DMatrix: Toward fast and accurate queries in graph stream
The graph stream has recently arisen in many interactive scenarios. Characterizing with large volume and high dynamic, graph streams are known to be difficult for high-speed summary and analysis, especially provided with limited resource availability. Existing solutions mainly use sketch-based metho...
Ausführliche Beschreibung
Autor*in: |
Hou, Changsheng [verfasserIn] |
---|
Format: |
E-Artikel |
---|---|
Sprache: |
Englisch |
Erschienen: |
2021transfer abstract |
---|
Schlagwörter: |
---|
Übergeordnetes Werk: |
Enthalten in: Pharmacokinetics of the Antifibrotic Drug Pirfenidone in Child Pugh A and B Cirrhotic Patients Compared to Healthy Age-Matched Controls - Poo, J.L. ELSEVIER, 2016, the international journal of computer and telecommunications networking, Amsterdam [u.a.] |
---|---|
Übergeordnetes Werk: |
volume:198 ; year:2021 ; day:24 ; month:10 ; pages:0 |
Links: |
---|
DOI / URN: |
10.1016/j.comnet.2021.108403 |
---|
Katalog-ID: |
ELV055187110 |
---|
LEADER | 01000caa a22002652 4500 | ||
---|---|---|---|
001 | ELV055187110 | ||
003 | DE-627 | ||
005 | 20230626041339.0 | ||
007 | cr uuu---uuuuu | ||
008 | 220105s2021 xx |||||o 00| ||eng c | ||
024 | 7 | |a 10.1016/j.comnet.2021.108403 |2 doi | |
028 | 5 | 2 | |a /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001522.pica |
035 | |a (DE-627)ELV055187110 | ||
035 | |a (ELSEVIER)S1389-1286(21)00377-7 | ||
040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
041 | |a eng | ||
082 | 0 | 4 | |a 610 |q VZ |
082 | 0 | 4 | |a 610 |q VZ |
084 | |a 44.44 |2 bkl | ||
100 | 1 | |a Hou, Changsheng |e verfasserin |4 aut | |
245 | 1 | 0 | |a DMatrix: Toward fast and accurate queries in graph stream |
264 | 1 | |c 2021transfer abstract | |
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 The graph stream has recently arisen in many interactive scenarios. Characterizing with large volume and high dynamic, graph streams are known to be difficult for high-speed summary and analysis, especially provided with limited resource availability. Existing solutions mainly use sketch-based methods to estimate the weight of items (e.g., Count-Min Sketch) and preserve the underlying graph structure information (e.g., TCM). Unfortunately, these solutions neither support complex graph-based queries nor achieve efficient real-time queries. In view of these limitations, we design DMatrix, a novel 3-dimensional graph sketch to facilitate fast and accurate queries in graph stream. Both structural query and weight-based estimation are supported with DMatrix. Through the integration of representative key reservation and majority voting, DMatrix can effectively narrow the error bounds of queries with real-time response efficiency. Both theoretical analysis and experimental results confirm that our solution is superior in accuracy and efficiency comparing with the state-of-the-art. | ||
520 | |a The graph stream has recently arisen in many interactive scenarios. Characterizing with large volume and high dynamic, graph streams are known to be difficult for high-speed summary and analysis, especially provided with limited resource availability. Existing solutions mainly use sketch-based methods to estimate the weight of items (e.g., Count-Min Sketch) and preserve the underlying graph structure information (e.g., TCM). Unfortunately, these solutions neither support complex graph-based queries nor achieve efficient real-time queries. In view of these limitations, we design DMatrix, a novel 3-dimensional graph sketch to facilitate fast and accurate queries in graph stream. Both structural query and weight-based estimation are supported with DMatrix. Through the integration of representative key reservation and majority voting, DMatrix can effectively narrow the error bounds of queries with real-time response efficiency. Both theoretical analysis and experimental results confirm that our solution is superior in accuracy and efficiency comparing with the state-of-the-art. | ||
650 | 7 | |a Graph stream |2 Elsevier | |
650 | 7 | |a Graph sketch |2 Elsevier | |
650 | 7 | |a Approximate query |2 Elsevier | |
700 | 1 | |a Hou, Bingnan |4 oth | |
700 | 1 | |a Zhou, Tongqing |4 oth | |
700 | 1 | |a Cai, Zhiping |4 oth | |
773 | 0 | 8 | |i Enthalten in |n Elsevier |a Poo, J.L. ELSEVIER |t Pharmacokinetics of the Antifibrotic Drug Pirfenidone in Child Pugh A and B Cirrhotic Patients Compared to Healthy Age-Matched Controls |d 2016 |d the international journal of computer and telecommunications networking |g Amsterdam [u.a.] |w (DE-627)ELV013796984 |
773 | 1 | 8 | |g volume:198 |g year:2021 |g day:24 |g month:10 |g pages:0 |
856 | 4 | 0 | |u https://doi.org/10.1016/j.comnet.2021.108403 |3 Volltext |
912 | |a GBV_USEFLAG_U | ||
912 | |a GBV_ELV | ||
912 | |a SYSFLAG_U | ||
912 | |a SSG-OLC-PHA | ||
912 | |a GBV_ILN_40 | ||
