AC Smart Government

Intelligent Communication with Citizens

Increasingly, citizens communicate with public administration via digital channels. At the same time, public administrations create additional interfaces for their services. Dialog systems constitute such an interface. They facilitate information access in the form of a conversation. In contrast to human employees, digital assistants work around the clock. Citizens gain better experience. Simultaneously, the dialog system relieves employees. They can handly frequent questions such that their human counterparts can focus on hard cases. Our research revolves around questions concerning how to detect the information need, imitate human dialog, and identify hard instances which it needs to pass on to employees.

Knowledge Management in Public Administration

Public administration continuously witnesses new documents, memoranda, and notes emerging. The included information is crucial to inform and improve workflows. Simultaneously, public administration frequently harbors a heterogeneous data landscape. As a result, information becomes inaccessible. To cope with this technical and organizational challenge, public administrations employ knowledge management systems. These systems gather data and provide tools to access information. Our research centers on defining suited data structures to facilitate distributed information access while considering access rights.

Data and Privacy Protection

Data breaches of considerable scale have awakened the population’s desire for more privacy and data protection. Both aspects concern public administrations as they allocate a variety of personal information. Conversely, public administrations require the information for their workflows. They work on digitizing further processes and thus create new interfaces. The interfaces can potentially access personal information. Our research aims to quantify the problem and suggest concepts to establish the principle of minimal data allocation.

Detecting Security Threats

Public administrations use a variety of software tools to fulfill their purpose. Software is subject to security threats. Such threats particularly challenge administrators as they have to maintain many software tools. Besides, software tools can affect one another, thus creating security threats. Also, administrators have to keep up with the continuously emerging information concerning security threats. Our research tries to establish intelligent systems that can detect security threats and notify administrators.

Intelligent Algorithms to Predict User Behavior

Interactions amid citizens and public administrations necessarily exhibit irregularities. Events can cause citizens to inquire about particular topics. In circumstances in which many citizens simultaneously demand a particular service, public administrations can become overloaded. To facilitate planning resource assignment, public administrations must anticipate these events. Our research employs machine learning to predict resource demand to support public administration in a data-driven fashion.

Further information is available on the web site of the Fachzentrums Intelligente Dienste für Bürger und Behörden (IDBB – Intelligent Services for Citizens and Authorities).