000 | 03401nam a22005295i 4500 | ||
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001 | 978-3-642-28135-8 | ||
003 | DE-He213 | ||
005 | 20140220083311.0 | ||
007 | cr nn 008mamaa | ||
008 | 120220s2012 gw | s |||| 0|eng d | ||
020 |
_a9783642281358 _9978-3-642-28135-8 |
||
024 | 7 |
_a10.1007/978-3-642-28135-8 _2doi |
|
050 | 4 | _aQA76.9.D343 | |
072 | 7 |
_aUNF _2bicssc |
|
072 | 7 |
_aUYQE _2bicssc |
|
072 | 7 |
_aCOM021030 _2bisacsh |
|
082 | 0 | 4 |
_a006.312 _223 |
100 | 1 |
_aDenecke, Kerstin. _eauthor. |
|
245 | 1 | 0 |
_aEvent-Driven Surveillance _h[electronic resource] : _bPossibilities and Challenges / _cby Kerstin Denecke. |
264 | 1 |
_aBerlin, Heidelberg : _bSpringer Berlin Heidelberg, _c2012. |
|
300 |
_aX, 76 p. _bonline resource. |
||
336 |
_atext _btxt _2rdacontent |
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337 |
_acomputer _bc _2rdamedia |
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338 |
_aonline resource _bcr _2rdacarrier |
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347 |
_atext file _bPDF _2rda |
||
490 | 1 |
_aSpringerBriefs in Computer Science, _x2191-5768 |
|
520 | _aThe Web has become a rich source of personal information in the last few years. People twitter, blog, and chat online. Current feelings, experiences or latest news are posted. For instance, first hints to disease outbreaks, customer preferences, or political changes could be identified with this data. Surveillance or early warning systems enable such detection of changes and support humans in getting information on changing situations. However, the variety of data that could be considered for surveillance is immense, ranging from sensor-measured values to collected counts and information extracted from natural language documents. Denecke’s objective is to introduce the multiple possibilities and facets of surveillance and its applications. She first introduces the task of surveillance and provides an overview on surveillance in various domains. Next, the various information sources that are available and could already be used by surveillance systems are summarized. In the main part of the book, her focus is on unstructured data as a source for surveillance. An overview on existing methods as well as methods to be developed in order to process this kind of data with respect to surveillance is presented. As an example application, she introduces disease surveillance using Web 2.0, including corresponding methods and challenges to be addressed. The book closes with remarks on new possibilities for surveillance gained by recent developments of the Internet and mobile communication, and with an outline of future challenges. | ||
650 | 0 | _aComputer science. | |
650 | 0 | _aData mining. | |
650 | 0 | _aInformation storage and retrieval systems. | |
650 | 0 | _aArtificial intelligence. | |
650 | 0 | _aText processing (Computer science. | |
650 | 0 | _aOptical pattern recognition. | |
650 | 1 | 4 | _aComputer Science. |
650 | 2 | 4 | _aData Mining and Knowledge Discovery. |
650 | 2 | 4 | _aInformation Storage and Retrieval. |
650 | 2 | 4 | _aDocument Preparation and Text Processing. |
650 | 2 | 4 | _aPattern Recognition. |
650 | 2 | 4 | _aArtificial Intelligence (incl. Robotics). |
710 | 2 | _aSpringerLink (Online service) | |
773 | 0 | _tSpringer eBooks | |
776 | 0 | 8 |
_iPrinted edition: _z9783642281341 |
830 | 0 |
_aSpringerBriefs in Computer Science, _x2191-5768 |
|
856 | 4 | 0 | _uhttp://dx.doi.org/10.1007/978-3-642-28135-8 |
912 | _aZDB-2-SCS | ||
999 |
_c102736 _d102736 |