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DBIS

Kategorie: ‘Lectures’

Bridge Course Databases

May 4th, 2022 | by

A blended learning bridge course for master students in Data Science, Computational Social Science and related programs.

Web Science

April 10th, 2022 | by

More than twenty years after the birth of the World Wide Web, Web Science has been becoming a new study field in Computer Science. This course introduces fundamental concepts (web centralities & basic algorithms, network models and web engineering principles) of Web Science. We will learn fundamental algorithms for web page ranking like PageRank and HITS as well as community detection algorithms. In the engineering part we dig into scalable approaches like cloud computing and peer-to-peer partly based on Post-HTTP protocols like the XMPP and WebRTC are. We will learn about Web Services and their RESTful implementation. With the knowledge gained in the preceding chapters we can analyze and engineer advanced Web applications.

Social Computing

December 20th, 2021 | by

Social Computing is an area of computer science that is concerned with the intersection of social behavior and computational systems. It is based on creating or recreating social conventions and social contexts through the use of software and technology. We will address social computing infrastructures, social computing engineering processes, computational social science, in particular recommender systems and community detection, crowdsourcing, collective intelligence, the dark web, mixed reality, mobile social computing, science 2.0 and advanced topics.

Web Science

December 11th, 2021 | by

More than twenty years after the birth of the World Wide Web, Web Science has been becoming a new study field in Computer Science. This course introduces fundamental concepts (web centralities & basic algorithms, network models and web engineering principles) of Web Science. We will learn fundamental algorithms for web page ranking like PageRank and HITS as well as community detection algorithms. In the engineering part we dig into scalable approaches like cloud computing and peer-to-peer partly based on Post-HTTP protocols like the XMPP and WebRTC are. We will learn about Web Services and their RESTful implementation. With the knowledge gained in the preceding chapters we can analyze and engineer advanced Web applications.

Social Computing

December 11th, 2021 | by

Web Science

December 11th, 2021 | by

More than twenty years after the birth of the World Wide Web, Web Science has been becoming a new study field in Computer Science. This course introduces fundamental concepts (web centralities & basic algorithms, network models and web engineering principles) of Web Science. We will learn fundamental algorithms for web page ranking like PageRank and HITS as well as community detection algorithms. In the engineering part we dig into scalable approaches like cloud computing and peer-to-peer partly based on Post-HTTP protocols like the XMPP and WebRTC are. We will learn about Web Services and their RESTful implementation. With the knowledge gained in the preceding chapters we can analyze and engineer advanced Web applications.

Social Computing

December 10th, 2021 | by

Social Computing is an area of computer science that is concerned with the intersection of social behavior and computational systems. It is based on creating or recreating social conventions and social contexts through the use of software and technology.

Social Computing

December 6th, 2021 | by

Bridge Course Databases

December 3rd, 2021 | by

A blended learning bridge course for master students in Data Science, Computational Social Science and related programs.

Implementation of Databases

December 3rd, 2021 | by

The lecture gives an introduction to the implementation of database systems. Besides the rough architecture of a DB system, detailed methods for solving individual DB tasks are discussed (e.g. query processing and transaction management). The concepts of implementation are demonstrated using classical relational DB systems as well as newer systems (distributed DB, NoSQL systems). Concepts, frameworks and components of Big Data architectures, e.g. MapReduce, Apache Spark and Apache Kafka are introduced and practically tested.