936 | b | k | |a 44.44 |j Parasitologie |x Medizin |q VZ |
951 | |a AR | ||
952 | |d 198 |j 2021 |b 24 |c 1024 |h 0 |
author_variant |
c h ch |
---|---|
matchkey_str |
houchangshenghoubingnanzhoutongqingcaizh:2021----:mtitwrfsadcuaeurei |
hierarchy_sort_str |
2021transfer abstract |
bklnumber |
44.44 |
publishDate |
2021 |
allfields |
10.1016/j.comnet.2021.108403 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001522.pica (DE-627)ELV055187110 (ELSEVIER)S1389-1286(21)00377-7 DE-627 ger DE-627 rakwb eng 610 VZ 610 VZ 44.44 bkl Hou, Changsheng verfasserin aut DMatrix: Toward fast and accurate queries in graph stream 2021transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier The graph stream has recently arisen in many interactive scenarios. Characterizing with large volume and high dynamic, graph streams are known to be difficult for high-speed summary and analysis, especially provided with limited resource availability. Existing solutions mainly use sketch-based methods to estimate the weight of items (e.g., Count-Min Sketch) and preserve the underlying graph structure information (e.g., TCM). Unfortunately, these solutions neither support complex graph-based queries nor achieve efficient real-time queries. In view of these limitations, we design DMatrix, a novel 3-dimensional graph sketch to facilitate fast and accurate queries in graph stream. Both structural query and weight-based estimation are supported with DMatrix. Through the integration of representative key reservation and majority voting, DMatrix can effectively narrow the error bounds of queries with real-time response efficiency. Both theoretical analysis and experimental results confirm that our solution is superior in accuracy and efficiency comparing with the state-of-the-art. The graph stream has recently arisen in many interactive scenarios. Characterizing with large volume and high dynamic, graph streams are known to be difficult for high-speed summary and analysis, especially provided with limited resource availability. Existing solutions mainly use sketch-based methods to estimate the weight of items (e.g., Count-Min Sketch) and preserve the underlying graph structure information (e.g., TCM). Unfortunately, these solutions neither support complex graph-based queries nor achieve efficient real-time queries. In view of these limitations, we design DMatrix, a novel 3-dimensional graph sketch to facilitate fast and accurate queries in graph stream. Both structural query and weight-based estimation are supported with DMatrix. Through the integration of representative key reservation and majority voting, DMatrix can effectively narrow the error bounds of queries with real-time response efficiency. Both theoretical analysis and experimental results confirm that our solution is superior in accuracy and efficiency comparing with the state-of-the-art. Graph stream Elsevier Graph sketch Elsevier Approximate query Elsevier Hou, Bingnan oth Zhou, Tongqing oth Cai, Zhiping oth Enthalten in Elsevier Poo, J.L. ELSEVIER Pharmacokinetics of the Antifibrotic Drug Pirfenidone in Child Pugh A and B Cirrhotic Patients Compared to Healthy Age-Matched Controls 2016 the international journal of computer and telecommunications networking Amsterdam [u.a.] (DE-627)ELV013796984 volume:198 year:2021 day:24 month:10 pages:0 https://doi.org/10.1016/j.comnet.2021.108403 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA GBV_ILN_40 44.44 Parasitologie Medizin VZ AR 198 2021 24 1024 0 |
spelling |
10.1016/j.comnet.2021.108403 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001522.pica (DE-627)ELV055187110 (ELSEVIER)S1389-1286(21)00377-7 DE-627 ger DE-627 rakwb eng 610 VZ 610 VZ 44.44 bkl Hou, Changsheng verfasserin aut DMatrix: Toward fast and accurate queries in graph stream 2021transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier The graph stream has recently arisen in many interactive scenarios. Characterizing with large volume and high dynamic, graph streams are known to be difficult for high-speed summary and analysis, especially provided with limited resource availability. Existing solutions mainly use sketch-based methods to estimate the weight of items (e.g., Count-Min Sketch) and preserve the underlying graph structure information (e.g., TCM). Unfortunately, these solutions neither support complex graph-based queries nor achieve efficient real-time queries. In view of these limitations, we design DMatrix, a novel 3-dimensional graph sketch to facilitate fast and accurate queries in graph stream. Both structural query and weight-based estimation are supported with DMatrix. Through the integration of representative key reservation and majority voting, DMatrix can effectively narrow the error bounds of queries with real-time response efficiency. Both theoretical analysis and experimental results confirm