Agile Workflow Technology for Long-Term Processes

The increasing dynamics of today’s work impacts the business processes. Agile workflow technology is a means for the automation of adaptable processes. However, the modification of workflows is a difficult task that is performed by human experts. This chapter discusses the novel approach of agile workflow technology for dynamic, long-term scenarios and on change reuse. First, it introduces new concepts for a workflow modelling language and enactment service, which enable an interlocked modelling and execution of workflows by means of a sophisticated suspension mechanism. Second, it provides new process-oriented methods of case-based reasoning in order to support the reuse of change experience. The results from an experimental evaluation in a real-world scenario highlight the usefulness and the practical impact of this work.

Mining E-Mail Messages

Increasingly information systems log historic information in a systematic way. Workflow management systems, but also ERP, CRM, SCM, and B2B systems often provide a so-called “event log’’, i.e., a log recording the execution of activities. Thus far, process mining has been mainly focusing on structured event logs resulting in powerful analysis techniques and tools for discovering process, control, data, organizational, and social structures from event logs. Unfortunately, many work processes are not supported by systems providing structured logs. Instead very basic tools such as text editors, spreadsheets, and e-mail are used. This paper explores the application of process mining to e-mail, i.e., unstructured or semi-structured e-mail messages are converted into event logs suitable for application of process mining tools. This paper presents the tool EMailAnalyzer, embedded in the ProM process mining framework, which analyzes and transforms e-mail messages to a format that allows for analysis using our process mining techniques. The main innovative aspect of this work is that, unlike most other work in this area, our analysis is not restricted to social network analysis. Based on e-mail logs we can also discover interaction patterns and processes.

Engineering Software Systems with Social-Driven Templates

Multi-Agent Systems (MAS) architectures are gaining popularity over traditional ones for building open, distributed, and evolving software required by today’s corporate IT applications such as e-business systems, Web services or enterprise knowledge bases. Since the fundamental concepts of multi-agent systems are social and intentional rather than object, functional, or implementation-oriented, the design of MAS architectures can be eased by using social-driven templates. They are detailed agent-oriented design idioms to describe MAS architectures as composed of autonomous agents that interact and coordinate to achieve their intentions, like actors in human organizations. This paper presents social patterns, as well as organizational styles, and focuses on a framework aimed to gain insight into these templates. The framework can be integrated into agent-oriented software engineering methodologies used to build MAS. We consider the Broker social pattern to illustrate the framework. The mapping from system architectural design (through organizational architectural styles), to system detailed design (through social patterns), is overviewed with a data integration case study. The automation of patterns design is also overviewed.

Semantic Supplier Contract Monitoring and Execution DSS Architecture

This research is motivated by the critical problem of stark incompatibility between the contractual clauses (typically buried in legal documents) and the myriad of performance measures used to evaluate and reward (or penalize) supply participants in the extended enterprise. This difference between what is contractually expected and what is actually performed in addition to the lack of transparency of what is measured and how those measures relate to the contractual obligations make it difficult, error prone and confusing for different partner organizations. To address this critical issue, in this article, we present a supplier performance contract monitoring and execution decision support architecture and its prototype implementation using a business case study. We use the SWRL extension of OWL-DL to represent contract conditions and rules as part of the ontology and then use the Jess Rule Reasoner to execute the contract rules integrating with Service Oriented Computing to provide decision support to managers in the extended enterprise.

A QoS Aware, Cognitive Parameters Based Model for the Selection of Semantic Web Services

Semantic Web service selection is considered as the one of the most important aspects of semantic web service composition process. The Quality of Service (QoS) and cognitive parameters can be a good basis for this selection process. In this paper, we have presented a hybrid selection model for the selection of Semantic Web services based on their QoS and cognitive parameters. The presented model provides a new approach of measuring the QoS parameters in an accurate way and provides a completely novel and formalized measurement of different cognitive parameters.

