Ahmed Gater

Ranking BPEL Processes for Service Discovery

Finding useful services is a challenging and important task in several applications. Current approaches for services retrieval are mostly limited to the matching of their inputs/outputs. In this paper, we argue that in several applications (services having multiple and dependent operations and scientific workflows), the service discovery should be based on the specification of service behavior. The idea behind is to develop matching techniques that operate on behavior models and allow delivery of approximate matches and evaluation of semantic distance between these matches and the user requirements. To do so, we reduce the problem of behavioral matching to a graph matching problem and adapt existing algorithms for this purpose. To validate our approach, we developed a BPEL ranking platform that allows to find in a service repository, a set of service candidates satisfying user requirements, and then, to rank these candidates using a behavioral-based similarity measure.

A Graph-Based Approach for Semantic Process Model Discovery

One of the key tasks in the service oriented architecture that Semantic Web services aim to automate is the discovery of services that can fulfill the applications or user needs. OWL-S is one of the proposals for describing semantic metadata about Web services, which is based on the OWL ontology language. Majority of current approaches for matching OWL-S processes take into account only the inputs/outputs service profile. This chapter argues that, in many situations the service matchmaking should take into account also the process model. We present matching techniques that operate on OWL-S process models and allow retrieving in a given repository, the processes most similar to the query. To do so, the chapter proposes to reduce the problem of process matching to a graph matching problem and to adapt existing algorithms for this purpose. It proposes a similarity measure used to rank the discovered services. This measure captures differences in process structure and semantic differences between input/outputs used in the processes.

A summary-based approach for enhancing process model matchmaking

The importance gained by the process models in modern information systems led to the increasing proliferation of process model repositories. Matching process models and assessing their similarity are critical functionalities required for the management of these collections. In this work1 we present an efficient graph-based technique for matching and evaluating the similarity of semantically annotated process models. Approximate graph matching algorithms which are used in literature (e.g., error correcting sub-graph isomorphism detection), are exponential in size of the graphs. In order to reduce the execution time and improve the applicability of the algorithm for matching and retrieval of process models, we propose a graph summarization technique which reduces the size of the graphs to be compared. Moreover, while most of the related works detect only 1–1 activity mappings, our matching approach is able to detect complex mappings (m-n) between activities based on their input/output sets. Experiments showed that the summarization technique reduces considerably the execution time, maintaining at the same time a good quality of the matching.

OWL-S Process Model Matchmaking

In this paper, we propose an approach for approximate matching of OWL-S process model. We also propose a similarity measure that captures structural and semantic differences between two process models. To do so, we reduce the process matching to a graph matching problem and we adapt existing algorithms for this purpose.

Business Process Paradigms

This chapter provides an overview of the technological landscape surrounding business process management and sets the stage for understanding the different aspects of analyzing business processes with the aim of improving them. The goal of this chapter is to develop an advanced recognition of the potential gaps and thereby an appreciation for key areas of improvement needed to target successful future growth in process analytics. After presenting an overview of the quintessential facets/dimensions often used to describe process types, the chapter examines the various identified implementation technologies and surveys the relevant support tools categorized according to process paradigm.

Spectral Graph Approach for Process Model Matchmaking

In this paper, we propose a novel approach for graph based web service matching. Our approach is inspired by spectral graph matching methods, in particular, by eigen-based projections. We introduce new mechanisms to perform the matchmaking at both structural and semantic levels. These mechanisms are based on algebraic graph techniques that make them run fast and thus suitable for large scale web service matching problems. Experimentation is provided to show the performance of the proposed approach.

A framework for service discovery based on structural similarity and quality satisfaction

The increasing number of published web services rendered the searching for a service within repositories a critical issue in many application domains. Recent approaches resorted to service structure and to preferences over quality attributes to reduce selectivity rate. In this paper, we present S-MatchMaker, a tool for service discovery based on both service structure and quality preferences. The tool implements several algorithms that can be coupled in different ways to provide a personalized solution for service discovery.

Indexing Process Model Flow Dependencies for Similarity Search

The importance gained by process models in modern information systems leaded to the proliferation of process model repositories. Retrieving process models within such repositories is a critical functionality. Recent works propose metrics that rank process models of a repository according to their similarity to a given query. However, these methods sequentially browse all the processes of the repository and compare each one against the query, which is computationally expensive. This paper presents a technique for quickly retrieving process models similar to a given query that relies on an index built on behavioral characteristics of process models.

Model-Based Business Process Query Techniques and Languages

This chapter looks at the business process querying techniques and languages and provides an overview of the various techniques for querying business processes. After discussing different techniques for querying the business process execution logs and their related artifacts, the chapter provides an overview of different approaches for utilizing business process querying techniques for ensuring business process compliance to their specifications and business rules.

Business Process Data Analysis

This chapter looks at business process data analysis and provides an overview of different aspects of business data analysis techniques and approaches from process/dataspaces to data provenance and data-based querying techniques. After providing an overview of warehousing process data, data services, and dataspaces, the chapter discusses the importance of supporting big data analytics over process execution data. It presents a holistic view of the process executions over various information systems and services (i.e., process space) followed by a brief overview of process mining to highlight the interpretation of the information in the enterprise in the context of process mining. Finally, the chapter focuses on process artifacts and introduces crosscutting aspects in processes data such as time and provenance.