An Edit-Distance Model for the Approximate Matching of Timed Strings

Dobrišek, Simon; Žibert, Janez; Pavešić, Nikola; Mihelic, F.

doi:10.1109/tpami.2008.197

Cited by 11 publications

(8 citation statements)

References 12 publications

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“…There is an abundant literature about distances. For distances between sequences, an edit distance model is used in [22] to approximate matching of timed strings; [23], [24] propose to represent each sequence in a suitable form, before computing distance. However, very few distances take into account the temporal aspect.…”

Section: Discussionmentioning

confidence: 99%

Distance-Based Trace Diagnosis for Multimedia Applications: Help Me TED!

Kengne

Ibrahim

Rousset

et al. 2013

2013 IEEE Seventh International Conference on Semantic Computing

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Execution traces have become essential resources that many developers analyze to debug their applications. Ideally, a developer wants to quickly detect whether there are anomalies on his application or not. However, in practice, size of multimedia applications trace can reach gigabytes, which makes their exploitation very complex. Usually, developers use visualization tools before stating a hypothesis. In this paper, we argue that this solution is not satisfactory and propose to automatically provide a diagnosis by comparing execution traces. We use distance based models and conduct a user case to show how TED, our automatic trace diagnosis tool, provides semantic added-value information to the developer. Performance evaluation over real world data shows that our approach is scalable. Index Terms-Execution traces; Diagnosis; Audio/Video decoding; Multimedia applications.

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Section: Discussionmentioning

confidence: 99%

Distance-Based Trace Diagnosis for Multimedia Applications: Help Me TED!

Kengne

Ibrahim

Rousset

et al. 2013

2013 IEEE Seventh International Conference on Semantic Computing

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“…In addition to these metrics we adapted the model proposed in [21,22] for measuring timed strings to the business process domain. In this article we present an extension for the strings distance metrics for sequences composed of symbols available solely in defined time intervals.…”

Section: Assessment and Optimizationmentioning

confidence: 99%

Automated discovery of business process simulation models from event logs

Camargo

Dumas

González-Rojas

2020

Decision Support Systems

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Simulation is a versatile technique for quantitative analysis of business processes. It allows analysts to estimate the performance of a process under multiple scenarios. However, the discovery, validation, and tuning of business process simulation models is cumbersome and error-prone. It requires manual iterative refinement of the process model and simulation parameters in order to match the observed reality as closely as possible. Modern information systems store detailed execution logs of the business processes they support. Previous work has shown that these logs can be used to discover simulation models. However, existing methods for log-based discovery of simulation models do not seek to optimize the accuracy of the resulting models. Instead they leave it to the user to manually tune the simulation model to achieve the desired level of accuracy. This article presents an accuracy optimized method to discover business process simulation models from execution logs. The method decomposes the problem into a series of steps with associated configuration parameters. A hyper-parameter optimization method is then used to search through the space of possible configurations so as to maximize the similarity between the behavior of the simulation model and the behavior observed in the log. The method has been implemented as a tool and evaluated using logs from different domains.

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“…A few projects were also developed in parallel with the work in this paper. Timed String Edit Distance (Dobrisek et al, 2009) inserted timed null symbols into event sequences before matching. It allowed matching between events with different event types and measured two types of difference: time difference and event type difference (symbol dissimilarity).…”

Section: Background and Related Workmentioning

confidence: 99%

Querying event sequences by exact match or similarity search: Design and empirical evaluation

Wongsuphasawat

Plaisant

Taieb-Maimon

et al. 2012

Interacting with Computers

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Specifying event sequence queries is challenging even for skilled computer professionals familiar with SQL. Most graphical user interfaces for database search use an exact match approach, which is often effective, but near misses may also be of interest. We describe a new similarity search interface, in which users specify a query by simply placing events on a blank timeline and retrieve a similarity-ranked list of results. Behind this user interface is a new similarity measure for event sequences which the users can customize by four decision criteria, enabling them to adjust the impact of missing, extra, or swapped events or the impact of time shifts. We describe a use case with Electronic Health Records based on our ongoing collaboration with hospital physicians. A controlled experiment with 18 participants compared exact match and similarity search interfaces. We report on the advantages and disadvantages of each interface and suggest a hybrid interface combining the best of both.

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An Edit-Distance Model for the Approximate Matching of Timed Strings

Cited by 11 publications

References 12 publications

Distance-Based Trace Diagnosis for Multimedia Applications: Help Me TED!

Distance-Based Trace Diagnosis for Multimedia Applications: Help Me TED!

Automated discovery of business process simulation models from event logs

Querying event sequences by exact match or similarity search: Design and empirical evaluation

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