| Jochen Fischer|
(Alternative names for this author)
|Co-authors||Dichev C., Dicheva D., Lars Schmidt-Thieme, Manuel Stritt, Steffen Rendle, Zeno Gantner|
|Authorship||Publications (2), datasets (0), tools (0)|
|Citations||Total (0), average (0), median (0), max (0), min (0)|
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Jochen Fischer is an author.
PublicationsOnly those publications related to wikis are shown here.
|Title||Keyword(s)||Published in||Language||DateThis property is a special property in this wiki.||Abstract||R||C|
|Identity: How to name it, how to find it||E-learning
|CEUR Workshop Proceedings||English||2007||The main objective of this work is to exploit the relationship between the information findability problem and a subject-based organization of information. Identification of a subject is involved when one wants to say something about that subject or when he or she tries to comprehend what was said by others about it. An example of this type of duality can be seen in the information world where content creators and content consumers need to communicate. In this paper we discuss the concept of subject identity in learning content authoring, where we view a topic map as supporting the communication between a content author and learners. In this context we address both sides of the dual system and propose some solutions intended to assist both content creators and consumers in dealing with problems typical for e-learning repositories. Concerning the learners who need to identify the subject they are looking information about, we suggest that a set of subjects related to it can be interpreted as a weak form of its identity. This can be used for finding a starting point for content exploration and we propose an algorithm for this task. As to the content authors, they need to use agreed-upon names and possibly subject identifiers to identify the subjects they are talking about. In this relation we suggest using Wikipedia articles as a source for both consensual naming and subject identifiers. We claim that Wikipedia can play a role of a shared context between topic map authors and users and propose an approach for extracting consensual information from Wikipedia. The proposed ideas are implemented in the Topic Maps for e-Learning tool (TM4L).||0||0|
|Ideas and improvements for semantic wikis||ESWC||English||2006||0||0|