Context-Aware Predictions on Business Processes: An Ensemble-Based Solution

2013 ◽  
pp. 215-229 ◽  
Author(s):  
Francesco Folino ◽  
Massimo Guarascio ◽  
Luigi Pontieri
Keyword(s):  
Business Processes ◽  
Context Aware

Call U Back

2011 ◽  
Vol 2 (2) ◽  
pp. 1-13
Author(s):  
Xining Li ◽  
Jiazao Lin
Keyword(s):  
Knowledge Sharing ◽  
Context Awareness ◽  
Intelligent Agents ◽  
Business Processes ◽  
Research Area ◽  
Mobile Users ◽  
Great Success ◽  
Context Aware ◽  
Logical Inference ◽  
Business Applications

Mobile commerce (M-commerce) is an attractive research area due to its relative novelty, rapid growth, and great potential in business applications. Over the last decade, various M-commerce applications have been geared to target mobile users and achieved great success. However, most M-commerce applications are developed by different retailers for special purposes and thus lack fully automated business processes to integrate various existing services. This paper presents a novel infrastructure, Call U Back (CUB), for M-commerce applications. The proposed scheme integrates concepts of agent and context-aware workflow to implement automated trading tasks and compose services dynamically. The context awareness is based on ontology and logic models which derive from a set of descriptive contextual attributes for knowledge sharing and logical inference. Based upon the context-aware workflow analysis, the system will generate automated intelligent agents to conduct commerce transactions on behalf of mobile users. The middleware layer of the CUB server has been implemented. An experimental prototype of the system is under development and testing.

A Broader View on Context Models towards Supporting Business Process Agility

2011 ◽  
pp. 337-358 ◽  
Author(s):  
Barbara Thönssen ◽  
Daniela Wolff
Keyword(s):  
Business Process ◽  
Enterprise Architecture ◽  
Business Processes ◽  
Ad Hoc ◽  
Workflow Engine ◽  
Context Aware ◽  
Context Model ◽  
Model Based ◽  
Run Time ◽  
Context Models

Today’s enterprises need to be agile, to be able to cope with unexpected changes, to increasingly be dynamic, and to continually deal with change. Change affecting business processes may range from ad hoc modification to process evolution. In this chapter we present dimensions of change concentrating on a specific ability of an enterprise to deal with change. To support business in being agile we propose a semantically enriched context model based on well known enterprise architecture. We present a context aware workflow engine basing on the context model and on rules which trigger process adaptations during run time.

POVOO

2011 ◽  
pp. 349-363
Author(s):  
Eva Gahleitner ◽  
Wolfram Wöß
Keyword(s):  
Information Retrieval ◽  
Information Systems ◽  
Business Processes ◽  
Knowledge Bases ◽  
Context Aware ◽  
Specialized Knowledge ◽  
Current Process ◽  
Actual Working ◽  
Static Information ◽  
Working Situation

Ontologies still lack in including and considering the dynamic aspects of business processes. Therefore, existing ontology-based information systems provide only static information which does not suit the actual working context of a user. In this project we extend information retrieval techniques with ontologies through a process oriented view on ontologies (POVOO). The purpose is to satisfy a user with information that depends on the current process the user is working on. Due to a context aware approach, it is possible to adapt the information to the user’s current working situation dynamically. We introduce a methodology for generating views on ontologies and we illustrate how an application can use them to query highly specialized knowledge bases.

Call U Back

2013 ◽  
pp. 61-73
Author(s):  
Xining Li ◽  
Jiazao Lin
Keyword(s):  
Knowledge Sharing ◽  
Context Awareness ◽  
Intelligent Agents ◽  
Business Processes ◽  
Research Area ◽  
Mobile Users ◽  
Great Success ◽  
Context Aware ◽  
Logical Inference ◽  
Business Applications

Mobile commerce (M-commerce) is an attractive research area due to its relative novelty, rapid growth, and great potential in business applications. Over the last decade, various M-commerce applications have been geared to target mobile users and achieved great success. However, most M-commerce applications are developed by different retailers for special purposes and thus lack fully automated business processes to integrate various existing services. This paper presents a novel infrastructure, Call U Back (CUB), for M-commerce applications. The proposed scheme integrates concepts of agent and context-aware workflow to implement automated trading tasks and compose services dynamically. The context awareness is based on ontology and logic models which derive from a set of descriptive contextual attributes for knowledge sharing and logical inference. Based upon the context-aware workflow analysis, the system will generate automated intelligent agents to conduct commerce transactions on behalf of mobile users. The middleware layer of the CUB server has been implemented. An experimental prototype of the system is under development and testing.

A framework for context-aware heterogeneous group decision making in business processes

2016 ◽  
Vol 102 ◽  
pp. 39-50 ◽  
Author(s):  
Carmen De Maio ◽  
Giuseppe Fenza ◽  
Vincenzo Loia ◽  
Francesco Orciuoli ◽  
Enrique Herrera-Viedma
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Business Processes ◽  
Group Decision ◽  
Heterogeneous Group ◽  
Context Aware

scholarly journals Towards Context-Aware Smart Healthcare Platform

2019 ◽  
Vol 3 (1) ◽  
Author(s):  
Aldina Avdić ◽  
Ejub Kajan ◽  
Dragan Janković ◽  
Dženan Avdić
Keyword(s):  
Business Processes ◽  
Energy Savings ◽  
Smart Cities ◽  
Special Kind ◽  
Future Research ◽  
Context Aware ◽  
Transportation Energy ◽  
Smart Transportation ◽  
Proper Actions ◽  
Smart Healthcare

This paper deals with the context-aware smart healthcare platform, based on IoT and citizen sensing. The proposed platform provides support to smart cities' citizens in the form of air quality visualization in their surroundings and by appropriate notifications in case of dangerous pollutants level is sensed. It also provides medical assistance based on “help needed” function, and where available, on the medical record of a patient that uses the platform services. The platform is interactive, so the information sent by the users and the requests for help will be processed. Platform development is based on a special kind of social machine that is capable to capture the city’s sensors data, analyze these data and to interact with appropriate business processes. On return, that interaction results with several goals achieved with the project. Presented dashboard visualization allows decision makers, e.g. medical staff, to take proper actions on time and on-the-fly. On the other side, citizens that suffer from a variety of disease problems are able to report an air pollution incident, and ask for help, if they felt worse. The platform itself has a wider usability value and may be deployed to other smart services in a city, e.g. waste management, smart transportation, energy savings, etc. It is also scalable and open for a variety of sensor devices ranges from smartphones, wearables, and other IoT that resides in a smart city, and for different forms of crowdsensing methods. Finally, concluding remarks emphasize the future research directions.

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