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
Gespeichert in:
| Autor*in: |
Hou, Changsheng [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2021transfer abstract |
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| Schlagwörter: |
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| 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.] |
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| Übergeordnetes Werk: |
volume:198 ; year:2021 ; day:24 ; month:10 ; pages:0 |
| Links: |
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| DOI / URN: |
10.1016/j.comnet.2021.108403 |
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ELV055187110 |
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| 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. | ||
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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 |
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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 |
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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 |
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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 |
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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 |
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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 |
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Pharmacokinetics of the Antifibrotic Drug Pirfenidone in Child Pugh A and B Cirrhotic Patients Compared to Healthy Age-Matched Controls |
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Pharmacokinetics of the Antifibrotic Drug Pirfenidone in Child Pugh A and B Cirrhotic Patients Compared to Healthy Age-Matched Controls |
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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. |
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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. |
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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. |
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