Cover of: Time Granularities in Databases, Data Mining, and Temporal Reasoning | Claudio Bettini

Time Granularities in Databases, Data Mining, and Temporal Reasoning

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Springer
Databases & data structures, Temporal databases, Data mining, Database Engineering, Computers, Computers - Data Base Management, Information Technology, Computer Books: General, Database management, Artificial Intelligence - General, Database Management - General, Computers / Database Management / Ge
The Physical Object
FormatHardcover
ID Numbers
Open LibraryOL9063242M
ISBN 103540669973
ISBN 139783540669975

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Time Granularities in Databases, Data Mining, and Temporal ReasoningCited by: Moreover, any graduate student working on time representation and reasoning, either in data or knowledge bases, should definitely read it.

Keywords Temporal database calendars data mining database information system knowledge base knowledge discovery temporal reasoning time. System support for reasoning about these units, called granularities in this book, is important for the efficient design, use, and implementation of such applications.

The book deals with Time Granularities in Databases aspects of temporal information and provides a unifying model for granularities. Request PDF | On Jan 1,Claudio Bettini and others published Time Granularities in Databases, Data Mining, and Temporal Reasoning | Find, read and.

“Time Granularities in Databases, Data Mining, and Temporal Reasoning” (Book Review) Massimo Franceschet Department of Sciences, University of Chieti-Pescara, Italy E-mail: [email protected] Angelo Montanari Department of Computer Science, University of Udine, Italy E-mail: [email protected] In this paper, a formalism for a specific temporal data mining task (the discovery of rules, inferred from databases of events having a temporal dimension), is defined.

The proposed theoretical framework, based on first-order temporal logic, allows the definition of the main notions (event, temporal rule, confidence) in a formal way. of time granularity or temporal operations must be generalized to cope with data associated with different temporal domains.

In both cases, a precise semantics for time granularity is and Temporal Reasoning book [3, 12, 18, 26, 37, 38, 45, 51, 54, 58, 59].

† Time Granularities in Databases regard to data mining, a huge amount of data is collected every day in the form of event-time sequences. Web services for time granularity reasoning to temporal data mining, from querying databases storing data in different granularities to constraint C.

Bettini, S. Jajodia, and X. Wang. Time Granularities in Databases, Temporal Reasoning, and Data Mining. Springer, [3] C. Bettini, X. Wang, S. Jajodia, Solving Multi. Recently, a comprehensive book on temporal granularities in databases, data mining, and temporal reasoning has been published.

Bettini et al. deals with several aspects of temporal information and provides a unifying model for granularities. The underlying data model considered in is the relational one. Time Granularities in Databases, Data Mining, and Temporal Reasoning mail discussions initiated during the preparation of the first book on temporal databases, Temporal Databases: Theory.

@ARTICLE{Franceschet_timegranularities, author = {Massimo Franceschet and Angelo Montanari}, title = {Time granularities in databases, data mining, and temporal reasoning, by Claudio}, journal = {Bettini, Sushil Jajodia, and Sean X.

Wang (book review). Online download time granularities databases data mining and temporal reasoning time granularities databases data mining and temporal reasoning claudio bettini sushil g.

A timeseries database. I know could just use datetime and ignore the other components the date but whats the best way this without storing more info than actually need.

Get this from a library. Time granularities in databases, data mining, and temporal reasoning. [Claudio Bettini; Sushil Jajodia; Sean Wang] -- "Calendar units, such as months and days, clock units, such as hours and seconds, and specialized units, such as business days and academic years, play a major role in a wide range of information.

Time granularities in databases, data mining, and temporal reasoning, by Claudio. temporal constraint reasoning, and natural language processing. Any time granularity can be viewed as the partitioning of a temporal domain in groups of elements, where each group is perceived as an indivisible unit (a granule).

The book aims at providing Author: Massimo Franceschet and Angelo Montanari. Querying Temporal Clinical Databases with Different Time Granularities: the GCH-OSQL Language.

In Proceedings of the Annual Symposium on Computer Applications in Medical Care (SCAMC), pagesNew-Orleans, USA, Google Scholar; C. Combi, M. Franceschet, and A. Peron. Representing and Reasoning about Temporal Granularities.

Time Granularities in Databases, Data Mining, and Temporal Reasoning Claudio Bettini, Sushil Jajodia, Sean Wang Limited preview - Einstein's Clocks, Poincaré's Maps: Empires of Time.

Read Database Mining: Propositionalization for Knowledge Discovery in Relational Databases Ebook New Book Time Granularities in Databases, Data Mining, and Temporal Reasoning Ebook Advances in Spatial and Temporal Databases: 7th International Symposium, SSTDRedondo.

