Mining Urban Data (Part B)
Modern cities are flooded with data. New information sources like public transport and wearable devices provide opportunities for novel applications that will improve citizens׳ quality of life. From a data science perspective, data emerging from smart cities give rise to a lot of challenges that con...
Ausführliche Beschreibung
Autor*in: |
Andrienko, Gennady [verfasserIn] |
---|
Format: |
E-Artikel |
---|---|
Sprache: |
Englisch |
Erschienen: |
2016 |
---|
Schlagwörter: |
---|
Umfang: |
2 |
---|
Übergeordnetes Werk: |
Enthalten in: Orthopedic sleep and novel analgesia pathway: a prospective randomized controlled trial to advance recovery after shoulder arthroplasty - Cheah, Jonathan W. ELSEVIER, 2022, IS : an international journal : data bases, Oxford [u.a.] |
---|---|
Übergeordnetes Werk: |
volume:57 ; year:2016 ; pages:75-76 ; extent:2 |
Links: |
---|
DOI / URN: |
10.1016/j.is.2016.01.001 |
---|
Katalog-ID: |
ELV024326836 |
---|
LEADER | 01000caa a22002652 4500 | ||
---|---|---|---|
001 | ELV024326836 | ||
003 | DE-627 | ||
005 | 20230623173538.0 | ||
007 | cr uuu---uuuuu | ||
008 | 180603s2016 xx |||||o 00| ||eng c | ||
024 | 7 | |a 10.1016/j.is.2016.01.001 |2 doi | |
028 | 5 | 2 | |a GBVA2016008000006.pica |
035 | |a (DE-627)ELV024326836 | ||
035 | |a (ELSEVIER)S0306-4379(16)00003-X | ||
040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
041 | |a eng | ||
082 | 0 | |a 070 | |
082 | 0 | 4 | |a 070 |q DE-600 |
082 | 0 | 4 | |a 610 |q VZ |
084 | |a 44.83 |2 bkl | ||
100 | 1 | |a Andrienko, Gennady |e verfasserin |4 aut | |
245 | 1 | 0 | |a Mining Urban Data (Part B) |
264 | 1 | |c 2016 | |
300 | |a 2 | ||
336 | |a nicht spezifiziert |b zzz |2 rdacontent | ||
337 | |a nicht spezifiziert |b z |2 rdamedia | ||
338 | |a nicht spezifiziert |b zu |2 rdacarrier | ||
520 | |a Modern cities are flooded with data. New information sources like public transport and wearable devices provide opportunities for novel applications that will improve citizens׳ quality of life. From a data science perspective, data emerging from smart cities give rise to a lot of challenges that constitute a new interdisciplinary field of research. This article introduces the second part of a special issue on the topic ‘Mining Urban Data’ published in the journal Information Systems. | ||
650 | 7 | |a Smart cities |2 Elsevier | |
650 | 7 | |a Data management |2 Elsevier | |
650 | 7 | |a Sensor networks |2 Elsevier | |
650 | 7 | |a Social networks |2 Elsevier | |
650 | 7 | |a Urban data |2 Elsevier | |
650 | 7 | |a Data mining |2 Elsevier | |
700 | 1 | |a Gunopulos, Dimitrios |4 oth | |
700 | 1 | |a Ioannidis, Yannis |4 oth | |
700 | 1 | |a Kalogeraki, Vana |4 oth | |
700 | 1 | |a Katakis, Ioannis |4 oth | |
700 | 1 | |a Morik, Katharina |4 oth | |
700 | 1 | |a Verscheure, Olivier |4 oth | |
773 | 0 | 8 | |i Enthalten in |n Pergamon Press |a Cheah, Jonathan W. ELSEVIER |t Orthopedic sleep and novel analgesia pathway: a prospective randomized controlled trial to advance recovery after shoulder arthroplasty |d 2022 |d IS : an international journal : data bases |g Oxford [u.a.] |w (DE-627)ELV007912846 |
773 | 1 | 8 | |g volume:57 |g year:2016 |g pages:75-76 |g extent:2 |
856 | 4 | 0 | |u https://doi.org/10.1016/j.is.2016.01.001 |3 Volltext |
912 | |a GBV_USEFLAG_U | ||
912 | |a GBV_ELV | ||
912 | |a SYSFLAG_U | ||
912 | |a SSG-OLC-PHA | ||
936 | b | k | |a 44.83 |j Rheumatologie |j Orthopädie |q VZ |
951 | |a AR | ||
952 | |d 57 |j 2016 |h 75-76 |g 2 | ||
953 | |2 045F |a 070 |
author_variant |
g a ga |
---|---|
matchkey_str |
andrienkogennadygunopulosdimitriosioanni:2016----:iigradt |
hierarchy_sort_str |
2016 |
bklnumber |
44.83 |
publishDate |
2016 |
allfields |
10.1016/j.is.2016.01.001 doi GBVA2016008000006.pica (DE-627)ELV024326836 (ELSEVIER)S0306-4379(16)00003-X DE-627 ger DE-627 rakwb eng 070 070 DE-600 610 VZ 44.83 bkl Andrienko, Gennady verfasserin aut Mining Urban Data (Part B) 2016 2 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Modern cities are flooded with data. New information sources like public transport and wearable devices provide opportunities for novel applications that will improve citizens׳ quality of life. From a data science perspective, data emerging from smart cities give rise to a lot of challenges that constitute a new interdisciplinary field of research. This article introduces the second