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Mashups are lightweight Web applications that enhance functionalities by combining and transforming online resources and services. Common examples include maps for real estate, hotel recommendations, and navigation tools. They can involve both client-side and server-side activities, necessitating an understanding of incoming resources such as services, statistics, text, and videos for optimal integration. Semantic annotations play a crucial role in evolving neutral mashups into branded semantic mashups, with deeper semantic processing like reasoning representing the next advancement. The chapters showcase the variety of real-life semantic mashups, starting with overviews of their environments and the regulations they encounter. Subsequent chapters delve into DBpedia, search engines, and the Web of Things, highlighting the primary contexts for mashups. While some chapters focus on enhancing search queries—relatable to everyday experiences—others explore less familiar developments using DBpedia and real-world sensor data. The book also examines diverse application areas, including mathematical knowledge, speech, crisis management, recommendations, urban information, and tourism. Authored by participants of the AI Mashup Challenge, the chapters aim to engage researchers and developers interested in integrating mashup functionalities into their work.
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Semantic Mashups, Brigitte Endres
- Lingua
- Pubblicato
- 2015
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- (In brossura)
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