Kategorie: ‘Courses’

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.

Knowledge Graph Lab SS 2022

April 1st, 2022 | by

Knowledge Graphs are large graphs used to capture information about the real world in such a way that is is useful for applications. In these data structures, there are all sorts of entities (for example, people, events, places, organizations, etc.). Knowledge Graphs are used by many organizations to represent the information they need for their operations. The most well-known example is Google, where a knowledge graph is used to enrich the search results. Also personal assistants, such as Amazon’s Alexa, Apple’s Siri and Google Now, as well as question answering systems such as IBM Watson, make use of knowledge graphs to provide information to their users.

Besides these, also other information graphs, are in use by large organizations to improve or personalize their services. Examples include the Facebook graph, the Amazon product graph, and the Thompson Reuters Knowledge Graph.

Opensource Knowledge Graphs such as Wikidata and DBPedia provide universal access to linked entities from a large range of domains.

The graph also contains all sorts of information about these entities (e.g., age, opening hours, …) and relations between them (e.g., “this shop is located in Aachen”). Furthermore, it may contain context information (e.g., the source of some information) and schema information or background knowledge (e.g., “shops have opening hours”).

In this course we will give a basic practical introduction to working with these graphs. We plan to cover the following in the course:

  • Graph representation of data
  • Knowledge Graph basics
  • Knowledge Graph creation and maintainance tasks: Creation, Hosting, Curation and Deployment
  • Use of vocabularies and ontologies as schemas for graphs
  • Searching information in knowledge graphs
  • Information extraction into knowledge graphs
  • Data mining techniques for knowledge graphs
  • Knowledge graph completion (predicting links, finding anomalies)
  • Data governance aspects, e.g., data quality
  • Architectures for knowledge graphs (e.g., data lakes, central vs. decentral storage, knowledge graphs on top of relational or NoSQL databases)

Datenbanken und Informationssysteme

March 23rd, 2022 | by

Die Vorlesung “Datenbanken und Informationssysteme” gibt einen einführenden Überblick über Datenbanken und ihre Verwendung in Informationssystemen.

Informationsmanagement für öffentliche Mobilitätsangebote

January 11th, 2022 | by

Die Vorlesung gibt eine Einführung in die organisatorischen und technischen Aufgabenstellungen bei der Planung, der Organisation, dem Betrieb und der Qualitätssicherung von öffentlichen Mobilitätsangeboten, die mit Hilfe von Ansätzen aus der Informatik und Informationssystemen gelöst werden können.

Seminar Data Stream Management and Analysis

December 21st, 2021 | by

Low-cost sensors and high communication bandwidths open up new possibilities for applications that benefit from a high amount of data. Such applications produce data continuously, potentially unbounded, and at high rates, which is subsumed under the term data stream. Examples for applications fields are smart manufacturing, high-speed trading, fraud detection, robotics, or social networks. Data stream management systems are special systems which address the specific requirements handling data streams. In this seminar we will research recent topics in data stream management and analysis, such as data compression, online learning, or operator distribution. The seminar will be offered as block seminar.

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.

Privacy and Big Data

December 20th, 2021 | by

This seminar is about new and emerging approaches to adjust and balance privacy and utility in data intensive applications, such as information retrieval, data mining and personalisation. These new approaches have the potential to enable a new generation of privacy-enabled services which are not focused on maximizing the collection of user data. Instead these new approaches enable user privacy under different threat models, such as protecting the identity of individual users when querying aggregated data, or preventing leakage of query patterns when users retrieve data from a database. As a result, these new approaches may help businesses in their compliance with increasingly regulatory trust and reinforce user trust, while enabling new business models at the same time.

Seminar Data Ecosystems

December 20th, 2021 | by

Organizations in many domains, such as manufacturing or healthcare, have a huge demand to exchange data to enable new services, drive research and innovation, or improve patient care.
Hence, organizations require alliance-driven infrastructures capable of supporting controlled data exchange across diverse stakeholders and transparent data management. Data Ecosystems are distributed, open, and adaptive information systems with the characteristics of being self-organizing, scalable, and sustainable trying to fulfil these requirements.
But there are many open issues, which make the exchange on a technological, processual, and organizational level a challenge. In this seminar, we will identify and discuss the main challenges in data ecosystems, such as data quality, data transparency, and data integration.

Web Science Seminar

December 20th, 2021 | by

Web Science has become an interdisciplinary study field between computer science, mathematics, sociology, economics, and other disciplines. This seminar researches advanced Web Analytics and Web Engineering topics in Web Science probably leading to master thesis topics for excellent students. Topics include: network evolution models and network dynamics, (overlapping) community detection, recommender systems, adaptation and personalization in Web Environments, the Educational Web, Web Trust & Credibility, Web Protocols, Peer-to-Peer Networking for Web Clients, Web-based Software Development Models, particular Web Development methods like Web Components and many more. Students do not only learn to write and present scientific papers but also to peer review them. Students will be assigned to a supervisor helping the student through all steps like literature research, seminar paper and seminar presentation.

Basic End2End Resourcemanager

December 20th, 2021 | by

In this practical course, the participants learn to run a software development project and create a software product from the very beginning – from requirement analysis to release. The students will learn the importance of Scrum as part of the agile software development process.