that our solution is superior in accuracy and efficiency comparing with the state-of-the-art. The graph stream has recently arisen in many interactive scenarios. Characterizing with large volume and high dynamic, graph streams are known to be difficult for high-speed summary and analysis, especially provided with limited resource availability. Existing solutions mainly use sketch-based methods to estimate the weight of items (e.g., Count-Min Sketch) and preserve the underlying graph structure information (e.g., TCM). Unfortunately, these solutions neither support complex graph-based queries nor achieve efficient real-time queries. In view of these limitations, we design DMatrix, a novel 3-dimensional graph sketch to facilitate fast and accurate queries in graph stream. Both structural query and weight-based estimation are supported with DMatrix. Through the integration of representative key reservation and majority voting, DMatrix can effectively narrow the error bounds of queries with real-time response efficiency. Both theoretical analysis and experimental results confirm that our solution is superior in accuracy and efficiency comparing with the state-of-the-art. Graph stream Elsevier Graph sketch Elsevier Approximate query Elsevier Hou, Bingnan oth Zhou, Tongqing oth Cai, Zhiping oth Enthalten in Elsevier Poo, J.L. ELSEVIER Pharmacokinetics of the Antifibrotic Drug Pirfenidone in Child Pugh A and B Cirrhotic Patients Compared to Healthy Age-Matched Controls 2016 the international journal of computer and telecommunications networking Amsterdam [u.a.] (DE-627)ELV013796984 volume:198 year:2021 day:24 month:10 pages:0 https://doi.org/10.1016/j.comnet.2021.108403 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA GBV_ILN_40 44.44 Parasitologie Medizin VZ AR 198 2021 24 1024 0 |
allfields_unstemmed |
10.1016/j.comnet.2021.108403 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001522.pica (DE-627)ELV055187110 (ELSEVIER)S1389-1286(21)00377-7 DE-627 ger DE-627 rakwb eng 610 VZ 610 VZ 44.44 bkl Hou, Changsheng verfasserin aut DMatrix: Toward fast and accurate queries in graph stream 2021transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier The graph stream has recently arisen in many interactive scenarios. Characterizing with large volume and high dynamic, graph streams are known to be difficult for high-speed summary and analysis, especially provided with limited resource availability. Existing solutions mainly use sketch-based methods to estimate the weight of items (e.g., Count-Min Sketch) and preserve the underlying graph structure information (e.g., TCM). Unfortunately, these solutions neither support complex graph-based queries nor achieve efficient real-time queries. In view of these limitations, we design DMatrix, a novel 3-dimensional graph sketch to facilitate fast and accurate queries in graph stream. Both structural query and weight-based estimation are supported with DMatrix. Through the integration of representative key reservation and majority voting, DMatrix can effectively narrow the error bounds of queries with real-time response efficiency. Both theoretical analysis and experimental results confirm that our solution is superior in accuracy and efficiency comparing with the state-of-the-art. The graph stream has recently arisen in many interactive scenarios. Characterizing with large volume and high dynamic, graph streams are known to be difficult for high-speed summary and analysis, especially provided with limited resource availability. Existing solutions mainly use sketch-based methods to estimate the weight of items (e.g., Count-Min Sketch) and preserve the underlying graph structure information (e.g., TCM). Unfortunately, these solutions neither support complex graph-based queries nor achieve efficient real-time queries. In view of these limitations, we design DMatrix, a novel 3-dimensional graph sketch to facilitate fast and accurate queries in graph stream. Both structural query and weight-based estimation are supported with DMatrix. Through the integration of representative key reservation and majority voting, DMatrix can effectively narrow the error bounds of queries with real-time response efficiency. Both theoretical analysis and experimental results confirm that our solution is superior in accuracy and efficiency comparing with the state-of-the-art. Graph stream Elsevier Graph sketch Elsevier Approximate query Elsevier Hou, Bingnan oth Zhou, Tongqing oth Cai, Zhiping oth Enthalten in Elsevier Poo, J.L. ELSEVIER Pharmacokinetics of the Antifibrotic Drug Pirfenidone in Child Pugh A and B Cirrhotic Patients Compared to Healthy Age-Matched Controls 2016 the international journal of computer and telecommunications networking Amsterdam [u.a.] (DE-627)ELV013796984 volume:198 year:2021 day:24 month:10 pages:0 https://doi.org/10.1016/j.comnet.2021.108403 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA GBV_ILN_40 44.44 Parasitologie Medizin VZ AR 198 2021 24 1024 0 |
