Fast and effective text mining using linear-time document clustering
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
Clustering Ontology-Based Metadata in the Semantic Web
PKDD '02 Proceedings of the 6th European Conference on Principles of Data Mining and Knowledge Discovery
Comparison of Conceptual Graphs
MICAI '00 Proceedings of the Mexican International Conference on Artificial Intelligence: Advances in Artificial Intelligence
Relationship-based clustering and cluster ensembles for high-dimensional data mining
Relationship-based clustering and cluster ensembles for high-dimensional data mining
Agent-Based Provisioning of Group-Oriented Non-linear Telecommunication Services
ICCCI '09 Proceedings of the 1st International Conference on Computational Collective Intelligence. Semantic Web, Social Networks and Multiagent Systems
Grouping Results of Queries to Ontological Knowledge Bases by Conceptual Clustering
ICCCI '09 Proceedings of the 1st International Conference on Computational Collective Intelligence. Semantic Web, Social Networks and Multiagent Systems
Query Results Clustering by Extending SPARQL with CLUSTER BY
OTM '09 Proceedings of the Confederated International Workshops and Posters on On the Move to Meaningful Internet Systems: ADI, CAMS, EI2N, ISDE, IWSSA, MONET, OnToContent, ODIS, ORM, OTM Academy, SWWS, SEMELS, Beyond SAWSDL, and COMBEK 2009
Disambiguating identity web references using Web 2.0 data and semantics
Web Semantics: Science, Services and Agents on the World Wide Web
Semantic similarity and selection of resources published according to linked data best practice
OTM'10 Proceedings of the 2010 international conference on On the move to meaningful internet systems
Group-oriented services: a shift towards consumer-managed relationships in the telecom industry
Transactions on computational collective intelligence II
Replication and versioning of partial RDF graphs
ESWC'10 Proceedings of the 7th international conference on The Semantic Web: research and Applications - Volume Part I
Predicate trees: a tool for descriptive subgraph extraction
Proceedings of the 2nd International Conference on Web Intelligence, Mining and Semantics
Proceedings of the 3rd Annual ACM Web Science Conference
Classification Analysis in Complex Online Social Networks Using Semantic Web Technologies
ASONAM '12 Proceedings of the 2012 International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2012)
Attract me!: how could end-users identify interesting resources?
Proceedings of the 3rd International Conference on Web Intelligence, Mining and Semantics
Hi-index | 0.00 |
The original Semantic Web vision was explicit in the need for intelligent autonomous agents that would represent users and help them navigate the Semantic Web. We argue that an essential feature for such agents is the capability to analyse data and learn. In this paper we outline the challenges and issues surrounding the application of clustering algorithms to Semantic Web data. We present several ways to extract instances from a large RDF graph and computing the distance between these. We evaluate our approaches on three different data-sets, one representing a typical relational database to RDF conversion, one based on data from a ontologically rich Semantic Web enabled application, and one consisting of a crawl of FOAF documents; applying both supervised and unsupervised evaluation metrics. Our evaluation did not support choosing a single combination of instance extraction method and similarity metric as superior in all cases, and as expected the behaviour depends greatly on the data being clustered. Instead, we attempt to identify characteristics of data that make particular methods more suitable.