Group items matching

in title, tags, annotations or url

Semantic Web applications offer great potential to student modellers who have traditionally struggled with issues of re-use, portability and tight coupling with learning applications. In this paper, we describe our use of ontology languages and elearning standards to develop a loosely coupled and portable student modelling architecture used in a large-scale, distributed production learning environment.

Latent Semantic Analysis @ CU Boulder Demonstration tools that use LSA.

Tamara Munzner Ph.D. dissertation, Stanford University, June 2000. Abstract *Visualization/graphing strategy for large semantic networks is described. Very technical.* Many real-world domains can be represented as large node-link graphs: backbone Internet routers connect with 70,000 other hosts, mid-sized Web servers handle between 20,000 and 200,000 hyperlinked documents, and dictionaries contain millions of words defined in terms of each other. Computational manipulation of such large graphs is common, but previous tools for graph visualization have been limited to datasets of a few thousand nodes. Visual depictions of graphs and networks are external representations that exploit human visual processing to reduce the cognitive load of many tasks that require understanding of global or local structure. We assert that the two key advantages of computer-based systems for information visualization over traditional paper-based visual exposition are interactivity and scalability. We also argue that designing visualization software by taking the characteristics of a target user's task domain into account leads to systems that are more effective and scale to larger datasets than previous work.