Supporting Structured Group Decision Making through System-Directed User Guidance

This article addresses an area which holds considerable promise for enhancing the effective utilization of advanced information technologies: the feasibility of using system-directed multi-modal user support for facilitating users of advanced information technologies. An application for automating the information technology facilitation process is used to compare group decision-making effectiveness of human-facilitated groups with groups using virtual facilitation in an experiment employing auditors, accountants, and IT security professionals as participants. The results of the experiment are presented and possible avenues for future research studies are suggested.

Information Customization using SOMSE

Information overload on the World-Wide Web is a well recognized problem. Research to subdue this problem and extract maximum benefit from the Internet is still in its infancy. Managing information overload on the Web is a challenge and the need for more precise techniques for assisting the user in finding the most relevant and most useful information is obvious. Search engines are very effective at filtering pages that match explicit queries. Search engines, however, require massive memory resources (to store an index of the Web) and tremendous network bandwidth (to create and continually refresh the index). These systems receive millions of queries per day, and as a result, the CPU cycles devoted to satisfying each individual query are sharply curtailed. There is no time for intelligence which is mandatory for offering ways to combat information overload. What is needed are systems, often referred to as information customization systems, that act on the user’s behalf and that can rely on existing information services like search engines that do the resource-intensive part of the work. These systems will be sufficiently lightweight to run on an average PC and serve as personal assistants. Since such an assistant has relatively modest resource requirements it can reside on an individual user’s machine. If the assistant resides on the user’s machine, there is no need to turn down intelligence. The system can have substantial local intelligence. In an attempt to circumvent the problems of search engines and contribute to resolving the problem of information overload over the Web, the authors propose SOMSE, a system that improves the quality of Web search by combining meta-search and unsupervised learning.

A New Approach for Building a Scalable and Adaptive Vertical Search Engine

Search engines are the most important search tools for finding useful and recent information on the Web today. They rely on crawlers that continually crawl the Web for new pages. Meanwhile, focused crawlers have become an attractive area for research in recent years. They suggest a better solution for general-purpose search engine limitations and lead to a new generation of search engines called vertical-search engines. Searching the Web vertically is to divide the Web into smaller regions; each region is related to a specific domain. In addition, one crawler is allowed to search in each domain. The innovation of this article is adding intelligence and adaptation ability to focused crawlers. Such added features will certainly guide the crawler perfectly to retrieve more relevant pages while crawling the Web. The proposed crawler has the ability to estimate the rank of the page before visiting it and adapts itself to any changes in its domain using.

Agent-Based Semantic Interoperability of Geo-Services

This chapter proposes a multi-agent based framework that allows multiple data sources and models to be semantically integrated for spatial modeling in business processing. The authros introduce a multiagent system (OSIRIS – Ontology-based Spatial Information and Resource Integration Services) to semantically interoperate complex spatial services and integrate them in a meaningful composition. The advantage of using multi-agent collaboration in OSIRIS is that it obviates the need for end-user analysts to be able to decompose a problem domain to subproblems or to map different models according to what they actually mean. The authors also illustrate a multi-agent interaction scenario for collaborative modeling of spatial applications using the proposed custom feature of OSIRIS using Description Logics. The system illustrates an application of domain ontology of urban environmental hydrology and evaluation of decision maker’s consequences of land use changes. In e-government context, the proposed OSIRIS framework works as semantic layer for one stop geospatial portal.

An Agent-Based Approach to Process Management in E-Learning Environments

Learning is a process to acquire new knowledge. Ideally, this process is the result of an active interaction of key cognitive processes, such as perception, imagery, organization, and elaboration. Quality learning has emphasized on designing a course curriculum or learning process, which can elicit the cognitive processing of learners. However, most e-learning systems nowadays are resources-oriented instead of process-oriented. These systems were designed without adequate support of pedagogical principles to guide the learning process. They have not explained the sequence of how the knowledge was acquired, which, in fact, is extremely important to the quality of learning. This study aims to develop an e-learning environment that enables students to get engaged in their learning process by guiding and customizing their learning process in an adaptive way. The expected performance of the Agent-based e-learning Process model is also evaluated by comparing with traditional e-learning models.