A5006551782- Business Process Modeling and Analysis
- Service-Oriented Architecture and Web Services
- Advanced Database Systems and Queries
- Big Data and Business Intelligence
- Data Quality and Management
- Software System Performance and Reliability
- Blockchain Technology Applications and Security
- Semantic Web and Ontologies
- Advanced Software Engineering Methodologies
- Data Management and Algorithms
- Information Technology Governance and Strategy
- Scientific Computing and Data Management
- Imbalanced Data Classification Techniques
- Explainable Artificial Intelligence (XAI)
- Data Stream Mining Techniques
- Constraint Satisfaction and Optimization
- Cloud Computing and Resource Management
- Anomaly Detection Techniques and Applications
- Data Mining Algorithms and Applications
- Data Visualization and Analytics
- Statistical and Computational Modeling
- Ethics and Social Impacts of AI
- Digital Transformation in Industry
- Artificial Intelligence in Law
- Cloud Data Security Solutions
IBM Research - Haifa
2011-2023
University of Haifa
2015-2021
IBM (United States)
2007-2013
Carmel (Israel)
2008
Technion – Israel Institute of Technology
1994
AI-augmented Business Process Management Systems (ABPMSs) are an emerging class of process-aware information systems, empowered by trustworthy AI technology. An ABPMS enhances the execution business processes with aim making these more adaptable, proactive, explainable, and context-sensitive. This manifesto presents a vision for ABPMSs discusses research challenges that need to be surmounted realize this vision. To end, we define concept ABPMS, outline lifecycle within discuss core...
A promising approach to managing business operations is based on artifacts, a.k.a. entities (with lifecycles). These are key conceptual that central guiding the of a business, and whose content changes as they move through those operations. An artifact type includes both an information model captures all business-relevant data about type, lifecycle model, specifies possible ways entity might progress business. Two recent papers have introduced studied Guard-Stage-Milestone (GSM) meta-model...
Big data is recognized as one of the three technology trends at leading edge a CEO cannot afford to overlook in 2012. characterized by volume, velocity, variety and veracity ("data doubt"). As big applications, many emerging event processing applications must process events that arrive from sources such sensors social media, which have inherent uncertainties associated with them. Consider, for example, possibility incomplete streams including inaccurate data. In this tutorial we classify...
Proactive event processing constitutes the next phase in evolution of complex processing. makes it possible to anticipate potential issues during process execution and thereby enables proactive management. One industry domain that can expect relevant benefits from applying is transportation. Transportation companies face numerous stochastic when managing shipment goods. such issue faced airfreight exact volume, weight, number pieces a shipper wants have shipped. Because high cost air...
The Agriculture business domain, as a vital part of the overall supply chain, is expected to highly evolve in upcoming years via developments, which are taking place on side Future Internet. This paper presents novel Business-to-Business collaboration platform from agri-food sector perspective, aims facilitate numerous stakeholders belonging associated domains, an effective and flexible manner. contemporary B2B schemes already requirements for swift deployment cloud applications, capable...
Due to its multivariate and multipurpose use reuse, data’s worth is dramatically increasing, leading an era characterized by the generation of data marketplaces towards accessing, selling, sharing, trading assets. However, most market vendors still follow a centralized monolithic cloud model for controlling services. Also, this strategy incompatible with European objectives computing economy, lacking sovereignty cross-cloud interoperability principles. Towards these limitations, FAME project...
As Artificial Intelligence (AI) becomes more integrated into public governance, concerns about its transparency and accountability have become increasingly important. The use of AI in decision-making processes raises questions bias, fairness, the protection individual fundamental rights. To ensure that is used a way upholds democratic values, it essential to develop systems are trustworthy, transparent, accountable. Trusted allows citizens greater trust organizations their processes, while...
This paper proposes a methodology for proactive event-driven decision making. Proper decisions are made by forecasting events prior to their occurrence. Motivation making stems from social and economic factors, is based on the fact that prevention often more effective than cure. The in real time require swift immediate processing of Big Data, is, extremely large amounts noisy data flooding various locations, as well historical data. will recognize forecast opportunities threats, capitalize...
To prevent problems and capitalise on opportunities before they even occur, the research project SPEEDD proposed a methodology, developed prototype for proactive event-driven decisionmaking. We present application of this methodology to credit card fraud management. The machine learning component supports online construction patterns, allowing it efficiently adapt continuously changing types. Moreover, user interface enables analysts make most out results automation (complex event...
In this demo, we present FERARI, a prototype that enables real-time Complex Event Processing (CEP) for large volume event data streams over distributed topologies. Our constitutes, to our knowledge, the first complete, multi-cloud based end-to-end CEP solution incorporating: a) user-friendly, web-based query authoring tool, (b) powerful engine implemented on top of streaming cloud platform, (c) optimizer chooses best execution plan with respect low latency and/or reduced inter-cloud...
Uncertainty is inherent in many real-time event-driven applications. Credit card fraud detection a typical uncertain domain, where potential incidents must be detected real time and tagged before the transaction has been accepted or denied. We present extensions to IBM Proactive Technology Online (PROTON) open source tool cope with uncertainty. The inclusion of uncertainty aspects impacts all levels architecture logic an event processing engine. implemented PROTON include addition new...
Analysts identified "Internet of Everything" (IoE), which is a generalization the term Internet Things as "one major technology trends that will have tremendous impact on life". The IoE stands for collection uniquely objects connected in an Internet-like structure, serving sensors or actuators. However, Forrester Research stated recently "there no Things, yet". Indeed, what makes traditional pervasive ability to consume its content easily by eventually everybody. This still not case IoE. In...
This paper presents The Event Model (TEM) as a means to design, develop, implement, and maintain event-driven applications. friendly, yet rigorous, representation of the event logic in Excel-like tables makes model accessible people lacking IT skills. follows driven engineering approach can be classified CIM (Computation Independent Model). goal is strive for automatic transformation along with engineering. In this we provide methodology transform into running application. We demonstrate our...
We present FERARI, a prototype for processing voluminous event streams over multi-cloud platforms. At its core, FERARI both exploits the potential in-situ (intra-cloud) and orchestrates inter-cloud complex detection in communication-efficient way. application level, it includes user-friendly query authoring tool an analytics dashboard providing granular reports about detected events. In that, constitutes, to our knowledge, first complete end-to-end solution of kind. this demo, we apply...
In recent years, event processing has matured from an emerging technology to one with pervasive uses in various industries. There is a growing segment of applications comprising diversity rule types that are developed by high-level users, who have business logic and process expertise rather than software development skills.