Codifying collaborative knowledge: using Wikipedia as a basis for automated ontology learning

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Codifying collaborative knowledge: using Wikipedia as a basis for automated ontology learning
Authors: Tao Guo, David G. Schwartz, Frada Burstein, Henry Linger [edit item]
Citation: Knowledge Management Research & Practice 7 (3): 206-17. 2009 September.
Publication type: Journal article
Peer-reviewed: Yes
Database(s):
DOI: 10.1057/kmrp.2009.14.
Google Scholar cites: Citations
Link(s): Paper link
Added by Wikilit team: Added on initial load
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Codifying collaborative knowledge: using Wikipedia as a basis for automated ontology learning is a publication by Tao Guo, David G. Schwartz, Frada Burstein, Henry Linger.


[edit] Abstract

In the context of knowledge management, ontology construction can be considered as a part of capturing of the body of knowledge of a particular problem domain. Traditionally, ontology construction assumes a tedious codification of the domain experts knowledge. In this paper, we describe a new approach to ontology engineering that has the potential of bridging the dichotomy between codification and collaboration turning to Web 2.0 technology. We propose to shift the primary source of ontology knowledge from the expert to socially emergent bodies of knowledge such as Wikipedia. Using Wikipedia as an example, we demonstrate how core terms and relationships of a domain ontology can be distilled from this socially constructed source. As an illustration, we describe how our approach achieved over 90\% conceptual coverage compared with Gold standard hand-crafted ontologies, such as Cyc. What emerges is not a folksonomy, but rather a formal ontology that has nonetheless found its roots in social knowledge.

[edit] Research questions

"In this paper, we argue that traditional approaches to ontology construction that rely on expert input and published documentation are inconsistent with the dynamic needs to enable situated action. Such approaches require significant effort to address multiple practices and different perspectives of the work domain and often fail in supporting knowledge sharing in time and space. We study an alternative ontology learning technique, which should be more efficient, sufficiently accurate and workable from an engineering perspective. We propose an innovative approach to ontology engineering that has the potential of bridging the traditional dichotomy between codification and collaboration through creative use of the knowledge management technology of Web 2.0. By shifting the primary source of knowledge from the expert to socially emergent bodies of knowledge created as a result of Web 2.0 development, we have identified the potential of using collaborative knowledge, rather than brittle expert knowledge, as the basis for ontology construction."

Research details

Topics: Ontology building [edit item]
Domains: Information science, Knowledge management [edit item]
Theory type: Design and action [edit item]
Wikipedia coverage: Sample data [edit item]
Theories: "Undetermined" [edit item]
Research design: Design science, Experiment [edit item]
Data source: Experiment responses, Wikipedia pages [edit item]
Collected data time dimension: Cross-sectional [edit item]
Unit of analysis: Category [edit item]
Wikipedia data extraction: Live Wikipedia [edit item]
Wikipedia page type: Article, Information categorization and navigation [edit item]
Wikipedia language: Not specified [edit item]

[edit] Conclusion

"We have proposed and illustrated an application of a semiautomatic approach to collaborative ontology learning that shows promising results when compared to two Gold standard hand-crafted ontologies with over 90% CC reached in 1-h effort by a non-expert. Our emerging ability to incorporate such knowledge in ontologies as the basis for knowledge management tools will result in richer, more precise, and more relevant knowledge codification, in an ever-changing world in which access to social knowledge plays an increasingly important role. As we advance testing of the ontology learning component, we expect that the impact on a broader engineering methodology will be substantial, and yet, much more work is needed in this area. Using additional meta-knowledge characteristics of the collaborative corpus as provided by the Wikipedia, API also opens up a number of interesting directions as mentioned above."

[edit] Comments

""Research design" should be "design science". There is a small evaluation with comparison against WordNet and Cyc. One could argue that "Research design" should also include "experiment".

"Wikipedia language could be set to "English". This is implicit given the words they are using.

"Wikipedia page type" should also include "Information categorization and navigation". These are downloaded.

"Unit of analysis" is mostly "category", - although pages are also used in their system."


