Semistructured Data and Recommendations

Semistructured Data and Recommendations

Current mass-collaboration and social media platforms use tags (or key-value pairs) to annotate and categorize resources enabling effective search capabilities. Due to the broad span of users of such systems (originating from different cultures and backgrounds, speaking different languages, etc.), the information provided features a limited amount of common structure, as e.g., objects are named differently and information is structured differently. This is a severe constraint in regards to the performance of search facilities. Our research aims to advance current recommendation approaches for semi-structured data to overcome structure heterogeneity and to develop tools to support users in the process of information curation.

Please find out more about the developed prototypes here.

 

Team

Current Theses

Publications

2018

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Eva Zangerle and Claudia Müller-Birn: Recommendation-Assisted Data Curation for Wikidata. In Wiki Workshop 2018 co-located with The Web Conference. 2018

2017

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Wolfgang Gassler: The SnoopyConcept: Leveraging Recommendations for Knowledge Curation. PhD thesis, University of Innsbruck, Department of Computer Science, 2017.

2014

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Wolfgang Gassler, Eva Zangerle and Günther Specht: Guided Curation of Semistructured Data in Collaboratively-built Knowledge Bases. In Journal on Future Generation Computer Systems, vol. 31, pages 111-119. Elsevier Science Publishers, 2014.

2013

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Eva Zangerle: Leveraging Recommender Systems for the Creation and Maintenance of Structure within Collaborative Social Media Platforms. PhD thesis, University of Innsbruck, Department of Computer Science, 2013.

2012

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Eva Zangerle and Wolfgang Gassler: Dealing with Structure Heterogeneity in Semantic Collaborative Environments. In Collaboration and the Semantic Web: Social Networks, Knowledge Networks and Knowledge Resources. IGI Publishers, Hershey, Pennsylvania (USA), 2012.

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Wolfgang Gassler, Eva Zangerle, Martin Bürgler and Günther Specht: SnoopyTagging: Recommending Contextualized Tags to Increase the Quality and Quantity of Meta-Information. In Proceedings of the 21st International Conference on the World Wide Web 2012 (WWW 2012), Lyon, France (Poster), pages 511-512. 2012.

2011

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Wolfgang Gassler, Eva Zangerle and Günther Specht: The Snoopy Concept: Fighting Heterogeneity in Semistructured and Collaborative Information Systems by Using Recommendations. In Proceedings of the 2011 International Conference on Collaboration Technologies and Systems (CTS 2011), pages 61-68. 2011.

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Alex Larcher, Eva Zangerle, Wolfgang Gassler and Günther Specht: Key Recommendations for Infoboxes in Wikipedia, 2011, Poster Presentation

2010

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Wolfgang Gassler, Eva Zangerle, Michael Tschuggnall and Günther Specht: SnoopyDB: Narrowing the Gap between Structured and Unstructured Information using Recommendations. In Proceedings of the 21st ACM Conference on Hypertext and Hypermedia (HT 2010), Toronto, Ontario, Canada, June 13-16, 2010, pages 271-272, 2010.

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Wolfgang Gassler and Eva Zangerle: Recommendation-Based Evolvement of Dynamic Schemata in Semistructured Information Systems. In Proceedings of the 22nd Workshop Grundlagen von Datenbanken (GvDB 2010), Bad Helmstedt, Germany. CEUR-WS.org, 2010.

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Eva Zangerle, Wolfgang Gassler and Günther Specht: Recommending Structure in Collaborative Semistructured Information Systems. In Proceedings of the third ACM Conference on Recommender Systems (RecSys 2010), pages 141-145. ACM, 2010.