allfieldsGer |
10.1016/j.comnet.2021.108403 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001522.pica (DE-627)ELV055187110 (ELSEVIER)S1389-1286(21)00377-7 DE-627 ger DE-627 rakwb eng 610 VZ 610 VZ 44.44 bkl Hou, Changsheng verfasserin aut DMatrix: Toward fast and accurate queries in graph stream 2021transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier The graph stream has recently arisen in many interactive scenarios. Characterizing with large volume and high dynamic, graph streams are known to be difficult for high-speed summary and analysis, especially provided with limited resource availability. Existing solutions mainly use sketch-based methods to estimate the weight of items (e.g., Count-Min Sketch) and preserve the underlying graph structure information (e.g., TCM). Unfortunately, these solutions neither support complex graph-based queries nor achieve efficient real-time queries. In view of these limitations, we design DMatrix, a novel 3-dimensional graph sketch to facilitate fast and accurate queries in graph stream. Both structural query and weight-based estimation are supported with DMatrix. Through the integration of representative key reservation and majority voting, DMatrix can effectively narrow the error bounds of queries with real-time response efficiency. Both theoretical analysis and experimental results confirm that our solution is superior in accuracy and efficiency comparing with the state-of-the-art. The graph stream has recently arisen in many interactive scenarios. Characterizing with large volume and high dynamic, graph streams are known to be difficult for high-speed summary and analysis, especially provided with limited resource availability. Existing solutions mainly use sketch-based methods to estimate the weight of items (e.g., Count-Min Sketch) and preserve the underlying graph structure information (e.g., TCM). Unfortunately, these solutions neither support complex graph-based queries nor achieve efficient real-time queries. In view of these limitations, we design DMatrix, a novel 3-dimensional graph sketch to facilitate fast and accurate queries in graph stream. Both structural query and weight-based estimation are supported with DMatrix. Through the integration of representative key reservation and majority voting, DMatrix can effectively narrow the error bounds of queries with real-time response efficiency. Both theoretical analysis and experimental results confirm that our solution is superior in accuracy and efficiency comparing with the state-of-the-art. Graph stream Elsevier Graph sketch Elsevier Approximate query Elsevier Hou, Bingnan oth Zhou, Tongqing oth Cai, Zhiping oth Enthalten in Elsevier Poo, J.L. ELSEVIER Pharmacokinetics of the Antifibrotic Drug Pirfenidone in Child Pugh A and B Cirrhotic Patients Compared to Healthy Age-Matched Controls 2016 the international journal of computer and telecommunications networking Amsterdam [u.a.] (DE-627)ELV013796984 volume:198 year:2021 day:24 month:10 pages:0 https://doi.org/10.1016/j.comnet.2021.108403 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA GBV_ILN_40 44.44 Parasitologie Medizin VZ AR 198 2021 24 1024 0 |
allfieldsSound |
10.1016/j.comnet.2021.108403 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001522.pica (DE-627)ELV055187110 (ELSEVIER)S1389-1286(21)00377-7 DE-627 ger DE-627 rakwb eng 610 VZ 610 VZ 44.44 bkl Hou, Changsheng verfasserin aut DMatrix: Toward fast and accurate queries in graph stream 2021transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier The graph stream has recently arisen in many interactive scenarios. Characterizing with large volume and high dynamic, graph streams are known to be difficult for high-speed summary and analysis, especially provided with limited resource availability. Existing solutions mainly use sketch-based methods to estimate the weight of items (e.g., Count-Min Sketch) and preserve the underlying graph structure information (e.g., TCM). Unfortunately, these solutions neither support complex graph-based queries nor achieve efficient real-time queries. In view of these limitations, we design DMatrix, a novel 3-dimensional graph sketch to facilitate fast and accurate queries in graph stream. Both structural query and weight-based estimation are supported with DMatrix. Through the integration of representative key reservation and majority voting, DMatrix can effectively narrow the error bounds of queries with real-time response efficiency. Both theoretical analysis and experimental results confirm that our solution is superior in accuracy and efficiency comparing with the state-of-the-art. The graph stream has recently arisen in many interactive scenarios. Characterizing with large volume and high