Probabilistic temporal databases, I: algebra
Dyreson and Snodgrass have drawn attention to the fact that, in many temporal database applications, there is often uncertainty about the start time of events, the end time of events, and the duration of events. When the granularity of time is small (e.g., milliseconds), a statement such as "Pa...
Gespeichert in:
Veröffentlicht in: | ACM transactions on database systems 2001-03, Vol.26 (1), p.41-95 |
---|---|
Hauptverfasser: | , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | 95 |
---|---|
container_issue | 1 |
container_start_page | 41 |
container_title | ACM transactions on database systems |
container_volume | 26 |
creator | Dekhtyar, Alex Ross, Robert Subrahmanian, V. S. |
description | Dyreson and Snodgrass have drawn attention to the fact that, in many temporal database applications, there is often uncertainty about the start time of events, the end time of events, and the duration of events. When the granularity of time is small (e.g., milliseconds), a statement such as "Packet p was shipped sometime during the first 5 days of January, 1998" leads to a massive amount of uncertainty (5×24×60×60×1000) possibilities. As noted in Zaniolo et al. [1997], past attempts to deal with uncertainty in databases have been restricted to relatively small amounts of uncertainty in attributes. Dyreson and Snodgrass have taken an important first step towards solving this problem. In this article, we first introduce the syntax of Temporal-Probabilistic (TP) relations and then show how they can be converted to an explicit, significantly more space-consuming form, called Annotated Relations. We then present a theoretical annotated temporal algebra (TATA). Being explicit, TATA is convenient for specifying how the algebraic operations should behave, but is impractical to use because annotated relations are overwhelmingly large. Next, we present a temporal probabilistic algebra (TPA). We show that our definition of the TP-algebra provides a correct implementation of TATA despite the fact that it operates on implicit, succinct TP-relations instead of overwhemingly large annotated relations. Finally, we report on timings for an implementation of the TP-Algebra built on top of ODBC. |
doi_str_mv | 10.1145/383734.383736 |
format | Article |
fullrecord | <record><control><sourceid>gale_proqu</sourceid><recordid>TN_cdi_proquest_journals_195304379</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><galeid>A79742753</galeid><sourcerecordid>A79742753</sourcerecordid><originalsourceid>FETCH-LOGICAL-a338t-2835f0fb7c467490ec489376aff42f40d7574bcc416bf870126a8eee844169ef3</originalsourceid><addsrcrecordid>eNp90UtLAzEQB_AgCtbH0YO3otduTTaTZPdYio9CQQ96Dtl0UlL2UZPtwW9vdIt6KJLDHyY_MhOGkCtGp4yBuOMFVxym3yGPyIgJoTKQAMdkRLnMM1EycUrOYtxQSqEo1YjcvoSuMpWvfey9HffYbLtg6vHK9KYyEeNkvLggJ87UES_3eU7eHu5f50_Z8vlxMZ8tM8N50Wd5wYWjrlIWpIKSok0tuJLGOcgd0JUSCiprgcnKFYqyXJoCEQtIlRIdPyc3w7vb0L3vMPZ60-1Cm1pqVgpOgavyF61Njdq3ruuDsY2PVs9UqSBXgic0OYDW2GL6W9ei86n8l2cHeDorbLz9x9vQxRjQ6W3wjQkfmlH9tQo9rGIImfz14NOgP3R_9wlg739V</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>195304379</pqid></control><display><type>article</type><title>Probabilistic temporal databases, I: algebra</title><source>Access via ACM Digital Library</source><creator>Dekhtyar, Alex ; Ross, Robert ; Subrahmanian, V. S.</creator><creatorcontrib>Dekhtyar, Alex ; Ross, Robert ; Subrahmanian, V. S.</creatorcontrib><description>Dyreson and Snodgrass have drawn attention to the fact that, in many temporal database applications, there is often uncertainty about the start time of events, the end time of events, and the duration of events. When the granularity of time is small (e.g., milliseconds), a statement such as "Packet p was shipped sometime during the first 5 days of January, 1998" leads to a massive amount of uncertainty (5×24×60×60×1000) possibilities. As noted in Zaniolo et al. [1997], past attempts to deal with uncertainty in databases have been restricted to relatively small amounts of uncertainty in attributes. Dyreson and Snodgrass have taken an important first step towards solving this problem. In this article, we first introduce the syntax of Temporal-Probabilistic (TP) relations and then show how they can be converted to an explicit, significantly more space-consuming form, called Annotated Relations. We then present a theoretical annotated temporal algebra (TATA). Being explicit, TATA is convenient for specifying how the algebraic operations should behave, but is impractical to use because annotated relations are overwhelmingly large. Next, we present a temporal probabilistic algebra (TPA). We show that our definition of the TP-algebra provides a correct implementation of TATA despite the fact that it operates on implicit, succinct TP-relations instead of overwhemingly large annotated relations. Finally, we report on timings for an implementation of the TP-Algebra built on top of ODBC.