Deriving concept hierarchies from text
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
Computers and Intractability; A Guide to the Theory of NP-Completeness
Computers and Intractability; A Guide to the Theory of NP-Completeness
Improved annotation of the blogosphere via autotagging and hierarchical clustering
Proceedings of the 15th international conference on World Wide Web
The complex dynamics of collaborative tagging
Proceedings of the 16th international conference on World Wide Web
All-pairs bottleneck paths in vertex weighted graphs
SODA '07 Proceedings of the eighteenth annual ACM-SIAM symposium on Discrete algorithms
Constructing folksonomies from user-specified relations on flickr
Proceedings of the 18th international conference on World wide web
User-induced links in collaborative tagging systems
Proceedings of the 18th ACM conference on Information and knowledge management
On Deriving Tagsonomies: Keyword Relations Coming from Crowd
ICCCI '09 Proceedings of the 1st International Conference on Computational Collective Intelligence. Semantic Web, Social Networks and Multiagent Systems
Proceedings of the third ACM international conference on Web search and data mining
Growing a tree in the forest: constructing folksonomies by integrating structured metadata
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
Ontology emergence from folksonomies
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
Crowdsourcing systems on the World-Wide Web
Communications of the ACM
Crowdsourcing 101: putting the WSDM of crowds to work for you
Proceedings of the fourth ACM international conference on Web search and data mining
Managing crowdsourced human computation: a tutorial
Proceedings of the 20th international conference companion on World wide web
CrowdDB: answering queries with crowdsourcing
Proceedings of the 2011 ACM SIGMOD International Conference on Management of data
Cascade: crowdsourcing taxonomy creation
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
| Hi-index | 0.00 |
Taxonomies are great for organizing and searching web content. As such, many popular classes of web applications, utilize them. However, their manual generation and maintenance by experts is a time-costly procedure, resulting in static taxonomies. On the other hand, mining and statistical approaches may produce low quality taxonomies. We thus propose a drastically new approach, based on the proven, increased human involvement and desire to tag/annotate web content. We define the required input from humans in the form of explicit structural, e.g., supertype-subtype relationships between concepts. Hence we harvest, via common annotation practices, the collective wisdom of users with respect to the (categorization of) web content they share and access. We further define the principles upon which crowdsourced taxonomy construction algorithms should be based. The resulting problem is NP-Hard. We thus provide and analyze heuristic algorithms that aggregate human input and resolve conflicts. We evaluate our approach with synthetic and real-world crowdsourcing experiments and on a real-world taxonomy.