Jagadeesh Chandra Bose R.P.

Jagadeesh Chandra Bose R.P.
Eindhoven University of Technology | TUE · Department of Mathematics and Computer Science

PhD

About

53
Publications
36,440
Reads
How we measure 'reads'
A 'read' is counted each time someone views a publication summary (such as the title, abstract, and list of authors), clicks on a figure, or views or downloads the full-text. Learn more
3,093
Citations

Publications

Publications (53)
Conference Paper
Full-text available
There has been a considerable shift in the way how software is built and delivered today. Most deployed software systems in modern times are created by (autonomous) distributed teams in heterogenous environments making use of many artifacts, such as externally developed libraries, drawn from a variety of disparate sources. Stakeholders such as deve...
Preprint
Full-text available
Training and practice play a key role in a medical students' attainment of surgical procedural skills. It is beyond doubt that good skills correlate with better clinical outcomes and improved healthcare. Timely, holistic, and effective feedback provide a significant impetus to students acquiring skills with precision. In this paper, we analyze the...
Conference Paper
We have recently witnessed tremendous success of Machine Learning (ML) in practical applications. Computer vision, speech recognition and language translation have all seen a near human level performance. We expect, in the near future, most business applications will have some form of ML. However, testing such applications is extremely challenging...
Conference Paper
Full-text available
Business processes often exhibit a high degree of variability. Process variants may manifest due to the differences in the nature of clients, heterogeneity in the type of cases, etc. Through the use of process mining techniques, one can benefit from historical event data to extract non-trivial knowledge for improving business process performance. A...
Conference Paper
Full-text available
Service delivery organizations cater similar processes across several clients. Process variants may manifest due to the differences in the nature of clients, heterogeneity in the type of cases, etc. The organization’s operational Key Performance Indices (KPIs) across these variants may vary, e.g., KPIs for some variants may be better than others. T...
Conference Paper
Business processes often incorporate stochastic decision points, either due to uncontrollable actions or because the control flow is not fully specified. Formal modeling of such business processes with resource constraints and multiple instances is hard because of the interplay among stochastic behavior, concurrency, real-time and resource contenti...
Article
Full-text available
Companies are increasingly embedded in B2B environments, where they have to collaborate in order to achieve their goals. Such collaborations lead to inter-organizational business processes that may be commonly supported through the exchange of electronic data interchange (EDI) messages (e.g., electronic purchase orders, invoices etc.). Despite the...
Conference Paper
Service delivery organizations are constantly under pressure to meet service level agreements (SLAs), operate under tight costs, utilize their resources well and to improve the operational performance. A well-planned task allocation plays an important role in meeting these objectives. This work considers the problem of efficient task allocation to...
Conference Paper
Full-text available
Services organizations are always under pressure to operate under tight costs and to improve their operational efficiency. Transaction processing is one of the major operations in a services organization. An organization is typically trained to serve a standard set of processes within different domains across several clients. Although each client h...
Conference Paper
Full-text available
In recent years process mining techniques have matured. Provided that the process is stable and enough example traces have been recorded in the event log, it is possible to discover a high-quality process model that can be used for performance analysis, compliance checking, and prediction. Unfortunately, most processes are not in steady-state and p...
Article
Full-text available
Although most business processes change over time, contemporary process mining techniques tend to analyze these processes as if they are in a steady state. Processes may change suddenly or gradually. The drift may be periodic (e.g., because of seasonal influences) or one-of-a-kind (e.g., the effects of new legislation). For the process management,...
Conference Paper
In order to achieve their goals, organizations collaborate with business partners. Such collaborations represent enactments of inter-organizational business processes and may be supported through the exchange of Electronic Data Interchange (EDI) messages (e.g., electronic purchase orders, invoices etc.). For gaining insights on such processes, rece...
Article
Background Trauma resuscitations without pre-arrival notification are often initially chaotic, potentially compromising patient care. We hypothesized that trauma resuscitations without pre-arrival notification are performed with more variable adherence to Advanced Trauma Life Support (ATLS) protocol and that implementation of a checklist would impr...
Conference Paper
Traditionally, most process mining techniques aim at dis-covering procedural process models (e.g., Petri nets, BPMN, and EPCs) from event data. However, the variability present in less-structured flex-ible processes complicates the discovery of such procedural models. The "open world" assumption used by declarative models makes it easier to handle...
Conference Paper
Process mining techniques can be used to discover process models from event data. Often the resulting models are complex due to the variability of the underlying process. Therefore, we aim at discovering declarative process models that can deal with such variability. However, for real-life event logs involving dozens of activities and hundreds or t...
Conference Paper
Full-text available
More and more information about processes is recorded in the form of so-called “event logs”. High-tech systems such as X-ray machines and high-end copiers provide their manufacturers and services organizations with detailed event data. Larger organizations record relevant business events for process improvement, auditing, and fraud detection. Trace...
Conference Paper
Full-text available
The growing interest in process mining is fueled by the increasing availability of event data. Process mining techniques use event logs to automatically discover process models, check conformance, identify bottlenecks and deviations, suggest improvements, and predict processing times. Lion's share of process mining research has been devoted to anal...
