Post on 26-Mar-2015
On Why and How to Marry Wikis with Enterprise Search
Hans-Jörg Happel, FZI Karlsruhe, 26.03.2009
2nd Workshop on Integrated Knowledge Management Systems (IKMS2009) at 5th Conference on Professional
Knowledge Management, Solothurn (Switzerland), 2009
Agenda
• Marrying Wikis with Enterprise Search• Architecture & Implementation• Evaluation
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Search and knowledge sharingare mutually intertwined (1)
• Search is an inherently social activity– 40,4% of users interact with others before and during
search; 58,7% share information after search [EC08]
• Knowledge sharing typically depends on a trigger– „If asked for the information, participants would be
willing to share most of the knowledge they accumulate in everyday life. However, they currently lack the tools to do so without exerting extraordinary effort” [DKT08]
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Search and knowledge sharingare mutually intertwined (2)
• However, this is typically not addressed by search and knowledge sharing tools A fundamental gap between creating and accessing information exists
• Research question: How to create a feedback loop to better connect information provision and access?
• Idea: Combine the synergetic features of Wikis and Enterprise Search
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Idea: Marry Wikis and Enterprise Search (1)
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Idea: Marry Wikis and Enterprise Search (2)
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Woogle: Design principles• Improve information access
– Introduce better IR functions to Wiki– Provide integrated search
• Improve information provision– Seamless transition from information seeking to information provision– Provide different modes of information provision– Guide information provision by aggregating information needs („need-
driven knowledge sharing“)
• Improve collaboration– Give queries a first order representation– Provide means for communication and awareness
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Need-driven knowledge sharing
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Collect information needs (e.g. from query logs)
Collect information needs (e.g. from query logs)
Calculate aggegate unsatisfiedinformation needs
Calculate aggegate unsatisfiedinformation needs
Identify private files worth sharing („Inverse Search“
[Hap08b])
Combine Wikis and Search („Woogle“)
Combine Wikis and Search („Woogle“)
Woogle: Implementation
• Woogle is available for two environments– MediaWiki: complete implementation replacing
the built-in search• WoogleNative: full PHP; only for MediaWiki content• WoogleRemote: using TeamWeaverIS Java backend as
a web service; can index various different data sources
– Atlassian Confluence: prototype currently under development
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Anatomy of Woogle4MediaWikihttp://myHost/wiki/Woogle:SOAP
External data sources can be accessed
Collaborative description of the information need
Notifications concerningsearch activities
Discussion page
Directly create new knowledge from the search dialog
Search has a URI and can be linked from within the Wiki(one page per search term)
Chose from different sources and/or content types
Additional clues with meta-information about a need
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Evaluation plan
• Woogle will be evaluated in two stepsa) Qualitative interviews/heuristic evaluation with a limited
number of people (currently ongoing)b) Online field experiments in real world environments (log
analysis plus questionnaire)• In internal projects• Industrial environments (additional partners sought!)
• Woogle has an instrumentation mode and advanded privacy settings for evaluation purposes
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Related work• Collaborative IR/“Social search“– Focus on synchronous collaboration– Do not address information provision
• Wiki & Search (Wikia Search, Google SearchWiki)– Primarily focus on ranking/result annotation– Focus on the Web
• Q/A systems (e.g. Yahoo Answers)– Lack „consensual spirit“ of Wikis– Do not consider external results
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Summary• Woogle is a novel approach to combine Wikis
and (Enterprise) Search– Search becomes collaboratively customizable– Additional content can be added in a piecemeal
fashion– Wikis become information hub by considering
external results improved bootstrapping?
• Next steps– Evaluation is forthcoming – evaluation partners
sought!– Possible extension concerning SMW (c.f.
[Hap08a])– Additional „social search“ features (e.g. social
ranking)
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Literature• [DKT08] Dearman, D., Kellar, M., and Truong, K. N. 2008. An examination of daily information
needs and sharing opportunities. In Proceedings of the ACM 2008 Conference on Computer Supported Cooperative Work (San Diego, CA, USA, November 08 - 12, 2008). CSCW '08. ACM, New York, NY, 679-688.
• [EC08] Evans, B. M. and Chi, E. H. 2008. Towards a model of understanding social search. In Proceedings of the ACM 2008 Conference on Computer Supported Cooperative Work (San Diego, CA, USA, November 08 - 12, 2008). CSCW '08. ACM, New York, NY, 485-494.
• [Hap08a] Hans-Jörg Happel: Growing the Semantic Web with Inverse Semantic Search. In Proceedings of the 1st Workshop on Incentives for the Semantic Web (INSEMTIVE '08)
• [Hap08b] Hans-Jörg Happel: Closing Information Gaps with Inverse Search. In Proceeedings of the 7th International Conference on Practical Aspects of Knowledge Management (PAKM2008)
• [Mor08] Morris, M. R. 2008. A survey of collaborative web search practices. In Proceeding of the Twenty-Sixth Annual SIGCHI Conference on Human Factors in Computing Systems (Florence, Italy, April 05 - 10, 2008). CHI '08. ACM, New York, NY, 1657-1660.
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