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Event queries on correlated probabilistic streams

Christopher Ré, Julie Letchner, Magdalena Balazinksa, Dan Suciu
2008 Proceedings of the 2008 ACM SIGMOD international conference on Management of data - SIGMOD '08  
Inference on these models creates streams of probabilistic events which cannot be directly queried by existing systems.  ...  To address this challenge we propose Lahar 1 , an event processing system for probabilistic event streams.  ...  In this paper we propose instead to process complex event queries on correlated, probabilistic streams.  ... 
doi:10.1145/1376616.1376688 dblp:conf/sigmod/ReLBS08 fatcat:uqk5teqtvjea5pafkpomnj7wum

Challenges for Event Queries over Markovian Streams

Julie Letchner, Christopher Ré, Magdalena Balazinska, Matthai Philipose
2008 IEEE Internet Computing  
The authors propose a novel model-based view, the Markovian stream, to represent correlated probabilistic sequences.  ...  Applications interested in evaluating event queries -extracting sophisticated state sequences -can improve robustness by querying a Markovian stream view instead of querying raw data directly.  ...  Processing Regular Event Queries Processing event-style queries on deterministic streams is straightforward using the NFA machinery just described.  ... 
doi:10.1109/mic.2008.118 fatcat:nxrl57g6gvdolpd6j42maxnlyu

Access Methods for Markovian Streams

Julie Letchner, Christopher Re, Magdalena Balazinska, Matthai Philipose
2009 Proceedings / International Conference on Data Engineering  
Probabilistic databases [3], [8], [20], [42], on the other hand, handle data uncertainty but do not support event queries and many do not handle correlations [3], [8], [42].  ...  Because of the probabilities and correlations present in a Markovian stream, archived event queries on these streams cannot be handled by any existing system.  ...  over a naïve stream scan on fixed-length queries, even while preserving the probabilistic, correlated relationships within Markovian streams.  ... 
doi:10.1109/icde.2009.21 dblp:conf/icde/LetchnerRBP09 fatcat:nuca2kqiyre7bmo6vp2tpwahse

Systems aspects of probabilistic data management

Magdalena Balazinska, Christopher Ré, Dan Suciu
2008 Proceedings of the VLDB Endowment  
Break (30 minutes) Part III: Processing Probabilistic Events (25 minutes) • Motivation for and definition of events, event queries, and their semantics on probabilistic data. • Online event query processing  ...  In the second half of the tutorial, we will discuss more advanced issues, such as event processing over probabilistic streams, and views over probabilistic data.  ... 
doi:10.14778/1454159.1454219 fatcat:2ngejlxgfbh5jnntqejllrddpy

Probabilistic Timing Join over Uncertain Event Streams

Aloysius K. Mok, Honguk Woo, Chan-Gun Lee
2006 12th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications (RTCSA'06)  
We describe a stream-partitioning technique for checking the satisfaction of a probabilistic timing constraint upon event arrivals in a systematic way in order to delimit the "probing range" in event streams  ...  This paper addresses the problem of processing eventtiming queries over event streams where the uncertainty in the values of the timestamps is characterizable by histograms.  ...  at which the events are detected from processing the data streams. This mode of query processing is said to be by detection semantics.  ... 
doi:10.1109/rtcsa.2006.52 dblp:conf/rtcsa/MokWL06 fatcat:vrqhiz6k5zcwja5i44uoo3zj7e

Multiple Regular Expression Pattern Monitoring over Probabilistic Event Streams

2020 IEICE transactions on information and systems  
One of the applications of probabilistic event streams is monitoring of time series events based on regular expressions.  ...  by using a regular expression, and then check whether corresponding events occur in a probabilistic event stream with a sliding window.  ...  Finally, we define pattern monitoring queries with a sliding window. Probabilistic Event Streams First, we define a probabilistic event as a component of a probabilistic event stream.  ... 
doi:10.1587/transinf.2019dap0009 fatcat:bibouzpembdkffgq6tj5ier5v4

Probabilistic Fuzzy Logic based Stock Price Prediction

V. Govindasamy, P. Thambidurai
2013 International Journal of Computer Applications  
This approach triggers an appropriate output event to notify the opportunities to buy and to sell share in real-time based on event patterns of price movements.  ...  In a real-time application scenario, the proposed Probabilistic Fuzzy Logic (PFL) approach can be implemented in various applications such as health care, stock trading, click stream analysis, retail and  ...  Publishers publish the continuously arriving stock exchange stream as follows Stock Request The stockbrokers or traders will like to start a query on the event stream as a Stock Request similar to the  ... 
doi:10.5120/12356-8669 fatcat:w2jtjlb7nnellgqdk5z4h5d6ye

Foundations of probabilistic answers to queries

Dan Suciu, Nilesh Dalvi
2005 Proceedings of the 2005 ACM SIGMOD international conference on Management of data - SIGMOD '05  
probabilisticQuery processing still in infancy 38 4.  ...  Data Balazinska UW WA Data streams Balazinska MIT MA Data streams Miklau Umass MA Data security Key (?!?)  ...  Brute force: X 1 X 2 X 3 E Pr Random Graphs [Erdos&Reny:1959 ,Fagin:1976 ,Spencer:2001 Domain: Boolean query Q What is lim n!  ... 
doi:10.1145/1066157.1066303 dblp:conf/sigmod/SuciuD05 fatcat:svwpawnpqff3blzatan3aadr6a