part of a special issue on the topic ‘Mining Urban Data’ published in the journal Information Systems. Smart cities Elsevier Data management Elsevier Sensor networks Elsevier Social networks Elsevier Urban data Elsevier Data mining Elsevier Gunopulos, Dimitrios oth Ioannidis, Yannis oth Kalogeraki, Vana oth Katakis, Ioannis oth Morik, Katharina oth Verscheure, Olivier oth Enthalten in Pergamon Press Cheah, Jonathan W. ELSEVIER Orthopedic sleep and novel analgesia pathway: a prospective randomized controlled trial to advance recovery after shoulder arthroplasty 2022 IS : an international journal : data bases Oxford [u.a.] (DE-627)ELV007912846 volume:57 year:2016 pages:75-76 extent:2 https://doi.org/10.1016/j.is.2016.01.001 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA 44.83 Rheumatologie Orthopädie VZ AR 57 2016 75-76 2 045F 070 |
spelling |
10.1016/j.is.2016.01.001 doi GBVA2016008000006.pica (DE-627)ELV024326836 (ELSEVIER)S0306-4379(16)00003-X DE-627 ger DE-627 rakwb eng 070 070 DE-600 610 VZ 44.83 bkl Andrienko, Gennady verfasserin aut Mining Urban Data (Part B) 2016 2 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Modern cities are flooded with data. New information sources like public transport and wearable devices provide opportunities for novel applications that will improve citizens׳ quality of life. From a data science perspective, data emerging from smart cities give rise to a lot of challenges that constitute a new interdisciplinary field of research. This article introduces the second part of a special issue on the topic ‘Mining Urban Data’ published in the journal Information Systems. Smart cities Elsevier Data management Elsevier Sensor networks Elsevier Social networks Elsevier Urban data Elsevier Data mining Elsevier Gunopulos, Dimitrios oth Ioannidis, Yannis oth Kalogeraki, Vana oth Katakis, Ioannis oth Morik, Katharina oth Verscheure, Olivier oth Enthalten in Pergamon Press Cheah, Jonathan W. ELSEVIER Orthopedic sleep and novel analgesia pathway: a prospective randomized controlled trial to advance recovery after shoulder arthroplasty 2022 IS : an international journal : data bases Oxford [u.a.] (DE-627)ELV007912846 volume:57 year:2016 pages:75-76 extent:2 https://doi.org/10.1016/j.is.2016.01.001 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA 44.83 Rheumatologie Orthopädie VZ AR 57 2016 75-76 2 045F 070 |
allfields_unstemmed |
10.1016/j.is.2016.01.001 doi GBVA2016008000006.pica (DE-627)ELV024326836 (ELSEVIER)S0306-4379(16)00003-X DE-627 ger DE-627 rakwb eng 070 070 DE-600 610 VZ 44.83 bkl Andrienko, Gennady verfasserin aut Mining Urban Data (Part B) 2016 2 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Modern cities are flooded with data. New information sources like public transport and wearable devices provide opportunities for novel applications that will improve citizens׳ quality of life. From a data science perspective, data emerging from smart cities give rise to a lot of challenges that constitute a new interdisciplinary field of research. This article introduces the second part of a special issue on the topic ‘Mining Urban Data’ published in the journal Information Systems. Smart cities Elsevier Data management Elsevier Sensor networks Elsevier Social networks Elsevier Urban data Elsevier Data mining Elsevier Gunopulos, Dimitrios oth Ioannidis, Yannis oth Kalogeraki, Vana oth Katakis, Ioannis oth Morik, Katharina oth Verscheure, Olivier oth Enthalten in Pergamon Press Cheah, Jonathan W. ELSEVIER Orthopedic sleep and novel analgesia pathway: a prospective randomized controlled trial to advance recovery after shoulder arthroplasty 2022 IS : an international journal : data bases Oxford [u.a.] (DE-627)ELV007912846 volume:57 year:2016 pages:75-76 extent:2 https://doi.org/10.1016/j.is.2016.01.001 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA 44.83 Rheumatologie Orthopädie VZ AR 57 2016 75-76 2 045F 070 |
allfieldsGer |
