ClaiMaker: weaving a semantic web of research papers

The usability of research papers on the Web would be enhanced by a system that explicitly modelled the rhetorical relations between claims in related papers. We describe ClaiMaker, a system for modelling readers’ interpretations of the core content of papers. ClaiMaker provides tools to build a Semantic Web representation of the claims in research papers using an ontology of relations. We demonstrate how the system can be used to make inter-document queries

Visualizing internetworked argumentation

In this chapter, we outline a project which traces its source of inspiration back to the grand visions of Vannevar Bush (scholarly trails of linked concepts), Doug Engelbart (highly interactive intellectual tools, particularly for argumentation), and Ted Nelson (large scale internet publishing with recognised intellectual property). In essence, we are tackling the age-old question of how to organise distributed, collective knowledge. Specifically, we pose the following question as a foil: In 2010, will scholarly knowledge still be published solely in prose, or can we imagine a complementary infrastructure that is ‘native’ to the emerging semantic, collaborative web, enabling more effective dissemination and analysis of ideas

Evaluation of Decision Forests on Text Categorization

Text categorization is useful for indexing documents for information retrieval, filtering parts for document understanding, and summarizing contents of documents of special interests. We describe a text categorization task and an experiment using documents from the Reuters and OHSUMED collections. We applied the Decision Forest classifier and compared its accuracies to those of C4.5 and kNN classifiers, using both category dependent and category independent term selection schemes. It is found that Decision Forest outperforms both C4.5 and kNN in all cases, and that category dependent term selection yields better accuracies. Performances of all three classifiers degrade from the Reuters collection to the OHSUMED collection, but Decision Forest remains to be superior