Conference Paper
Full-text available
A real-life event log, taken from a Dutch financial institute, is analyzed using state-of-the-art process mining techniques. The log contains events related to loan/overdraft applications of customers. We propose a hierarchical decomposition of the log into homogenous subsets of cases based on characteristics such as the final decision, offer, and...
Conference Paper
Process mining techniques often reveal that real-life processes are more variable than anticipated. Although declarative process models are more suitable for less structured processes, most discovery techniques generate conventional procedural models. In this paper, we focus on discovering Declare models based on event logs. A Declare model is comp...
Article
Full-text available
Business processes leave trails in a variety of data sources (e.g., audit trails, databases, and transaction logs). Hence, every process instance can be described by a trace, i.e., a sequence of events. Process mining techniques are able to extract knowledge from such traces and provide a welcome extension to the repertoire of business process anal...
Conference Paper
Full-text available
Process mining techniques are able to extract knowledge from event logs commonly available in today’s information systems. These techniques provide new means to discover, monitor, and improve processes in a variety of application domains. There are two main drivers for the growing interest in process mining. On the one hand, more and more events ar...
Conference Paper
Full-text available
A real-life event log, taken from a Dutch Academic Hospital, provided for the BPI challenge is analyzed using process mining techniques. The log contains events related to treatment and diagnosis steps for patients diagnosed with cancer. Given the heterogeneous nature of these cases, we first demonstrate that it is possible to create more homogeneo...
Conference Paper
Full-text available
Process mining techniques are able to extract knowledge from event logs commonly available in today’s information systems. These techniques provide new means to discover, monitor, and improve processes in a variety of application domains. There are two main drivers for the growing interest in process mining. On the one hand, more and more events ar...
Conference Paper
Full-text available
Operational processes need to change to adapt to changing circumstances, e.g., new legislation, extreme variations in supply and demand, seasonal effects, etc. While the topic of flexibility is well-researched in the BPM domain, contemporary process mining approaches assume the process to be in steady state. When discovering a process model from ev...
Conference Paper
Full-text available
Process models can be seen as “maps ” describing the operational processes of organizations. Traditional process discovery algorithms have problems dealing with fine-grained event logs and lessstructured processes. The discovered models (i.e., “maps”) are spaghettilike and are difficult to comprehend or even misleading. One of the reasons for this...
Conference Paper
Full-text available
Process mining techniques can be used to extract non-trivial process related knowledge and thus generate interesting insights from event logs. Similarly, bioinformatics aims at increasing the understand- ing of biological processes through the analysis of information associated with biological molecules. Techniques developed in both disciplines can...
Conference Paper
Full-text available
Process mining techniques attempt to extract non-trivial knowledge and interesting insights from event logs. Process mining provides a welcome extension of the repertoire of business process analysis techniques and has been adopted in various commercial BPM systems (BPM∣one, Futura Reflect, ARIS PPM, Fujitsu, etc.). Unfortunately, traditional proce...
Conference Paper
Process mining techniques attempt to extract non-trivial knowledge and interesting insights from event logs. Process models can be seen as the "maps" describing the operational processes of organizations. Unfortunately, traditional process discovery algorithms have problems dealing with less-structured processes. Furthermore, existing discovery alg...
Conference Paper
Full-text available
Process mining refers to the extraction of process models from event logs. Real-life processes tend to be less structured and more flexible. Traditional process mining algorithms have problems dealing with such unstructured processes and generate spaghetti-like process models that are hard to comprehend. One reason for such a result can be attribut...
Conference Paper
Full-text available
Process mining refers to the extraction of process models from event logs. Real-life processes tend to be less structured and more flexible. Traditional process mining algorithms have problems dealing with such unstructured processes and generate "spaghetti-like" process models that are hard to comprehend. An approach to overcome this is to cluster...
Conference Paper
Automatic identification of software faults has enormous practical significance. This requires characterizing program execution behavior. Equally important is the aspect of diagnosing (finding root-cause of) faults encountered. In this article, we address the problem of identifying the root cause of failure from the test sequences that caused failu...
Article
An adaptive algorithm for function minimization based on conjugate gradients for the problem of finding linear discriminant functions in pattern classification is developed. The algorithm converges to a solution in both consistent and inconsistent cases in a finite number of steps on several datasets. We have applied our algorithm and compared its...
Conference Paper
Microsoft Windows uses the notion of registry to store all configuration information. The registry entries have associations and dependencies. For example, the paths to executables may be relative to some home directories. The registry being designed with faster access as one of the objectives does not explicitly capture these relations. In this pa...
Conference Paper
Automatic identification of software faults has enormous practical significance. This requires characterizing program execution behavior and the use of appropriate data mining techniques on the chosen representation. In this paper we use the sequence of system calls to characterize program execution. The data mining tasks addressed are learning to...
Conference Paper
Hybrid models combining the analytical (rule-based) and connectionist (artificial neural network (ANN)) paradigms are called knowledge based neural networks (KBNN). The knowledge based artificial neural network (KBANN) is one such model that makes use of the domain theory represented as propositional rules and training examples. In this article, we...

Network

Cited By