Scalable semantic aware context storage
The number of connected devices collecting and distributing real-world information through various systems, is expected to soar in the coming years. As the number of such connected devices grows, it becomes increasingly difficult to store and share all these new sources of information. Several conte...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Antunes, Mário [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2016transfer abstract |
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| Schlagwörter: |
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| Umfang: |
9 |
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| Übergeordnetes Werk: |
Enthalten in: Surgeon-patient matching based on pairwise comparisons information for elective surgery - Jiang, Yan-Ping ELSEVIER, 2020, Amsterdam [u.a.] |
|---|---|
| Übergeordnetes Werk: |
volume:56 ; year:2016 ; pages:675-683 ; extent:9 |
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| DOI / URN: |
10.1016/j.future.2015.09.008 |
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| 520 | |a The number of connected devices collecting and distributing real-world information through various systems, is expected to soar in the coming years. As the number of such connected devices grows, it becomes increasingly difficult to store and share all these new sources of information. Several context representation schemes try to standardize this information, but none of them have been widely adopted. In previous work we addressed this challenge, however our solution had some drawbacks: poor semantic extraction and scalability. In this paper we discuss ways to efficiently deal with representation schemes’ diversity and propose a novel d -dimension organization model. Our evaluation shows that d -dimension model improves scalability and semantic extraction. | ||
| 520 | |a The number of connected devices collecting and distributing real-world information through various systems, is expected to soar in the coming years. As the number of such connected devices grows, it becomes increasingly difficult to store and share all these new sources of information. Several context representation schemes try to standardize this information, but none of them have been widely adopted. In previous work we addressed this challenge, however our solution had some drawbacks: poor semantic extraction and scalability. In this paper we discuss ways to efficiently deal with representation schemes’ diversity and propose a novel d -dimension organization model. Our evaluation shows that d -dimension model improves scalability and semantic extraction. | ||
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10.1016/j.future.2015.09.008 doi GBVA2016004000022.pica (DE-627)ELV01911317X (ELSEVIER)S0167-739X(15)00288-5 DE-627 ger DE-627 rakwb eng 004 004 DE-600 004 VZ 85.35 bkl 54.80 bkl Antunes, Mário verfasserin aut Scalable semantic aware context storage 2016transfer abstract 9 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier The number of connected devices collecting and distributing real-world information through various systems, is expected to soar in the coming years. As the number of such connected devices grows, it becomes increasingly difficult to store and share all these new sources of information. Several context representation schemes try to standardize this information, but none of them have been widely adopted. In previous work we addressed this challenge, however our solution had some drawbacks: poor semantic extraction and scalability. In this paper we discuss ways to efficiently deal with representation schemes’ diversity and propose a novel d -dimension organization model. Our evaluation shows that d -dimension model improves scalability and semantic extraction. The number of connected devices collecting and distributing real-world information through various systems, is expected to soar in the coming years. As the number of such connected devices grows, it becomes increasingly difficult to store and share all these new sources of information. Several context representation schemes try to standardize this information, but none of them have been widely adopted. In previous work we addressed this challenge, however our solution had some drawbacks: poor semantic extraction and scalability. In this paper we discuss ways to efficiently deal with representation schemes’ diversity and propose a novel d -dimension organization model. Our evaluation shows that d -dimension model improves scalability and semantic extraction. M2M Elsevier Context information Elsevier IoT Elsevier Gomes, Diogo oth Aguiar, Rui L. oth Enthalten in Elsevier Science Jiang, Yan-Ping ELSEVIER Surgeon-patient matching based on pairwise comparisons information for elective surgery 2020 Amsterdam [u.a.] (DE-627)ELV004280385 volume:56 year:2016 pages:675-683 extent:9 https://doi.org/10.1016/j.future.2015.09.008 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U 85.35 Fertigung VZ 54.80 Angewandte Informatik VZ AR 56 2016 675-683 9 045F 004 |
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10.1016/j.future.2015.09.008 doi GBVA2016004000022.pica (DE-627)ELV01911317X (ELSEVIER)S0167-739X(15)00288-5 DE-627 ger DE-627 rakwb eng 004 004 DE-600 004 VZ 85.35 bkl 54.80 bkl Antunes, Mário verfasserin aut Scalable semantic aware context storage 2016transfer abstract 9 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier The number of connected devices collecting and distributing real-world information through various systems, is expected to soar in the coming years. As the number of such connected devices grows, it becomes increasingly difficult to store and share all these new sources of information. Several context representation schemes try to standardize this information, but none of them have been widely adopted. In previous work we addressed this challenge, however our solution had some drawbacks: poor semantic extraction and scalability. In this paper we discuss ways to efficiently deal with representation schemes’ diversity and propose a novel d -dimension organization model. Our evaluation shows that d -dimension model improves scalability and semantic extraction. The number of connected devices collecting and distributing real-world information through various systems, is expected to soar in the coming