showing how its two state of the art models (functional and creational templating) are sub-optimal. We then propose a third, better, model called lightly constrained (LC) templating and show its implementation in the Moin wiki engine. We show how LC templating implementations are the appropriate technologies to push forward semantically rich web pages on the lines of (lowercase) semantic web and microformats.".
- 497 hasAuthorList authorList.
- 497 hasTopic World_Wide_Web.
- 497 isPartOf proceedings.
- 497 keyword "microformats".
- 497 keyword "semantic web".
- 497 keyword "template".
- 497 keyword "wiki engine".
- 497 title "Wiki Content Templating for (lowercase) semantic web".
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- item-1 hasContent angelo-di-iorio.
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