dynamic, graph streams are known to be difficult for high-speed summary and analysis, especially provided with limited resource availability. Existing solutions mainly use sketch-based methods to estimate the weight of items (e.g., Count-Min Sketch) and preserve the underlying graph structure information (e.g., TCM). Unfortunately, these solutions neither support complex graph-based queries nor achieve efficient real-time queries. In view of these limitations, we design DMatrix, a novel 3-dimensional graph sketch to facilitate fast and accurate queries in graph stream. Both structural query and weight-based estimation are supported with DMatrix. Through the integration of representative key reservation and majority voting, DMatrix can effectively narrow the error bounds of queries with real-time response efficiency. Both theoretical analysis and experimental results confirm that our solution is superior in accuracy and efficiency comparing with the state-of-the-art. Graph stream Elsevier Graph sketch Elsevier Approximate query Elsevier Hou, Bingnan oth Zhou, Tongqing oth Cai, Zhiping oth Enthalten in Elsevier Poo, J.L. ELSEVIER Pharmacokinetics of the Antifibrotic Drug Pirfenidone in Child Pugh A and B Cirrhotic Patients Compared to Healthy Age-Matched Controls 2016 the international journal of computer and telecommunications networking Amsterdam [u.a.] (DE-627)ELV013796984 volume:198 year:2021 day:24 month:10 pages:0 https://doi.org/10.1016/j.comnet.2021.108403 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA GBV_ILN_40 44.44 Parasitologie Medizin VZ AR 198 2021 24 1024 0 |
language |
English |
source |
Enthalten in Pharmacokinetics of the Antifibrotic Drug Pirfenidone in Child Pugh A and B Cirrhotic Patients Compared to Healthy Age-Matched Controls Amsterdam [u.a.] volume:198 year:2021 day:24 month:10 pages:0 |
sourceStr |
Enthalten in Pharmacokinetics of the Antifibrotic Drug Pirfenidone in Child Pugh A and B Cirrhotic Patients Compared to Healthy Age-Matched Controls Amsterdam [u.a.] volume:198 year:2021 day:24 month:10 pages:0 |
format_phy_str_mv |
Article |
bklname |
Parasitologie |
institution |
findex.gbv.de |
topic_facet |
Graph stream Graph sketch Approximate query |
dewey-raw |
610 |
isfreeaccess_bool |
false |
container_title |
Pharmacokinetics of the Antifibrotic Drug Pirfenidone in Child Pugh A and B Cirrhotic Patients Compared to Healthy Age-Matched Controls |
authorswithroles_txt_mv |
Hou, Changsheng @@aut@@ Hou, Bingnan @@oth@@ Zhou, Tongqing @@oth@@ Cai, Zhiping @@oth@@ |
publishDateDaySort_date |
2021-01-24T00:00:00Z |
hierarchy_top_id |
ELV013796984 |
dewey-sort |
3610 |
id |
ELV055187110 |
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">ELV055187110</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230626041339.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">220105s2021 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1016/j.comnet.2021.108403</subfield><subfield code="2">doi</subfield></datafield><datafield tag="028" ind1="5" ind2="2"><subfield code="a">/cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001522.pica</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)ELV055187110</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ELSEVIER)S1389-1286(21)00377-7</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="4"><subfield code="a">610</subfield><subfield code="q">VZ</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">44.44</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Hou, Changsheng</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">DMatrix: Toward fast and accurate queries in graph stream</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2021transfer abstract</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">The graph stream has recently arisen in many interactive scenarios. Characterizing with large volume and high dynamic, graph streams are known to be difficult for high-speed summary and analysis, especially provided with limited resource availability. Existing solutions mainly use sketch-based methods to estimate the weight of items (e.g., Count-Min Sketch) and preserve the underlying graph structure information (e.g., TCM). Unfortunately, these solutions neither support complex graph-based queries nor achieve efficient real-time queries. In view of these limitations, we design DMatrix, a novel 3-dimensional graph sketch to facilitate fast and accurate queries in graph stream. Both structural query and weight-based estimation are supported with DMatrix. Through the integration of representative key reservation and majority voting, DMatrix can effectively narrow the error bounds of queries with real-time response efficiency. Both theoretical analysis and experimental results confirm that our solution is superior in accuracy and efficiency comparing with the state-of-the-art.