10.1016/j.is.2016.01.001 doi GBVA2016008000006.pica (DE-627)ELV024326836 (ELSEVIER)S0306-4379(16)00003-X DE-627 ger DE-627 rakwb eng 070 070 DE-600 610 VZ 44.83 bkl Andrienko, Gennady verfasserin aut Mining Urban Data (Part B) 2016 2 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Modern cities are flooded with data. New information sources like public transport and wearable devices provide opportunities for novel applications that will improve citizens׳ quality of life. From a data science perspective, data emerging from smart cities give rise to a lot of challenges that constitute a new interdisciplinary field of research. This article introduces the second part of a special issue on the topic ‘Mining Urban Data’ published in the journal Information Systems. Smart cities Elsevier Data management Elsevier Sensor networks Elsevier Social networks Elsevier Urban data Elsevier Data mining Elsevier Gunopulos, Dimitrios oth Ioannidis, Yannis oth Kalogeraki, Vana oth Katakis, Ioannis oth Morik, Katharina oth Verscheure, Olivier oth Enthalten in Pergamon Press Cheah, Jonathan W. ELSEVIER Orthopedic sleep and novel analgesia pathway: a prospective randomized controlled trial to advance recovery after shoulder arthroplasty 2022 IS : an international journal : data bases Oxford [u.a.] (DE-627)ELV007912846 volume:57 year:2016 pages:75-76 extent:2 https://doi.org/10.1016/j.is.2016.01.001 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA 44.83 Rheumatologie Orthopädie VZ AR 57 2016 75-76 2 045F 070 |
allfieldsSound |
10.1016/j.is.2016.01.001 doi GBVA2016008000006.pica (DE-627)ELV024326836 (ELSEVIER)S0306-4379(16)00003-X DE-627 ger DE-627 rakwb eng 070 070 DE-600 610 VZ 44.83 bkl Andrienko, Gennady verfasserin aut Mining Urban Data (Part B) 2016 2 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Modern cities are flooded with data. New information sources like public transport and wearable devices provide opportunities for novel applications that will improve citizens׳ quality of life. From a data science perspective, data emerging from smart cities give rise to a lot of challenges that constitute a new interdisciplinary field of research. This article introduces the second part of a special issue on the topic ‘Mining Urban Data’ published in the journal Information Systems. Smart cities Elsevier Data management Elsevier Sensor networks Elsevier Social networks Elsevier Urban data Elsevier Data mining Elsevier Gunopulos, Dimitrios oth Ioannidis, Yannis oth Kalogeraki, Vana oth Katakis, Ioannis oth Morik, Katharina oth Verscheure, Olivier oth Enthalten in Pergamon Press Cheah, Jonathan W. ELSEVIER Orthopedic sleep and novel analgesia pathway: a prospective randomized controlled trial to advance recovery after shoulder arthroplasty 2022 IS : an international journal : data bases Oxford [u.a.] (DE-627)ELV007912846 volume:57 year:2016 pages:75-76 extent:2 https://doi.org/10.1016/j.is.2016.01.001 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA 44.83 Rheumatologie Orthopädie VZ AR 57 2016 75-76 2 045F 070 |
language |
English |
source |
Enthalten in Orthopedic sleep and novel analgesia pathway: a prospective randomized controlled trial to advance recovery after shoulder arthroplasty Oxford [u.a.] volume:57 year:2016 pages:75-76 extent:2 |
sourceStr |
Enthalten in Orthopedic sleep and novel analgesia pathway: a prospective randomized controlled trial to advance recovery after shoulder arthroplasty Oxford [u.a.] volume:57 year:2016 pages:75-76 extent:2 |
format_phy_str_mv |
Article |
bklname |
Rheumatologie Orthopädie |
institution |
findex.gbv.de |
topic_facet |
Smart cities Data management Sensor networks Social networks Urban data Data mining |
dewey-raw |
070 |
isfreeaccess_bool |
false |
container_title |
Orthopedic sleep and novel analgesia pathway: a prospective randomized controlled trial to advance recovery after shoulder arthroplasty |
authorswithroles_txt_mv |
Andrienko, Gennady @@aut@@ Gunopulos, Dimitrios @@oth@@ Ioannidis, Yannis @@oth@@ Kalogeraki, Vana @@oth@@ Katakis, Ioannis @@oth@@ Morik, Katharina @@oth@@ Verscheure, Olivier @@oth@@ |
publishDateDaySort_date |
2016-01-01T00:00:00Z |
hierarchy_top_id |
ELV007912846 |
dewey-sort |
270 |
id |
ELV024326836 |
language_de |
englisch |
