Yurdaer N. Doganata

Business Provenance --- A Technology to Increase Traceability of End-to-End Operations

Todays enterprise applications span multiple systems and organizations, integrating legacy and newly developed software components to deliver value to business operations. Often business processes rely on human activities that may not be predicted in advance, and information exchange is heavily based on e-mails or attachments where the content is unstructured and needs discovery. Visibility of such end-to-end operations is required to manage compliance and business performance. Hence, it becomes necessary to develop techniques for tracking and correlating the relevant aspects of business operations as needed without the cost and overhead of a fully fledged data and process reengineering. Our business provenance solution provides a generic data model and middleware infrastructure to collect and correlate information about how data was produced, what resources were involved and which tasks were executed. Business provenance gives the flexibility to selectively capture information required to address a specific compliance or performance goal. Additionally, a powerful correlation mechanism yields a representation of the end-to-end operation that puts each business artifact into the right context, for example, to detect situations of compliance violations and find their root causes.

Making a cost-effective video server

A cost-effective system must allocate video files to the right place at the right time. We present the characteristics of different storage media and provide an analytical model for obtaining the cost of storing video files. We then state the video file allocation problem and provide a solution.<<ETX>>

Glossary extraction and utilization in the information search and delivery system for IBM technical support

In this paper we describe the practical aspects of extracting and using a glossary for a selected technical domain. We first describe the existing glossary extraction process, as applied to general corpora, and examine its shortcomings in the technical support domain. Then we propose a number of enhancements to it, including focusing the glossary on a selected domain context, providing support for multidomain glossaries, and importing domain-specific dictionaries. We apply our focused-glossary approach to the IBM Technical Support corpus and incorporate resulting glossaries within the information search and delivery system used by IBM Technical Support. We demonstrate the effectiveness of our approach by evaluating the quality of keywords and terms extracted from sample documents with the help of these glossaries.

A markov prediction model for data-driven semi-structured business processes

In semi-structured case-oriented business processes, the sequence of process steps is determined by case workers based on available document content associated with a case. Transitions between process execution steps are therefore case specific and depend on independent judgment of case workers. In this paper, we propose an instance-specific probabilistic process model (PPM) whose transition probabilities are customized to the semi-structured business process instance it represents. An instance-specific PPM serves as a powerful representation to predict the likelihood of different outcomes. We also show that certain instance-specific PPMs can be transformed into a Markov chain under some non-restrictive assumptions. For instance-specific PPMs that contain parallel execution of tasks, we provide an algorithm to map them to an extended space Markov chain. This way existing Markov techniques can be leveraged to make predictions about the likelihood of executing future tasks. Predictions provided by our technique could generate early alerts for case workers about the likelihood of important or undesired outcomes in an executing case instance. We have implemented and validated our approach on a simulated automobile insurance claims handling semi-structured business process. Results indicate that an instance-specific PPM provides more accurate predictions than other methods such as conditional probability. We also show that as more document data become available, the prediction accuracy of an instance-specific PPM increases.

Large-Scale Distributed Storage System for Business Provenance

In todays complex business environment, applications span across loosely coupled systems generating massive amounts of business artifacts at various levels of granularity. Monitoring and analyzing these artifacts enables access to critical process information to improve the effectiveness of business operations. Tracking, capturing, storing and processing such large volumes of data, however, is difficult and resource intensive with current relational database technologies. Hence, designers are forced to make trade-offs in deciding the type and the granularity level of the data to be captured. Nevertheless, the amount of historical data that carries important insight about the business processes that need to be captured is growing. A solution that is capable of handling massive business provenance data is necessary. In this paper, using cloud as opposed to relational databases to manage this massive amount of business provenance data is proposed and a cloud-based business provenance architecture based on HBase/Hadoop technology is introduced.

Modeling timed user-interactions in multimedia documents

Interactive multimedia documents (or systems) can be characterized by active user participation and the diversity of multimedia information accessed at various levels of granularity. They need to support extensive user participation in selecting and tailoring the information and its presentation. Multimedia information fragments may vary from portions of video, pieces of audio, newspaper quotations or chapters of a book. Effectively managing the creation, evolution and complexity of multimedia documents formed by combining media fragments is an essential capability. We consider the hyperstory model of a multimedia document, where a document is structured hierarchically in three dimensions: time, space and asynchrony. The model provides a layered approach in structuring multimedia documents, thus reducing the complexities of large systems. The hyperstory model supports user interactions that are timed, and also supports preemptive resuming. Timed user interactions with the document are modeled with a newly introduced timed Petri-net (TPN*). TPN* is used to infer the behavior of the system. This paper describes TPN*s modeling and analysis and its application to the hyperstory model.

Multimedia digital conferencing: a web-enabled multimedia teleconferencing system

The convergence of the telecommunication and information technologies brings a real revolution to the communications world and hence in the way that people interact and communicate with each other. With the development of the World Wide Web technology for browsing and navigating through the Internet, complemented by the global telecommunication network, new, easy-to-use tools are being developed to simplify and enhance collaboration among people. In this paper, we describe the MultiMedia Digital Conferencing (MMDC) prototype system, which is a Web-enabled teleconferencing system. The MMDC server allows heterogeneous clients to use the Internet and the telecommunication network in order to establish and participate in data and/or audio conferences through the use of a variety of audio systems and computing platforms.

Effect of Using Automated Auditing Tools on Detecting Compliance Failures in Unmanaged Processes

The effect of using automated auditing tools to detect compliance failures in unmanaged business processes is investigated. In the absence of a process execution engine, compliance of an unmanaged business process is tracked by using an auditing tool developed based on business provenance technology or employing auditors. Since budget constraints limit employing auditors to evaluate all process instances, a methodology is devised to use both expert opinion on a limited set of process instances and the results produced by fallible automated audit machines on all process instances. An improvement factor is defined based on the average number of non-compliant process instances detected and it is shown that the improvement depends on the prevalence of non-compliance in the process as well as the sensitivity and the specificity of the audit machine.

Leveraging path information to generate predictions for parallel business processes

In semi-structured processes, the set of activities that need to be performed, their order and whether additional steps are required are determined by human judgment. There is a growing demand for operational support of such processes during runtime particularly in the form of predictions about the likelihood of future tasks. We address the problem of making predictions for a running instance of a semi-structured process that contains parallel execution paths where the execution path taken by a process instance influences its outcome. In particular, we consider five different models for how to represent an execution trace as a path attribute for training a prediction model. We provide a methodology to determine whether parallel paths are independent, and whether it is worthwhile to model execution paths as independent based on a comparison of the information gain obtained by dependent and independent path representations. We tested our methodology by simulating a marketing campaign as a business process model and selected decision trees as the prediction model. In the evaluation, we compare the complexity and prediction accuracy of a prediction model trained with five different models.

A communication network architecture for transportation information systems

An emerging application of mobile computing and communication is the delivery of information related to the transportation system to drivers and travelers. Such real-time information would be very valuable in providing services such as pre-trip planning, route guidance, intermodal transportation, yellow pages, and ride matching and reservation. This so-called advanced traveler information system (ATIS) is an important subset of an intelligent transportation system (ITS). The authors are developing an ATIS operational field test called SWIFT (Seattle wide-area information for travelers) in the Seattle metropolitan area which uses technological advances in wireless communication, personal digital assistants (PDA), and traffic modeling and analysis. SWIFT uses an advanced 19 kbps FM subcarrier broadcast medium for the delivery of transportation information as well as personal paging information. Preliminary description of the logical and physical architecture of the SWIFT system along with communication loading analysis for this system, are presented.