EstellaDowd. Books Advances in Spatial and Temporal. Abstract. The notion of time granularity comes into play in a variety of problems involving time representation and management in database applications, including temporal database design, temporal data conversion, temporal database inter-operability, temporal constraint reasoning, data mining, and time management in workflow systems.

Claudio Bettini, S. Jajodia and Sean X. Wang, Time Granularities in Databases, Data Mining and Temporal Reasoning, Springer. Google Scholar Digital Library Claudio Bettini, Sean X. Wang, S. Jajodia and Jia-Ling Lin, Discovering Frequent Event Patterns with Multiple Granularities in Time Sequences, IEEE Transactions on Knowledge and Data.

The Protégé-Owl SWRLTab and Temporal Data Mining in Surgery Guenter Tusch 1,2, Martin O’Connor 1, clinical data come with different time granularities, hourly, daily, monthly or yearly.

Second, clinical concepts captured in the valid time model as used in temporal database research and in temporal. Background. The historical relational data model (HRDM) provides an example of a highly sophisticated representation of the temporal validity of assertions to a database.

9 It allows a user or applications programmer to specify the temporal interval over which an assertion is valid at the table level, the tuple level, or the attribute level.

This internal temporal representation provides the. In many real-world applications, temporal information is often imprecise about the temporal location of events (indeterminacy) and comes at different granularities.

Formalisms for reasoning about events and change, such as the Event Calculus (EC) and the Situation Calculus, do not usually provide mechanisms for handling such information, and very little research has been devoted.

Spatiotemporal Data Time & Space:The inherent attributes of any existing object and event. statistic distortion results from the loss of data among granularities. Time Granularities in Databases, Data Mining, and Temporal Reasoning. Springer () M.

Sester: Abstraction of GeoDatabases. databases, real-time databases), and inter-relationships between temporal databases and temporal reasoning in artificial intelligence.

Some of the in-vited participants have also been involved in the standardization activities of the temporal community. Having a diverse group that shared a focus on. In proceedings of the International Symposium on temporal representation and reasoning (TIME), pages[PDF, DOI] M.

Franceschet and A. Montanari. Time Granularities in Databases, Data Mining, and Temporal Reasoning.

Details Time Granularities in Databases, Data Mining, and Temporal Reasoning EPUB

By Claudio Bettini, Sushil Jajodia, and Sean X. Wang (book review). The Computer Journal, 45(6), pagesIt has been an active research area for about half a century in the field of artificial intelligence and has applications in many related research areas, including NLP, 1 data mining, 2 robotics, 3 and database design and query.

4 We limit the scope of this introduction to temporal reasoning in NLP, with a focus on applications in clinical. Mining Temporal Sequential Patterns Based on Multi-granularities 3 Problem Formulation Time granularity In order to formally define temporal sequence pattern that involves time granularities, we first review the notion of a time granularity [15].

Definition 1. This paper focuses on the identification of temporal trends involving different granularities in clinical databases, where data are temporal in nature: for example, while follow-up visit data are usually stored at the granularity of working days, queries on these data could require to consider trends either at the granularity of months (“find patients who had an increase of systolic blood.

temporal model.: implementation challenges. Time Granularities in Databases, Data Mining, and Temporal Reasoning. Schmidtke, W. Woo. A size-based qualitative approach to the Supporting temporal reasoning by mapping calendar expressions to minimal periodic sets.

JAIR 6. Pozzani, C. Combi. An inference system for. A clustering-based data reduction for very large spatio-temporal datasets Nhien-An Le-Khac1, Martin Bue2, Michael Whelan1, M-Tahar Kechadi1, 1School of Computer Science and Informatics, University College Dublin, Belfield, Dublin 4, Ireland 2Ecole Polytechnique Universitaire de Lille, Villeneuve d'Ascq cedex, France 1{, ,i}@.

Description Time Granularities in Databases, Data Mining, and Temporal Reasoning PDF

ifications, knowledge representation and temporal databases that do support a limited concept of time granularity are proposed in [12]–[14].

Finally, Bettini et al. [15], [16] provide a formal framework for expressing data mining tasks involving time granularities, investigate the formal relationships among.temporal granularities (e.g., [28]). A consensus among the different disciplines interested in temporal granularity representation has been achieved with the formalization proposed by Bettini et al.

[11], who give a comprehensive dis-cussion on temporal granularities for databases, data mining, and temporal reasoning.Time granularities in databases, data mining, and temporal reasoning.

C Bettini, S Jajodia, S Wang. Springer Science & Business Media, An access control model supporting periodicity constraints and temporal reasoning. E Bertino, C Bettini, E Ferrari, P Samarati. ACM Transactions on Database Systems (TODS) 23 (3),