Ontology

Ontology (Alternative names for this keyword)
Related keyword(s)	Unknown [+]
Export and share
BibTeX, CSV, RDF, JSON
Browse properties · List of keywords

Ontology is included as keyword or extra keyword in 0 datasets, 0 tools and 15 publications.

Datasets

There is no datasets for this keyword.

Tools

There is no tools for this keyword.

Publications

Title	Author(s)	Published in	Language	DateThis property is a special property in this wiki.	Abstract	R	C
The people's encyclopedia under the gaze of the sages: a systematic review of scholarly research on Wikipedia	Chitu Okoli Mohamad Mehdi Mostafa Mesgari Finn Årup Nielsen Arto Lanamäki		English	2012	Wikipedia has become one of the ten most visited sites on the Web, and the world’s leading source of Web reference information. Its rapid success has inspired hundreds of scholars from various disciplines to study its content, communication and community dynamics from various perspectives. This article presents a systematic review of scholarly research on Wikipedia. We describe our detailed, rigorous methodology for identifying over 450 scholarly studies of Wikipedia. We present the WikiLit website (http wikilit dot referata dot com), where most of the papers reviewed here are described in detail. In the major section of this article, we then categorize and summarize the studies. An appendix features an extensive list of resources useful for Wikipedia researchers.	15	0
Building ontological models from Arabic Wikipedia: a proposed hybrid approach	Nora I. Al-Rajebah Hend S. Al-Khalifa AbdulMalik S. Al-Salman	IiWAS	English	2010		0	0
Frequent itemset based hierarchical document clustering using Wikipedia as external knowledge	G. V. R. Kiran Ravi Shankar Vikram Pudi	KES	English	2010		0	0
Ontology-driven generation of wiki content and interfaces	Angelo Di Iorio Alberto Musetti Silvio Peroni Fabio Vitali	New Rev. Hypermedia Multimedia	English	2010		0	0
Semantic Web for E-Governance Using Wiki Technology	Vidya Gavekar Manisha A. Kumbhar Anil D. Kumbhar	ICETET	English	2010		0	0
Timely YAGO: harvesting, querying, and visualizing temporal knowledge from Wikipedia	Yafang Wang Mingjie Zhu Lizhen Qu Marc Spaniol Gerhard Weikum	EDBT	English	2010		0	0
"All You Can Eat" Ontology-Building: Feeding Wikipedia to Cyc	Samuel Sarjant Catherine Legg Michael Robinson Olena Medelyan	WI-IAT	English	2009	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 ontology-building, 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.	0	0
Identifying document topics using the Wikipedia category network	Peter Schönhofen	Web Intelli. and Agent Sys.	English	2009	In the last few years the size and coverage of Wikipedia, a community edited, freely available on-line encyclopedia has reached the point where it can be effectively used to identify topics discussed in a document, similarly to an ontology or taxonomy. In this paper we will show that even a fairly simple algorithm that exploits only the titles and categories of Wikipedia articles can characterize documents by Wikipedia categories surprisingly well. We test the reliability of our method by predicting categories of Wikipedia articles themselves based on their bodies, and also by performing classification and clustering on 20 Newsgroups and RCV1, representing documents by their Wikipedia categories instead of (or in addition to) their texts.	0	1
Mining meaning from Wikipedia	Olena Medelyan David N. Milne Catherine Legg Ian H. Witten	Int. J. Hum.-Comput. Stud.	English	2009		0	4
WikiOnto: A System for Semi-automatic Extraction and Modeling of Ontologies Using Wikipedia XML Corpus	Lalindra Niranjan De Silva Lakshman Jayaratne	ICSC	English	2009		0	0
Ontology enhanced web image retrieval: aided by wikipedia \& spreading activation theory	Huan Wang Xing Jiang Liang-Tien Chia Ah-Hwee Tan	MIR	English	2008		0	0
Wikipedia in Action: Ontological Knowledge in Text Categorization	Maciej Janik Krys J. Kochut	ICSC	English	2008		0	0
YAGO: A Large Ontology from Wikipedia and WordNet	F. Suchanek G. Kasneci G. Weikum	Web Semantics: Science, Services and Agents on the World Wide Web	English	2008	This article presents YAGO, a large ontology with high coverage and precision. YAGO has been automatically derived from Wikipedia and WordNet. It comprises entities and relations, and currently contains more than 1.7 million entities and 15 million facts. These include the taxonomic Is-A hierarchy as well as semantic relations between entities. The facts for YAGO have been extracted from the category system and the infoboxes of Wikipedia and have been combined with taxonomic relations from WordNet. Type checking techniques help us keep YAGO’s precision at 95%—as proven by an extensive evaluation study. YAGO is based on a clean logical model with a decidable consistency. Furthermore, it allows representing n-ary relations in a natural way while maintaining compatibility with RDFS. A powerful query model facilitates access to YAGO’s data.	0	1
OntoWiki: Commuity-driven Ontology Engineering and Ontology Usage based on Wikis	Martin Hepp Daniel Bachlechner Katharina Siorpaes	WikiSym	English	2006		0	1
Wiki Communities in the Context of Work Processes	Frank Fuchs-Kittowski Andre Köhler	WikiSym	English	2005	In this article we examine the integration of communities of practice supported by a wiki into work processes. Linear structures are often inappropriate for the execution of knowledge-intensive tasks and work processes. The latter are characterized by non-linear sequences and dynamic social interaction. Communities of practice, however, often lack the „guiding light” needed to structure their work. We discuss the primary requirements for the integration of formally described knowledge-intensive processes into the dynamic social processes of knowledge generation in communities of practice and use the wiki approach for their support. We present our approach for an appropriate interface to integrate wiki communities into process structures and an information retrieval algorithm based on it to connect the process-oriented structures with community-oriented wiki structures. We show the prototypical realization of the concept by a brief example.	0	1