fullrecord |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">ELV024326836</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230623173538.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">180603s2016 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1016/j.is.2016.01.001</subfield><subfield code="2">doi</subfield></datafield><datafield tag="028" ind1="5" ind2="2"><subfield code="a">GBVA2016008000006.pica</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)ELV024326836</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ELSEVIER)S0306-4379(16)00003-X</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2=" "><subfield code="a">070</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">070</subfield><subfield code="q">DE-600</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">610</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">44.83</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Andrienko, Gennady</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Mining Urban Data (Part B)</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2016</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">2</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">zzz</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">z</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">zu</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Modern cities are flooded with data. New information sources like public transport and wearable devices provide opportunities for novel applications that will improve citizens׳ quality of life. From a data science perspective, data emerging from smart cities give rise to a lot of challenges that constitute a new interdisciplinary field of research. This article introduces the second part of a special issue on the topic ‘Mining Urban Data’ published in the journal Information Systems.</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Smart cities</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Data management</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Sensor networks</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Social networks</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Urban data</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Data mining</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Gunopulos, Dimitrios</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Ioannidis, Yannis</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Kalogeraki, Vana</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Katakis, Ioannis</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Morik, Katharina</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Verscheure, Olivier</subfield><subfield code="4">oth</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="n">Pergamon Press</subfield><subfield code="a">Cheah, Jonathan W. ELSEVIER</subfield><subfield code="t">Orthopedic sleep and novel analgesia pathway: a prospective randomized controlled trial to advance recovery after shoulder arthroplasty</subfield><subfield code="d">2022</subfield><subfield code="d">IS : an international journal : data bases</subfield><subfield code="g">Oxford [u.a.]</subfield><subfield code="w">(DE-627)ELV007912846</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:57</subfield><subfield code="g">year:2016</subfield><subfield code="g">pages:75-76</subfield><subfield code="g">extent:2</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.1016/j.is.2016.01.001</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_U</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ELV</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_U</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-PHA</subfield></datafield><datafield tag="936" ind1="b" ind2="k"><subfield code="a">44.83</subfield><subfield code="j">Rheumatologie</subfield><subfield code="j">Orthopädie</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">57</subfield><subfield code="j">2016</subfield><subfield code="h">75-76</subfield><subfield code="g">2</subfield></datafield><datafield tag="953" ind1=" " ind2=" "><subfield code="2">045F</subfield><subfield code="a">070</subfield></datafield></record></collection>
|
author |
Andrienko, Gennady |
spellingShingle |
Andrienko, Gennady ddc 070 ddc 610 bkl 44.83 Elsevier Smart cities Elsevier Data management Elsevier Sensor networks Elsevier Social networks Elsevier Urban data Elsevier Data mining Mining Urban Data (Part B) |
authorStr |
Andrienko, Gennady |
ppnlink_with_tag_str_mv |
@@773@@(DE-627)ELV007912846 |
format |
electronic Article |
dewey-ones |
070 - News media, journalism & publishing 610 - Medicine & health |
delete_txt_mv |
keep |
author_role |
aut |
collection |
elsevier |
remote_str |
true |
illustrated |
Not Illustrated |
topic_title |
070 070 DE-600 610 VZ 44.83 bkl Mining Urban Data (Part B) Smart cities Elsevier Data management Elsevier Sensor networks Elsevier Social networks Elsevier Urban data Elsevier Data mining Elsevier |
