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001 978-3-642-36403-7
003 DE-He213
005 20140220082904.0
007 cr nn 008mamaa
008 130406s2013 gw | s |||| 0|eng d
020 _a9783642364037
_9978-3-642-36403-7
024 7 _a10.1007/978-3-642-36403-7
_2doi
050 4 _aQA76.76.A65
072 7 _aUNH
_2bicssc
072 7 _aUDBD
_2bicssc
072 7 _aCOM032000
_2bisacsh
082 0 4 _a005.7
_223
100 1 _aEndres-Niggemeyer, Brigitte.
_eeditor.
245 1 0 _aSemantic Mashups
_h[electronic resource] :
_bIntelligent Reuse of Web Resources /
_cedited by Brigitte Endres-Niggemeyer.
264 1 _aBerlin, Heidelberg :
_bSpringer Berlin Heidelberg :
_bImprint: Springer,
_c2013.
300 _aVII, 382 p. 153 illus., 22 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
505 0 _aThe Mashup Ecosystem -- Mashups live on Standards -- Mashups for web search engines -- DBpedia Mashups -- Mashups for the Web of Things -- Mashups using Mathematical Knowledge -- Speech Mashups -- Mashups for the Emergency Management Domain -- Similarity Mashups for Recommendation -- Urban Mash-ups -- Travel Mashups.
520 _aMashups are mostly lightweight Web applications that offer new functionalities by combining, aggregating and transforming resources and services available on the Web. Popular examples include a map in their main offer, for instance for real estate, hotel recommendations, or navigation tools.   Mashups may contain and mix client-side and server-side activity. Obviously, understanding the incoming resources (services, statistical figures, text, videos, etc.) is a precondition for optimally combining them, so that there is always some undercover semantics being used.  By using semantic annotations, neutral mashups permute into the branded type of semantic mashups. Further and deeper semantic processing such as reasoning is the next step.   The chapters of this book reflect the diversity of real-life semantic mashups. Two overview chapters take the reader to the environments where mashups are at home and review the regulations (standards, guidelines etc.) mashups are based on and confronted with. Chapters focusing on DBpedia, search engines and the Web of Things inspect the main Web surroundings of mashups. While mashups upgrading search queries may be nearer to the everyday experience of readers, mashups using DBpedia input and sensor data from the real world lead to important new and therefore less known developments. Finally, the diversity of mashups is tracked through a few application areas: mathematical knowledge, speech, crisis and disaster management, recommendations (for games), inner-city information, and tourism.   Participants of the AI Mashup Challenge wrote all the chapters of this book. The authors were writing for their current and future colleagues – researchers and developers all over the Web who integrate mashup functionalities into their thinking and possibly into their applications.
650 0 _aComputer science.
650 0 _aSoftware engineering.
650 0 _aMultimedia systems.
650 0 _aArtificial intelligence.
650 1 4 _aComputer Science.
650 2 4 _aInformation Systems Applications (incl. Internet).
650 2 4 _aArtificial Intelligence (incl. Robotics).
650 2 4 _aSoftware Engineering.
650 2 4 _aMultimedia Information Systems.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783642364020
856 4 0 _uhttp://dx.doi.org/10.1007/978-3-642-36403-7
912 _aZDB-2-SCS
999 _c97862
_d97862