Wikipedia is a goldmine of information; not just for its many readers, but also for the growing community of researchers who recognize it as a resource of exceptional scale and utility. It represents a vast investment of manual effort and judgment: a huge, constantly evolving tapestry of concepts and relations that is being applied to a host of tasks.This article provides a comprehensive description of this work. It focuses on research that extracts and makes use of the concepts, relations, facts and descriptions found in Wikipedia, and organizes the work into four broad categories: applying Wikipedia to natural language processing; using it to facilitate information retrieval and information extraction; and as a resource for ontology building. The article addresses how Wikipedia is being used as is, how it is being improved and adapted, and how it is being combined with other structures to create entirely new resources. We identify the research groups and individuals involved, and how their work has developed in the last few years. We provide a comprehensive list of the open-source software they have produced. r
This article is concerned with developing a philosophical approach to a number of significant changes to academic publishing, and specifically the global journal knowledge system wrought by a range of new digital technologies that herald the third age of the journal as an electronic, interactive and mixed-media form of scientific communication. The paper emerges from an Editors' Collective, a small New Zealand-based organisation comprised of editors and reviewers of academic journals mostly in the fields of education and philosophy. The paper is the result of a collective writing process.
In order to achieve genuine web intelligence, building some kind of large general machine-readable conceptual scheme (i.e. ontology) seems inescapable. Yet the past 20 years have shown that manual ontology-building is not practicable. The recent explosion of free user-supplied knowledge on the Web has led to great strides in automatic ontologybuilding, but quality-control is still a major issue. Ideally one should automatically build onto an already intelligent base. We suggest that the long-running Cyc project is able to assist here. We describe methods used to add 35K new concepts mined from Wikipedia to collections in ResearchCyc entirely automatically. Evaluation with 22 human subjects shows high precision both for the new concepts' categorization, and their assignment as individuals or collections. Most importantly we show how Cyc itself can be leveraged for ontological quality control by 'feeding' it assertions one by one, enabling it to reject those that contradict its other knowledge.
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