Topic
Transaction time
About: Transaction time is a research topic. Over the lifetime, 607 publications have been published within this topic receiving 14392 citations.
Papers published on a yearly basis
Papers
IBM1
TL;DR: Three algorithms are presented to solve the problem of mining sequential patterns over databases of customer transactions, and empirically evaluating their performance using synthetic data shows that two of them have comparable performance.
Abstract: We are given a large database of customer transactions, where each transaction consists of customer-id, transaction time, and the items bought in the transaction. We introduce the problem of mining sequential patterns over such databases. We present three algorithms to solve this problem, and empirically evaluate their performance using synthetic data. Two of the proposed algorithms, AprioriSome and AprioriAll, have comparable performance, albeit AprioriSome performs a little better when the minimum number of customers that must support a sequential pattern is low. Scale-up experiments show that both AprioriSome and AprioriAll scale linearly with the number of customer transactions. They also have excellent scale-up properties with respect to the number of transactions per customer and the number of items in a transaction. >
6,001 citations
Aalborg University1, James Cook University2, University of Texas at Arlington3, Iowa State University4, University of Bologna5, University of Illinois at Urbana–Champaign6, George Mason University7, Mercedes-Benz8, Microsoft9, Agricultural University of Athens10, University of Udine11, Concordia University12, Polytechnic University of Milan13, University of South Australia14, Indian Institutes of Technology15, University of California16, University of Arizona17, University of South Florida18, City University of New York19, Stanford University20
TL;DR: This document1 contains definitions of a wide range of concepts specific to and widely used within temporal databases, as well as discussions of the adopted names.
Abstract: This document1 contains definitions of a wide range of concepts specific to and widely used within temporal databases. In addition to providing definitions, the document also includes explanations of concepts as well as discussions of the adopted names.
300 citations
10 Oct 2013
TL;DR: This paper independently investigate the performance of some NoSQL and SQL databases in the light of key-value stores, and shows that not all NoSQL databases perform better than SQL databases.
Abstract: With the current emphasis on “Big Data”, NoSQL databases have surged in popularity. These databases are claimed to perform better than SQL databases. In this paper we aim to independently investigate the performance of some NoSQL and SQL databases in the light of key-value stores. We compare read, write, delete, and instantiate operations on key-value stores implemented by NoSQL and SQL databases. Besides, we also investigate an additional operation: iterating through all keys. An abstract key-value pair framework supporting these basic operations is designed and implemented using all the databases tested. Experimental results measure the timing of these operations and we summarize our findings of how the databases stack up against each other. Our results show that not all NoSQL databases perform better than SQL databases. Some are much worse. And for each database, the performance varies with each operation. Some are slow to instantiate, but fast to read, write, and delete. Others are fast to instantiate but slow on the other operations. And there is little correlation between performance and the data model each database uses.
298 citations
Book•
13 May 1998
TL;DR: An object-oriented framework for temporal data models for supporting interoperability among temporal databases and a glossary of time granularity concepts for temporal database concepts.
Abstract: An object-oriented framework for temporal data models.- An architecture for supporting interoperability among temporal databases.- Extended update functionality in temporal databases.- On transaction management in temporal databases.- Implementation options for time-series data.- Expressive power of temporal relational query languages and temporal completeness.- Transitioning temporal support in TSQL2 to SQL3.- Valid time and transaction time proposals: Language design aspects.- Point-based temporal extensions of SQL and their efficient implementation.- Applicability of temporal data models to query multilevel security databases: A case study.- An architecture and construction of a business event manager.- Discovering unexpected patterns in temporal data using temporal logic.- Querying the uncertain position of moving objects.- Temporal database bibliography update.- The consensus glossary of temporal database concepts - February 1998 version.- A glossary of time granularity concepts.
281 citations
Patent•
16 Nov 1994
TL;DR: In this article, a system for providing security on an interactive television system (see the figure), two sets of interactive data, with time stamps (22, 26) are separately sent to a remote location (28, 32, 34).
Abstract: A system for providing security on an interactive television system (see the figure). Two sets of interactive data, with time stamps (22), are separately sent (24, 26) to a remote location (28, 32, 34). At the remote location (28, 32, 34), the time stamps are checked against a remote clock, a time difference being noted for both sets of data. The two differences are compared to determine if one set of data has been delayed as compared to the other. Non-delayed data can be used to update a game score for an interactive game. After the game is completed, the remote clock is compared with a central clock. The difference between the two clocks is compared to the time difference for non-delayed data to determine whether the entire aggregate of interactive data was delayed.
220 citations
Related Topics (5)
Performance Metrics
| Year | Papers |
|---|---|
| 2021 | 8 |
| 2020 | 23 |
| 2019 | 40 |
| 2018 | 39 |
| 2017 | 31 |
| 2016 | 24 |