Further notes[edit]

Facts about "Codifying collaborative knowledge: using Wikipedia as a basis for automated ontology learning"RDF feed
AbstractIn the context of knowledge management, onIn the context of knowledge management, ontology construction can be considered as a part of capturing of the body of knowledge of a particular problem domain. Traditionally, ontology construction assumes a tedious codification of the domain experts knowledge. In this paper, we describe a new approach to ontology engineering that has the potential of bridging the dichotomy between codification and collaboration turning to Web 2.0 technology. We propose to shift the primary source of ontology knowledge from the expert to socially emergent bodies of knowledge such as Wikipedia. Using Wikipedia as an example, we demonstrate how core terms and relationships of a domain ontology can be distilled from this socially constructed source. As an illustration, we describe how our approach achieved over 90\% conceptual coverage compared with Gold standard hand-crafted ontologies, such as Cyc. What emerges is not a folksonomy, but rather a formal ontology that has nonetheless found its roots in social knowledge.eless found its roots in social knowledge.
Added by wikilit teamAdded on initial load +
Collected data time dimensionCross-sectional +
Comments"Research design" should be "design scienc"Research design" should be "design science". There is a small evaluation with comparison against WordNet and Cyc. One could argue that "Research design" should also include "experiment".

"Wikipedia language could be set to "English". This is implicit given the words they are using.

"Wikipedia page type" should also include "Information categorization and navigation". These are downloaded.

"Unit of analysis" is mostly "category", - although pages are also used in their system.
hough pages are also used in their system.
ConclusionWe have proposed and illustrated an applicWe have proposed and illustrated an application of

a semiautomatic approach to collaborative ontology learning that shows promising results when compared to two Gold standard hand-crafted ontologies with over 90% CC reached in 1-h effort by a non-expert. Our emerging ability to incorporate such knowledge in ontologies as the basis for knowledge management tools will result in richer, more precise, and more relevant knowledge codification, in an ever-changing world in which access to social knowledge plays an increasingly important role. As we advance testing of the ontology learning component, we expect that the impact on a broader engineering methodology will be substantial, and yet, much more work is needed in this area. Using additional meta-knowledge characteristics of the collaborative corpus as provided by the Wikipedia, API also opens up a

number of interesting directions as mentioned above.
interesting directions as mentioned above.
Data sourceExperiment responses + and Wikipedia pages +
Doi10.1057/kmrp.2009.14 +
Google scholar urlhttp://scholar.google.com/scholar?ie=UTF-8&q=%22Codifying%2Bcollaborative%2Bknowledge%3A%2Busing%2BWikipedia%2Bas%2Ba%2Bbasis%2Bfor%2Bautomated%2Bontology%2Blearning%22 +
Has authorTao Guo +, David G. Schwartz +, Frada Burstein + and Henry Linger +
Has domainInformation science + and Knowledge management +
Has topicOntology building +
Issue3 +
MonthSeptember +
Pages206-17 +
Peer reviewedYes +
Publication typeJournal article +
Published inKnowledge Management Research & Practice +
Research designDesign science + and Experiment +
Research questionsIn this paper, we argue that traditional aIn this paper, we argue that traditional approaches to

ontology construction that rely on expert input and published documentation are inconsistent with the dynamic needs to enable situated action. Such approaches require significant effort to address multiple practices and different perspectives of the work domain and often fail in supporting knowledge sharing in time and space. We study an alternative ontology learning technique, which should be more efficient, sufficiently accurate and workable from an engineering perspective. We propose an innovative approach to ontology engineering that has the potential of bridging the traditional dichotomy between codification and collaboration through creative use of the knowledge management technology of Web 2.0. By shifting the primary source of knowledge from the expert to socially emergent bodies of knowledge created as a result of Web 2.0 development, we have identified the potential of using collaborative knowledge, rather than brittle expert

knowledge, as the basis for ontology construction.
e, as the basis for ontology construction.
Revid10,698 +
TheoriesUndetermined
Theory typeDesign and action +
TitleCodifying collaborative knowledge: using Wikipedia as a basis for automated ontology learning
Unit of analysisCategory +
Urlhttp://dx.doi.org/10.1057/kmrp.2009.14 +
Volume7 +
Wikipedia coverageSample data +
Wikipedia data extractionLive Wikipedia +
Wikipedia languageNot specified +
Wikipedia page typeArticle + and Information categorization and navigation +
Year2009 +