topic |
ddc 070 ddc 610 bkl 44.83 Elsevier Smart cities Elsevier Data management Elsevier Sensor networks Elsevier Social networks Elsevier Urban data Elsevier Data mining |
topic_unstemmed |
ddc 070 ddc 610 bkl 44.83 Elsevier Smart cities Elsevier Data management Elsevier Sensor networks Elsevier Social networks Elsevier Urban data Elsevier Data mining |
topic_browse |
ddc 070 ddc 610 bkl 44.83 Elsevier Smart cities Elsevier Data management Elsevier Sensor networks Elsevier Social networks Elsevier Urban data Elsevier Data mining |
format_facet |
Elektronische Aufsätze Aufsätze Elektronische Ressource |
format_main_str_mv |
Text Zeitschrift/Artikel |
carriertype_str_mv |
zu |
author2_variant |
d g dg y i yi v k vk i k ik k m km o v ov |
hierarchy_parent_title |
Orthopedic sleep and novel analgesia pathway: a prospective randomized controlled trial to advance recovery after shoulder arthroplasty |
hierarchy_parent_id |
ELV007912846 |
dewey-tens |
070 - News media, journalism & publishing 610 - Medicine & health |
hierarchy_top_title |
Orthopedic sleep and novel analgesia pathway: a prospective randomized controlled trial to advance recovery after shoulder arthroplasty |
isfreeaccess_txt |
false |
familylinks_str_mv |
(DE-627)ELV007912846 |
title |
Mining Urban Data (Part B) |
ctrlnum |
(DE-627)ELV024326836 (ELSEVIER)S0306-4379(16)00003-X |
title_full |
Mining Urban Data (Part B) |
author_sort |
Andrienko, Gennady |
journal |
Orthopedic sleep and novel analgesia pathway: a prospective randomized controlled trial to advance recovery after shoulder arthroplasty |
journalStr |
Orthopedic sleep and novel analgesia pathway: a prospective randomized controlled trial to advance recovery after shoulder arthroplasty |
lang_code |
eng |
isOA_bool |
false |
dewey-hundreds |
000 - Computer science, information & general works 600 - Technology |
recordtype |
marc |
publishDateSort |
2016 |
contenttype_str_mv |
zzz |
container_start_page |
75 |
author_browse |
Andrienko, Gennady |
container_volume |
57 |
physical |
2 |
class |
070 070 DE-600 610 VZ 44.83 bkl |
format_se |
Elektronische Aufsätze |
author-letter |
Andrienko, Gennady |
doi_str_mv |
10.1016/j.is.2016.01.001 |
dewey-full |
070 610 |
title_sort |
mining urban data (part b) |
title_auth |
Mining Urban Data (Part B) |
abstract |
Modern cities are flooded with data. New information sources like public transport and wearable devices provide opportunities for novel applications that will improve citizens׳ quality of life. From a data science perspective, data emerging from smart cities give rise to a lot of challenges that constitute a new interdisciplinary field of research. This article introduces the second part of a special issue on the topic ‘Mining Urban Data’ published in the journal Information Systems. |
abstractGer |
Modern cities are flooded with data. New information sources like public transport and wearable devices provide opportunities for novel applications that will improve citizens׳ quality of life. From a data science perspective, data emerging from smart cities give rise to a lot of challenges that constitute a new interdisciplinary field of research. This article introduces the second part of a special issue on the topic ‘Mining Urban Data’ published in the journal Information Systems. |
abstract_unstemmed |
Modern cities are flooded with data. New information sources like public transport and wearable devices provide opportunities for novel applications that will improve citizens׳ quality of life. From a data science perspective, data emerging from smart cities give rise to a lot of challenges that constitute a new interdisciplinary field of research. This article introduces the second part of a special issue on the topic ‘Mining Urban Data’ published in the journal Information Systems. |
collection_details |
GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA |
title_short |
Mining Urban Data (Part B) |
url |
https://doi.org/10.1016/j.is.2016.01.001 |
remote_bool |
true |
author2 |
Gunopulos, Dimitrios Ioannidis, Yannis Kalogeraki, Vana Katakis, Ioannis Morik, Katharina Verscheure, Olivier |
author2Str |
Gunopulos, Dimitrios Ioannidis, Yannis Kalogeraki, Vana Katakis, Ioannis Morik, Katharina Verscheure, Olivier |
ppnlink |
ELV007912846 |
mediatype_str_mv |
z |
isOA_txt |
false |
hochschulschrift_bool |
