Christopher Klinkmüller

Increasing recall of process model matching by improved activity label matching

Comparing process models and matching similar activities has recently emerged as a research area of business process management. However, the problem is fundamentally hard when considering realistic scenarios: e.g., there is a huge variety of terms and various options for the grammatical structure of activity labels exist. While prior research has established important conceptual foundations, recall values have been fairly low (around 0.26) --- arguably too low to be useful in practice. In this paper, we present techniques for activity label matching which improve current results (recall of 0.44, without sacrificing precision). Furthermore, we identify categories of matching challenges to guide future research.

Report : The Process Model Matching Contest 2013

Process model matching refers to the creation of correspondences between activities of process models. Applications of process model matching are manifold, reaching from model validation over harmonization of process variants to effective management of process model collections. Recently, this demand led to the development of different techniques for process model matching. Yet, these techniques are heuristics and, thus, their results are inherently uncertain and need to be evaluated on a common basis. Currently, however, the BPM community lacks established data sets and frameworks for evaluation. The Process Model Matching Contest 2013 aimed at addressing the need for effective evaluation by defining process model matching problems over published data sets.

Listen to me: Improving process model matching through user feedback

Many use cases in business process management rely on the identification of correspondences between process models. However, the sparse information in process models makes matching a fundamentally hard problem. Consequently, existing approaches yield a matching quality which is too low to be useful in practice. Therefore, we investigate incorporating user feedback to improve matching quality. To this end, we examine which information is suitable for feedback analysis. On this basis, we design an approach that performs matching in an iterative, mixed-initiative approach: we determine correspondences between two models automatically, let the user correct them, and analyze this input to adapt the matching algorithm. Then, we continue with matching the next two models, and so forth. This approach improves the matching quality, as showcased by a comparative evaluation. From this study, we also derive strategies on how to maximize the quality while limiting the additional effort required from the user.

Towards an Integrated Simulation Approach for Planning Logistics Service Systems

The planning of complex logistics service systems is increasingly characterized as a collaborative process with various participants involved. The planning process of a logistics service system can be rendered by a Fourth Party Logistics Service Provider (4PL) together with an existing network of logistics partners. Simulation can be used to improve the decision-making process in the planning phase and to detect errors that can become cost intensive in the future. This paper outlines how simulation is integrated into a planning approach for a 4PL. The focus is on the derivation of goals and requirements from the specific characteristics of a 4PL. Based on these goals and requirements an initial integrated planning and simulation procedure is presented.

The Logistics Service Engineering and Management Platform: Features, Architecture, Implementation

The logistics service sector is faced with a growing complexity which needs to be handled by cooperating logistics providers aligning their services in a network. This paper introduces the Logistics Service Engineering and Management platform supporting the Fourth Party Logistics Provider business model that aims at establishing a coordinator of such a network. Hence the idea to employ the service oriented design paradigm at the software and at the business level along with the main features of the platform is presented. Furthermore the basic architecture is explained and a closer look at some implementation details is presented.

Activity Matching with Human Intelligence

Effective matching of activities is the first step toward successful process model matching and search. The problem is nontrivial and has led to a variety of computational similarity metrics and matching approaches, however all still with low performance in terms of precision and recall. In this paper, instead, we study how to leverage on human intelligence to identify matches among activities and show that the problem is not as straightforward as most computational approaches assume. We access human intelligence (i) by crowdsourcing the activity matching problem to generic workers and (ii) by eliciting ground truth matches from experts. The precision and recall we achieve and the qualitative analysis of the results testify huge potential for a human-based activity matching that contemplates disagreement and interpretation.

Visualising Business Capabilities in the Context of Business Analysis

Business capabilities represent potentials of an organisation to reach a specific goal or outcome. Business capabilities abstract from processes, resources and people that are required to provide the potential and are connected with a role model of provider and customer, both, internally and externally to an organisation. While related work provides fundamental concepts and usage descriptions of the business capability approach, so far the aspect of visualisation of business capabilities in the context of business analysis was only rudimentary addressed. In this paper, a three-dimensional business capability visualisation metaphor for business analyses is outlined which supports the visualisation of business capabilities and their qualifying dimensions but also the representation of their complex multi-dimensional interrelations.

Analyzing control flow information to improve the effectiveness of process model matching techniques

Abstract Process model matchers automatically identify activities that represent similar functionality in different process models. As such, they support various tasks in business process management including model collection management and process design. Yet, comparative evaluations revealed that state-of-the-art matchers fall short of offering high performance across varied datasets. To facilitate the development of more effective matchers, we systematically study, if and how the analysis of control flow information in process models can contribute to the matching process. In particular, we empirically examine the validity of analysis options and use our findings to automate the adaptation of matcher configurations to model collections.