</description><identifier>ISSN: 0362-5915</identifier><identifier>EISSN: 1557-4644</identifier><identifier>DOI: 10.1145/383734.383736</identifier><identifier>CODEN: ATDSD3</identifier><language>eng</language><publisher>New York, NY, USA: ACM</publisher><subject>Algebra ; Artificial intelligence ; Combinatorial probabilities ; Computing methodologies ; Database administration ; Geometric probabilities ; Information technology ; Information theory ; Knowledge representation and reasoning ; Logic ; Mathematics of computing ; Modal and temporal logics ; Modeling and simulation ; Probabilistic reasoning ; Probabilities ; Query processing ; Scheduling (Management) ; Simulation theory ; Software ; Statistics ; Systems theory ; Theory of computation ; Vagueness and fuzzy logic</subject><ispartof>ACM transactions on database systems, 2001-03, Vol.26 (1), p.41-95</ispartof><rights>ACM</rights><rights>COPYRIGHT 2001 Association for Computing Machinery, Inc.</rights><rights>Copyright Association for Computing Machinery Mar 2001</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-a338t-2835f0fb7c467490ec489376aff42f40d7574bcc416bf870126a8eee844169ef3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://dl.acm.org/doi/pdf/10.1145/383734.383736$$EPDF$$P50$$Gacm$$H</linktopdf><link.rule.ids>315,781,785,2283,27929,27930,40201,76233</link.rule.ids></links><search><creatorcontrib>Dekhtyar, Alex</creatorcontrib><creatorcontrib>Ross, Robert</creatorcontrib><creatorcontrib>Subrahmanian, V. S.</creatorcontrib><title>Probabilistic temporal databases, I: algebra</title><title>ACM transactions on database systems</title><addtitle>ACM TODS</addtitle><description>Dyreson and Snodgrass have drawn attention to the fact that, in many temporal database applications, there is often uncertainty about the start time of events, the end time of events, and the duration of events. When the granularity of time is small (e.g., milliseconds), a statement such as "Packet p was shipped sometime during the first 5 days of January, 1998" leads to a massive amount of uncertainty (5×24×60×60×1000) possibilities. As noted in Zaniolo et al. [1997], past attempts to deal with uncertainty in databases have been restricted to relatively small amounts of uncertainty in attributes. Dyreson and Snodgrass have taken an important first step towards solving this problem. In this article, we first introduce the syntax of Temporal-Probabilistic (TP) relations and then show how they can be converted to an explicit, significantly more space-consuming form, called Annotated Relations. We then present a theoretical annotated temporal algebra (TATA). Being explicit, TATA is convenient for specifying how the algebraic operations should behave, but is impractical to use because annotated relations are overwhelmingly large. Next, we present a temporal probabilistic algebra (TPA). We show that our definition of the TP-algebra provides a correct implementation of TATA despite the fact that it operates on implicit, succinct TP-relations instead of overwhemingly large annotated relations. Finally, we report on timings for an implementation of the TP-Algebra built on top of ODBC.</description><subject>Algebra</subject><subject>Artificial intelligence</subject><subject>Combinatorial probabilities</subject><subject>Computing methodologies</subject><subject>Database administration</subject><subject>Geometric probabilities</subject><subject>Information technology</subject><subject>Information theory</subject><subject>Knowledge representation and reasoning</subject><subject>Logic</subject><subject>Mathematics of computing</subject><subject>Modal and temporal logics</subject><subject>Modeling and simulation</subject><subject>Probabilistic reasoning</subject><subject>Probabilities</subject><subject>Query processing</subject><subject>Scheduling (Management)</subject><subject>Simulation theory</subject><subject>Software</subject><subject>Statistics</subject><subject>Systems theory</subject><subject>Theory of computation</subject><subject>Vagueness and fuzzy logic</subject><issn>0362-5915</issn><issn>1557-4644</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2001</creationdate><recordtype>article</recordtype><recordid>eNp90UtLAzEQB_AgCtbH0YO3otduTTaTZPdYio9CQQ96Dtl0UlL2UZPtwW9vdIt6KJLDHyY_MhOGkCtGp4yBuOMFVxym3yGPyIgJoTKQAMdkRLnMM1EycUrOYtxQSqEo1YjcvoSuMpWvfey9HffYbLtg6vHK9KYyEeNkvLggJ87UES_3eU7eHu5f50_Z8vlxMZ8tM8N50Wd5wYWjrlIWpIKSok0tuJLGOcgd0JUSCiprgcnKFYqyXJoCEQtIlRIdPyc3w7vb0L3vMPZ60-1Cm1pqVgpOgavyF61Njdq3ruuDsY2PVs9UqSBXgic0OYDW2GL6W9ei86n8l2cHeDorbLz9x9vQxRjQ6W3wjQkfmlH9tQo9rGIImfz14NOgP3R_9wlg739V</recordid><startdate>20010301</startdate><enddate>20010301</enddate><creator>Dekhtyar, Alex</creator><creator>Ross, Robert</creator><creator>Subrahmanian, V. S.</creator><general>ACM</general><general>Association for Computing Machinery, Inc</general><general>Association for Computing Machinery</general><scope>AAYXX</scope><scope>CITATION</scope><scope>JQ2</scope></search><sort><creationdate>20010301</creationdate><title>Probabilistic temporal databases, I</title><author>Dekhtyar, Alex ; Ross, Robert ; Subrahmanian, V. S.