</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">The graph stream has recently arisen in many interactive scenarios. Characterizing with large volume and high dynamic, graph streams are known to be difficult for high-speed summary and analysis, especially provided with limited resource availability. Existing solutions mainly use sketch-based methods to estimate the weight of items (e.g., Count-Min Sketch) and preserve the underlying graph structure information (e.g., TCM). Unfortunately, these solutions neither support complex graph-based queries nor achieve efficient real-time queries. In view of these limitations, we design DMatrix, a novel 3-dimensional graph sketch to facilitate fast and accurate queries in graph stream. Both structural query and weight-based estimation are supported with DMatrix. Through the integration of representative key reservation and majority voting, DMatrix can effectively narrow the error bounds of queries with real-time response efficiency. Both theoretical analysis and experimental results confirm that our solution is superior in accuracy and efficiency comparing with the state-of-the-art.</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Graph stream</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Graph sketch</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Approximate query</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Hou, Bingnan</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Zhou, Tongqing</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Cai, Zhiping</subfield><subfield code="4">oth</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="n">Elsevier</subfield><subfield code="a">Poo, J.L. ELSEVIER</subfield><subfield code="t">Pharmacokinetics of the Antifibrotic Drug Pirfenidone in Child Pugh A and B Cirrhotic Patients Compared to Healthy Age-Matched Controls</subfield><subfield code="d">2016</subfield><subfield code="d">the international journal of computer and telecommunications networking</subfield><subfield code="g">Amsterdam [u.a.]</subfield><subfield code="w">(DE-627)ELV013796984</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:198</subfield><subfield code="g">year:2021</subfield><subfield code="g">day:24</subfield><subfield code="g">month:10</subfield><subfield code="g">pages:0</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.1016/j.comnet.2021.108403</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="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_40</subfield></datafield><datafield tag="936" ind1="b" ind2="k"><subfield code="a">44.44</subfield><subfield code="j">Parasitologie</subfield><subfield code="x">Medizin</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">198</subfield><subfield code="j">2021</subfield><subfield code="b">24</subfield><subfield code="c">1024</subfield><subfield code="h">0</subfield></datafield></record></collection>
|
author |
Hou, Changsheng |
spellingShingle |
Hou, Changsheng ddc 610 bkl 44.44 Elsevier Graph stream Elsevier Graph sketch Elsevier Approximate query DMatrix: Toward fast and accurate queries in graph stream |
authorStr |
Hou, Changsheng |
ppnlink_with_tag_str_mv |
@@773@@(DE-627)ELV013796984 |
format |
electronic Article |
dewey-ones |
610 - Medicine & health |
delete_txt_mv |
keep |
author_role |
aut |
collection |
elsevier |
remote_str |
true |
illustrated |
Not Illustrated |
topic_title |
610 VZ 44.44 bkl DMatrix: Toward fast and accurate queries in graph stream Graph stream Elsevier Graph sketch Elsevier Approximate query Elsevier |
topic |
ddc 610 bkl 44.44 Elsevier Graph stream Elsevier Graph sketch Elsevier Approximate query |
topic_unstemmed |
ddc 610 bkl 44.44 Elsevier Graph stream Elsevier Graph sketch Elsevier Approximate query |
topic_browse |
ddc 610 bkl 44.44 Elsevier Graph stream Elsevier Graph sketch Elsevier Approximate query |
format_facet |
Elektronische Aufsätze Aufsätze Elektronische Ressource |
format_main_str_mv |
Text Zeitschrift/Artikel |
carriertype_str_mv |
zu |
author2_variant |
b h bh t z tz z c zc |
hierarchy_parent_title |
Pharmacokinetics of the Antifibrotic Drug Pirfenidone in Child Pugh A and B Cirrhotic Patients Compared to Healthy Age-Matched Controls |
hierarchy_parent_id |
ELV013796984 |
dewey-tens |
610 - Medicine & health |
hierarchy_top_title |
Pharmacokinetics of the Antifibrotic Drug Pirfenidone in Child Pugh A and B Cirrhotic Patients Compared to Healthy Age-Matched Controls |
isfreeaccess_txt |
false |
familylinks_str_mv |
(DE-627)ELV013796984 |
title |
DMatrix: Toward fast and accurate queries in graph stream |
ctrlnum |
(DE-627)ELV055187110 (ELSEVIER)S1389-1286(21)00377-7 |
title_full |
DMatrix: Toward fast and accurate queries in graph stream |
author_sort |
Hou, Changsheng |
journal |
Pharmacokinetics of the Antifibrotic Drug Pirfenidone in Child Pugh A and B Cirrhotic Patients Compared to Healthy Age-Matched Controls |