false |
author2_role |
oth oth oth oth oth oth |
doi_str |
10.1016/j.is.2016.01.001 |
up_date |
2024-07-06T21:08:35.758Z |
_version_ |
1803865414183157760 |
fullrecord_marcxml |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">ELV024326836</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230623173538.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">180603s2016 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1016/j.is.2016.01.001</subfield><subfield code="2">doi</subfield></datafield><datafield tag="028" ind1="5" ind2="2"><subfield code="a">GBVA2016008000006.pica</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)ELV024326836</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ELSEVIER)S0306-4379(16)00003-X</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2=" "><subfield code="a">070</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">070</subfield><subfield code="q">DE-600</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">610</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">44.83</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Andrienko, Gennady</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Mining Urban Data (Part B)</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2016</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">2</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">zzz</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">z</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">zu</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Modern cities are flooded with data. New information sources like public transport and wearable devices provide opportunities for novel applications that will improve citizens׳ quality of life. From a data science perspective, data emerging from smart cities give rise to a lot of challenges that constitute a new interdisciplinary field of research. This article introduces the second part of a special issue on the topic ‘Mining Urban Data’ published in the journal Information Systems.</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Smart cities</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Data management</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Sensor networks</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Social networks</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Urban data</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Data mining</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Gunopulos, Dimitrios</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Ioannidis, Yannis</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Kalogeraki, Vana</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Katakis, Ioannis</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Morik, Katharina</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Verscheure, Olivier</subfield><subfield code="4">oth</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="n">Pergamon Press</subfield><subfield code="a">Cheah, Jonathan W. ELSEVIER</subfield><subfield code="t">Orthopedic sleep and novel analgesia pathway: a prospective randomized controlled trial to advance recovery after shoulder arthroplasty</subfield><subfield code="d">2022</subfield><subfield code="d">IS : an international journal : data bases</subfield><subfield code="g">Oxford [u.a.]</subfield><subfield code="w">(DE-627)ELV007912846</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:57</subfield><subfield code="g">year:2016</subfield><subfield code="g">pages:75-76</subfield><subfield code="g">extent:2</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.1016/j.is.2016.01.001</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_U</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ELV</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_U</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-PHA</subfield></datafield><datafield tag="936" ind1="b" ind2="k"><subfield code="a">44.83</subfield><subfield code="j">Rheumatologie</subfield><subfield code="j">Orthopädie</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">57</subfield><subfield code="j">2016</subfield><subfield code="h">75-76</subfield><subfield code="g">2</subfield></datafield><datafield tag="953" ind1=" " ind2=" "><subfield code="2">045F</subfield><subfield code="a">070</subfield></datafield></record></collection>
|
score |
7.4016542 |