Efficient Similarity Search over Future Stream Time Series

Xiang Lian, Lei Chen
2008 IEEE Transactions on Knowledge and Data Engineering  
queries based on the predicted data.  ...  Especially, in the cases where data often arrive periodically for various reasons (for example, the communication congestion or batch processing), queries on such incomplete time series or even future  ...  Last but not least, we further extend the probabilistic approach to the group probabilistic approach by utilizing the correlations among stream time series.  ... 
doi:10.1109/tkde.2007.190666 fatcat:nv3alfjdafentd6bouz2a7azg4

Approximation trade-offs in Markovian stream processing: An empirical study

Julie Letchner, Christopher Re, Magdalena Balazinska, Matthai Philipose
2010 2010 IEEE 26th International Conference on Data Engineering (ICDE 2010)  
The rich semantics and large volumes of these streams make them difficult to query efficiently.  ...  In this paper, we study the effects-on both efficiency and accuracy-of two common stream approximations.  ...  (b1) Event query output (unaggregated) on a real-world Markovian stream. (b2) Output of a countbased aggregation of the event query shown in (b1).  ... 
doi:10.1109/icde.2010.5447926 dblp:conf/icde/LetchnerRBP10 fatcat:wcvxsd5fxfhwlm4hd5ihekec6i

Distribution and Uncertainty in Complex Event Recognition [chapter]

Alexander Artikis, Matthias Weidlich
2015 Lecture Notes in Computer Science  
In this paper, we reflect on some of these application areas to outline open research problems in event recognition.  ...  In particular, we focus on the questions of (1) how to distribute event recognition and (2) how to deal with the inherent uncertainty observed in many event recognition scenarios.  ...  For instance, the Lahar system [28] , which is based on Cayuga, has an inference mechanism for answering queries over probabilistic data streams, that is, streams whose events are tagged with a probability  ... 
doi:10.1007/978-3-319-21542-6_5 fatcat:uk7ysbbk4jc3lgucakobhbzh2q

Continuously monitoring top-k uncertain data streams: a probabilistic threshold method

Ming Hua, Jian Pei
2009 Distributed and parallel databases  
Although a significant amount of previous research explores various continuous queries on data streams, continuous queries on uncertain data streams have seldom been investigated.  ...  In this paper, we formulate a novel and challenging problem of continuously monitoring top-k uncertain data streams, and propose a probabilistic threshold method.  ...  Continuous queries on probabilistic streams To the best of our knowledge, [11, 34, 35, 37] are the only existing studies on continuous queries on probabilistic data streams, which are highly related  ... 
doi:10.1007/s10619-009-7043-x fatcat:ti4uiuns7rgrjensmqgoypmvsi

Online Filtering, Smoothing and Probabilistic Modeling of Streaming data

Bhargav Kanagal, Amol Deshpande
2008 2008 IEEE 24th International Conference on Data Engineering  
We develop novel techniques to convert the queries on the model-based view directly into queries over particle tables, enabling highly efficient query processing.  ...  We support declarative querying over such views using an extended version of SQL that allows for querying probabilistic data.  ...  events (subject to privacy policies) directly in a streaming fashion, so they can provide user services.  ... 
doi:10.1109/icde.2008.4497525 dblp:conf/icde/KanagalD08 fatcat:rolsuoxpdreldfcqhn6lj626vm

Capturing Data Uncertainty in High-Volume Stream Processing [article]

Yanlei Diao, Boduo Li (University of Massachusetts Amherst), Anna Liu, Liping Peng (UMass Amherst), Charles Sutton, Michael Zink
2009 arXiv   pre-print
Since such raw streams can be highly noisy and may not carry sufficient information for query processing, our system employs probabilistic models of the data generation process and stream-speed inference  ...  To efficiently quantify result uncertainty of a query operator, we explore a variety of techniques based on probability and statistical theory to compute the result distribution at stream speed.  ...  There has been a recent surge of research on probabilistic databases [1, 3, 4, 9, 12, 38, 60, 62] and probabilistic stream processing [11, 31] .  ... 
arXiv:0909.1777v1 fatcat:mkknxviaybasxntbofxxdjcgwa

Lahar demonstration

Julie Letchner, Christopher Ré, Magdalena Balazinska, Matthai Philipose
2009 Proceedings of the VLDB Endowment  
Lahar is a warehousing system for Markovian streams-a common class of uncertain data streams produced via inference on probabilistic models.  ...  Lahar supports OLAP-style queries on Markovian stream archives by leveraging novel approximation and indexing techniques that efficiently manipulate stream probabilities.  ...  The effect on result quality depends on the strength of correlations in the data as well as on the event pattern length. • MAP compression determinizes a Markovian stream into the single most likely (maximum  ... 
doi:10.14778/1687553.1687605 fatcat:fvitfmipfveqpc7tcjvip7yeoy
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