journalStr |
Pharmacokinetics of the Antifibrotic Drug Pirfenidone in Child Pugh A and B Cirrhotic Patients Compared to Healthy Age-Matched Controls |
lang_code |
eng |
isOA_bool |
false |
dewey-hundreds |
600 - Technology |
recordtype |
marc |
publishDateSort |
2021 |
contenttype_str_mv |
zzz |
container_start_page |
0 |
author_browse |
Hou, Changsheng |
container_volume |
198 |
class |
610 VZ 44.44 bkl |
format_se |
Elektronische Aufsätze |
author-letter |
Hou, Changsheng |
doi_str_mv |
10.1016/j.comnet.2021.108403 |
dewey-full |
610 |
title_sort |
dmatrix: toward fast and accurate queries in graph stream |
title_auth |
DMatrix: Toward fast and accurate queries in graph stream |
abstract |
The graph stream has recently arisen in many interactive scenarios. Characterizing with large volume and high dynamic, graph streams are known to be difficult for high-speed summary and analysis, especially provided with limited resource availability. Existing solutions mainly use sketch-based methods to estimate the weight of items (e.g., Count-Min Sketch) and preserve the underlying graph structure information (e.g., TCM). Unfortunately, these solutions neither support complex graph-based queries nor achieve efficient real-time queries. In view of these limitations, we design DMatrix, a novel 3-dimensional graph sketch to facilitate fast and accurate queries in graph stream. Both structural query and weight-based estimation are supported with DMatrix. Through the integration of representative key reservation and majority voting, DMatrix can effectively narrow the error bounds of queries with real-time response efficiency. Both theoretical analysis and experimental results confirm that our solution is superior in accuracy and efficiency comparing with the state-of-the-art. |
abstractGer |
The graph stream has recently arisen in many interactive scenarios. Characterizing with large volume and high dynamic, graph streams are known to be difficult for high-speed summary and analysis, especially provided with limited resource availability. Existing solutions mainly use sketch-based methods to estimate the weight of items (e.g., Count-Min Sketch) and preserve the underlying graph structure information (e.g., TCM). Unfortunately, these solutions neither support complex graph-based queries nor achieve efficient real-time queries. In view of these limitations, we design DMatrix, a novel 3-dimensional graph sketch to facilitate fast and accurate queries in graph stream. Both structural query and weight-based estimation are supported with DMatrix. Through the integration of representative key reservation and majority voting, DMatrix can effectively narrow the error bounds of queries with real-time response efficiency. Both theoretical analysis and experimental results confirm that our solution is superior in accuracy and efficiency comparing with the state-of-the-art. |
abstract_unstemmed |
The graph stream has recently arisen in many interactive scenarios. Characterizing with large volume and high dynamic, graph streams are known to be difficult for high-speed summary and analysis, especially provided with limited resource availability. Existing solutions mainly use sketch-based methods to estimate the weight of items (e.g., Count-Min Sketch) and preserve the underlying graph structure information (e.g., TCM). Unfortunately, these solutions neither support complex graph-based queries nor achieve efficient real-time queries. In view of these limitations, we design DMatrix, a novel 3-dimensional graph sketch to facilitate fast and accurate queries in graph stream. Both structural query and weight-based estimation are supported with DMatrix. Through the integration of representative key reservation and majority voting, DMatrix can effectively narrow the error bounds of queries with real-time response efficiency. Both theoretical analysis and experimental results confirm that our solution is superior in accuracy and efficiency comparing with the state-of-the-art. |
collection_details |
GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA GBV_ILN_40 |
title_short |
DMatrix: Toward fast and accurate queries in graph stream |
url |
https://doi.org/10.1016/j.comnet.2021.108403 |
remote_bool |
true |
author2 |
Hou, Bingnan Zhou, Tongqing Cai, Zhiping |
author2Str |
Hou, Bingnan Zhou, Tongqing Cai, Zhiping |
ppnlink |
ELV013796984 |
mediatype_str_mv |
z |
isOA_txt |
false |
hochschulschrift_bool |
false |
author2_role |
oth oth oth |
doi_str |
10.1016/j.comnet.2021.108403 |
up_date |
2024-07-06T16:51:26.852Z |
_version_ |
1803849235804717056 |
