When human tutors engage in dialogue, they freely exploit all aspects of the mutually known context, including the previous discourse. Utterances that do not draw on previous discourse seem awkward, unnatural, or even incoherent. Previous discourse must be taken into account in order to relate new information effectively to recently conveyed material , and to avoid repeating old material that w...

Innovative information systems such as content management systems and information brokers are designed to organize a complex mixture of media content – texts, images, maps, videos, . . . – and to present it through domain specific conceptual models, for example, on sports, stock exchange, or art history. In this paper we extend the currently dominating computational container models into a cohe...

Integrating higher level visual and linguistic interpretations is at the heart of human intelligence. As automatic visual category recognition in images is approaching human performance, the high level understanding in the dynamic spatiotemporal domain of videos and its translation into natural language is still far from being solved. While most works on vision-to-text translations use pre-lear...

Graph convolutional network-based methods have become mainstream for cross-language entity alignment. The graph network has multi-order characteristics that not only process data more conveniently but also reduce the interference of noise effectively. Although existing achieved good results task alignment, they often overlooked same names in real corpus, resulting an entity-matching result was ...

This thesis proposes new methods for entity linking in natural language text that assigns entity mentions in unstructured natural language text to the semi-structured encyclopedia Wikipedia. Doing so, entity linking grounds a mention to an encyclopedic entry in Wikipedia and embeds it into this Linked-Open-Data hub. This enables a higher level view on single documents, provides hints for furthe...

In the era of big data, a large amount unstructured text data springs up every day. Entity linking involves relating mentions found in texts to corresponding entities, which stand for objective things real world, knowledge base. This task can help computers understand semantics correctly. Although there have been numerous approaches employed research such as this, some challenges are still unre...

Distributed systems are becoming increasingly important in order to scale services. However, these systems are complex with significant concurrency and need for synchronization. Hence, these are difficult to develop and we need better ways to program such systems. In this work, we present a new paradigm to program distributed systems based on real world distributed systems. We are social beings...