| Marko Grobelnik|
(Alternative names for this author)
|Co-authors||Abhijit Bhole, Blaz Fortuna, Davies J., Dunja Mladeni, Elena Simperl, Frank Dengler, Gomez-Perez J.M., Mladenic D., Moreno C.R., Paul Warren, Sipos R., Thurlow I.|
|Authorship||Publications (3), datasets (0), tools (0)|
|Citations||Total (0), average (0), median (0), max (0), min (0)|
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Marko Grobelnik 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|
|Overcoming information overload in the enterprise: The active approach||Context mining
|IEEE Internet Computing||English||2010||Knowledge workers are central to an organization's success, yet their information management tools often hamper their productivity. This has major implications for businesses across the globe because their commercial advantage relies on the optimal exploitation of their own enterprise information, the huge volumes of online information, and the productivity of the required knowledge work. The Active project addresses this challenge through an integrated knowledge management workspace that reduces information overload by significantly improving the mechanisms for creating, managing, and using information. The project's approach follows three themes: sharing information through tagging, wikis, and ontologies; prioritizing information delivery by understanding users' current-task context; and leveraging informal processes that are learned from user behavior.||0||0|
|Demo: Historyviz - Visualizing events and relations extracted from wikipedia||Lecture Notes in Computer Science||English||2009||HistoryViz provides a new perspective on a certain kind of textual data, in particular the data available in the Wikipedia, where different entities are described and put in historical perspective. Instead of browsing through pages each describing a certain topic, we can look at the relations between entities and events connected with the selected entities. The presented solution implemented in HistoryViz provides user with a graphical interface allowing viewing events concerning the selected person on a timeline and viewing relations to other entities as a graph that can be dynamically expanded.||0||0|
|Mining Wikipedia and Relating Named Entities over Time||English||2007||0||0|