years. As the number of such connected devices grows, it becomes increasingly difficult to store and share all these new sources of information. Several context representation schemes try to standardize this information, but none of them have been widely adopted. In previous work we addressed this challenge, however our solution had some drawbacks: poor semantic extraction and scalability. In this paper we discuss ways to efficiently deal with representation schemes’ diversity and propose a novel d -dimension organization model. Our evaluation shows that d -dimension model improves scalability and semantic extraction. M2M Elsevier Context information Elsevier IoT Elsevier Gomes, Diogo oth Aguiar, Rui L. oth Enthalten in Elsevier Science Jiang, Yan-Ping ELSEVIER Surgeon-patient matching based on pairwise comparisons information for elective surgery 2020 Amsterdam [u.a.] (DE-627)ELV004280385 volume:56 year:2016 pages:675-683 extent:9 https://doi.org/10.1016/j.future.2015.09.008 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U 85.35 Fertigung VZ 54.80 Angewandte Informatik VZ AR 56 2016 675-683 9 045F 004 |
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10.1016/j.future.2015.09.008 doi GBVA2016004000022.pica (DE-627)ELV01911317X (ELSEVIER)S0167-739X(15)00288-5 DE-627 ger DE-627 rakwb eng 004 004 DE-600 004 VZ 85.35 bkl 54.80 bkl Antunes, Mário verfasserin aut Scalable semantic aware context storage 2016transfer abstract 9 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier The number of connected devices collecting and distributing real-world information through various systems, is expected to soar in the coming years. As the number of such connected devices grows, it becomes increasingly difficult to store and share all these new sources of information. Several context representation schemes try to standardize this information, but none of them have been widely adopted. In previous work we addressed this challenge, however our solution had some drawbacks: poor semantic extraction and scalability. In this paper we discuss ways to efficiently deal with representation schemes’ diversity and propose a novel d -dimension organization model. Our evaluation shows that d -dimension model improves scalability and semantic extraction. The number of connected devices collecting and distributing real-world information through various systems, is expected to soar in the coming years. As the number of such connected devices grows, it becomes increasingly difficult to store and share all these new sources of information. Several context representation schemes try to standardize this information, but none of them have been widely adopted. In previous work we addressed this challenge, however our solution had some drawbacks: poor semantic extraction and scalability. In this paper we discuss ways to efficiently deal with representation schemes’ diversity and propose a novel d -dimension organization model. Our evaluation shows that d -dimension model improves scalability and semantic extraction. M2M Elsevier Context information Elsevier IoT Elsevier Gomes, Diogo oth Aguiar, Rui L. oth Enthalten in Elsevier Science Jiang, Yan-Ping ELSEVIER Surgeon-patient matching based on pairwise comparisons information for elective surgery 2020 Amsterdam [u.a.] (DE-627)ELV004280385 volume:56 year:2016 pages:675-683 extent:9 https://doi.org/10.1016/j.future.2015.09.008 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U 85.35 Fertigung VZ 54.80 Angewandte Informatik VZ AR 56 2016 675-683 9 045F 004 |
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The number of connected devices collecting and distributing real-world information through various systems, is expected to soar in the coming years. As the number of such connected devices grows, it becomes increasingly difficult to store and share all these new sources of information. Several context representation schemes try to standardize this information, but none of them have been widely adopted. In previous work we addressed this challenge, however our solution had some drawbacks: poor semantic extraction and scalability. In this paper we discuss ways to efficiently deal with representation schemes’ diversity and propose a novel d -dimension organization model. Our evaluation shows that d -dimension model improves scalability and semantic extraction. |
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The number of connected devices collecting and distributing real-world information through various systems, is expected to soar in the coming years. As the number of such connected devices grows, it becomes increasingly difficult to store and share all these new sources of information. Several context representation schemes try to standardize this information, but none of them have been widely adopted. In previous work we addressed this challenge, however our solution had some drawbacks: poor semantic extraction and scalability. In this paper we discuss ways to efficiently deal with representation schemes’ diversity and propose a novel d -dimension organization model. Our evaluation shows that d -dimension model improves scalability and semantic extraction. |
| abstract_unstemmed |
The number of connected devices collecting and distributing real-world information through various systems, is expected to soar in the coming years. As the number of such connected devices grows, it becomes increasingly difficult to store and share all these new sources of information. Several context representation schemes try to standardize this information, but none of them have been widely adopted. In previous work we addressed this challenge, however our solution had some drawbacks: poor semantic extraction and scalability. In this paper we discuss ways to efficiently deal with representation schemes’ diversity and propose a novel d -dimension organization model. Our evaluation shows that d -dimension model improves scalability and semantic extraction. |
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Scalable semantic aware context storage |
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Gomes, Diogo Aguiar, Rui L. |
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10.1016/j.future.2015.09.008 |
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2024-07-06T20:36:13.239Z |
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7.399722 |