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">ELV055187110</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230626041339.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">220105s2021 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1016/j.comnet.2021.108403</subfield><subfield code="2">doi</subfield></datafield><datafield tag="028" ind1="5" ind2="2"><subfield code="a">/cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001522.pica</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)ELV055187110</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ELSEVIER)S1389-1286(21)00377-7</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="4"><subfield code="a">610</subfield><subfield code="q">VZ</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">44.44</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Hou, Changsheng</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">DMatrix: Toward fast and accurate queries in graph stream</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2021transfer abstract</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">The graph stream has recently arisen in many interactive scenarios. Characterizing with large volume and high dynamic, graph streams are known to be difficult for high-speed summary and analysis, especially provided with limited resource availability. Existing solutions mainly use sketch-based methods to estimate the weight of items (e.g., Count-Min Sketch) and preserve the underlying graph structure information (e.g., TCM). Unfortunately, these solutions neither support complex graph-based queries nor achieve efficient real-time queries. In view of these limitations, we design DMatrix, a novel 3-dimensional graph sketch to facilitate fast and accurate queries in graph stream. Both structural query and weight-based estimation are supported with DMatrix. Through the integration of representative key reservation and majority voting, DMatrix can effectively narrow the error bounds of queries with real-time response efficiency. Both theoretical analysis and experimental results confirm that our solution is superior in accuracy and efficiency comparing with the state-of-the-art.</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">The graph stream has recently arisen in many interactive scenarios. Characterizing with large volume and high dynamic, graph streams are known to be difficult for high-speed summary and analysis, especially provided with limited resource availability. Existing solutions mainly use sketch-based methods to estimate the weight of items (e.g., Count-Min Sketch) and preserve the underlying graph structure information (e.g., TCM). Unfortunately, these solutions neither support complex graph-based queries nor achieve efficient real-time queries. In view of these limitations, we design DMatrix, a novel 3-dimensional graph sketch to facilitate fast and accurate queries in graph stream. Both structural query and weight-based estimation are supported with DMatrix. Through the integration of representative key reservation and majority voting, DMatrix can effectively narrow the error bounds of queries with real-time response efficiency. Both theoretical analysis and experimental results confirm that our solution is superior in accuracy and efficiency comparing with the state-of-the-art.</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Graph stream</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Graph sketch</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Approximate query</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Hou, Bingnan</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Zhou, Tongqing</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Cai, Zhiping</subfield><subfield code="4">oth</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="n">Elsevier</subfield><subfield code="a">Poo, J.L. ELSEVIER</subfield><subfield code="t">Pharmacokinetics of the Antifibrotic Drug Pirfenidone in Child Pugh A and B Cirrhotic Patients Compared to Healthy Age-Matched Controls</subfield><subfield code="d">2016</subfield><subfield code="d">the international journal of computer and telecommunications networking</subfield><subfield code="g">Amsterdam [u.a.]</subfield><subfield code="w">(DE-627)ELV013796984</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:198</subfield><subfield code="g">year:2021</subfield><subfield code="g">day:24</subfield><subfield code="g">month:10</subfield><subfield code="g">pages:0</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.1016/j.comnet.2021.108403</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="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_40</subfield></datafield><datafield tag="936" ind1="b" ind2="k"><subfield code="a">44.44</subfield><subfield code="j">Parasitologie</subfield><subfield code="x">Medizin</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">198</subfield><subfield code="j">2021</subfield><subfield code="b">24</subfield><subfield code="c">1024</subfield><subfield code="h">0</subfield></datafield></record></collection>
|
score |
7.3999805 |