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a338t-2835f0fb7c467490ec489376aff42f40d7574bcc416bf870126a8eee844169ef3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2001</creationdate><topic>Algebra</topic><topic>Artificial intelligence</topic><topic>Combinatorial probabilities</topic><topic>Computing methodologies</topic><topic>Database administration</topic><topic>Geometric probabilities</topic><topic>Information technology</topic><topic>Information theory</topic><topic>Knowledge representation and reasoning</topic><topic>Logic</topic><topic>Mathematics of computing</topic><topic>Modal and temporal logics</topic><topic>Modeling and simulation</topic><topic>Probabilistic reasoning</topic><topic>Probabilities</topic><topic>Query processing</topic><topic>Scheduling (Management)</topic><topic>Simulation theory</topic><topic>Software</topic><topic>Statistics</topic><topic>Systems theory</topic><topic>Theory of computation</topic><topic>Vagueness and fuzzy logic</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Dekhtyar, Alex</creatorcontrib><creatorcontrib>Ross, Robert</creatorcontrib><creatorcontrib>Subrahmanian, V. S.</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Computer Science Collection</collection><jtitle>ACM transactions on database systems</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Dekhtyar, Alex</au><au>Ross, Robert</au><au>Subrahmanian, V. S.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Probabilistic temporal databases, I: algebra</atitle><jtitle>ACM transactions on database systems</jtitle><stitle>ACM TODS</stitle><date>2001-03-01</date><risdate>2001</risdate><volume>26</volume><issue>1</issue><spage>41</spage><epage>95</epage><pages>41-95</pages><issn>0362-5915</issn><eissn>1557-4644</eissn><coden>ATDSD3</coden><abstract>Dyreson and Snodgrass have drawn attention to the fact that, in many temporal database applications, there is often uncertainty about the start time of events, the end time of events, and the duration of events. When the granularity of time is small (e.g., milliseconds), a statement such as "Packet p was shipped sometime during the first 5 days of January, 1998" leads to a massive amount of uncertainty (5×24×60×60×1000) possibilities. As noted in Zaniolo et al. [1997], past attempts to deal with uncertainty in databases have been restricted to relatively small amounts of uncertainty in attributes. Dyreson and Snodgrass have taken an important first step towards solving this problem. In this article, we first introduce the syntax of Temporal-Probabilistic (TP) relations and then show how they can be converted to an explicit, significantly more space-consuming form, called Annotated Relations. We then present a theoretical annotated temporal algebra (TATA). Being explicit, TATA is convenient for specifying how the algebraic operations should behave, but is impractical to use because annotated relations are overwhelmingly large. Next, we present a temporal probabilistic algebra (TPA). We show that our definition of the TP-algebra provides a correct implementation of TATA despite the fact that it operates on implicit, succinct TP-relations instead of overwhemingly large annotated relations. Finally, we report on timings for an implementation of the TP-Algebra built on top of ODBC.</abstract><cop>New York, NY, USA</cop><pub>ACM</pub><doi>10.1145/383734.383736</doi><tpages>55</tpages></addata></record> |
fulltext | fulltext |
identifier | ISSN: 0362-5915 |
ispartof | ACM transactions on database systems, 2001-03, Vol.26 (1), p.41-95 |
issn | 0362-5915 1557-4644 |
language | eng |
recordid | cdi_proquest_journals_195304379 |
source | Access via ACM Digital Library |
subjects | Algebra Artificial intelligence Combinatorial probabilities Computing methodologies Database administration Geometric probabilities Information technology Information theory Knowledge representation and reasoning Logic Mathematics of computing Modal and temporal logics Modeling and simulation Probabilistic reasoning Probabilities Query processing Scheduling (Management) Simulation theory Software Statistics Systems theory Theory of computation Vagueness and fuzzy logic |
title | Probabilistic temporal databases, I: algebra |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-14T23%3A06%3A38IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-gale_proqu&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Probabilistic%20temporal%20databases,%20I:%20algebra&rft.jtitle=ACM%20transactions%20on%20database%20systems&rft.au=Dekhtyar,%20Alex&rft.date=2001-03-01&rft.volume=26&rft.issue=1&rft.spage=41&rft.epage=95&rft.pages=41-95&rft.issn=0362-5915&rft.eissn=1557-4644&rft.coden=ATDSD3&rft_id=info:doi/10.1145/383734.383736&rft_dat=%3Cgale_proqu%3EA79742753%3C/gale_proqu%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=195304379&rft_id=info:pmid/&rft_galeid=A79742753&rfr_iscdi=true |