TY - GEN
T1 - Using ontologies in semantic data mining with SEGS and g-SEGS
AU - Lavrač, Nada
AU - Vavpetič, Anže
AU - Soldatova, Larisa
AU - Trajkovski, Igor
AU - Novak, Petra Kralj
PY - 2011
Y1 - 2011
N2 - With the expanding of the Semantic Web and the availability of numerous ontologies which provide domain background knowledge and semantic descriptors to the data, the amount of semantic data is rapidly growing. The data mining community is faced with a paradigm shift: instead of mining the abundance of empirical data supported by the background knowledge, the new challenge is to mine the abundance of knowledge encoded in domain ontologies, constrained by the heuristics computed from the empirical data collection. We address this challenge by an approach, named semantic data mining, where domain ontologies define the hypothesis search space, and the data is used as means of constraining and guiding the process of hypothesis search and evaluation. The use of prototype semantic data mining systems SEGS and g-SEGS is demonstrated in a simple semantic data mining scenario and in two real-life functional genomics scenarios of mining biological ontologies with the support of experimental microarray data.
AB - With the expanding of the Semantic Web and the availability of numerous ontologies which provide domain background knowledge and semantic descriptors to the data, the amount of semantic data is rapidly growing. The data mining community is faced with a paradigm shift: instead of mining the abundance of empirical data supported by the background knowledge, the new challenge is to mine the abundance of knowledge encoded in domain ontologies, constrained by the heuristics computed from the empirical data collection. We address this challenge by an approach, named semantic data mining, where domain ontologies define the hypothesis search space, and the data is used as means of constraining and guiding the process of hypothesis search and evaluation. The use of prototype semantic data mining systems SEGS and g-SEGS is demonstrated in a simple semantic data mining scenario and in two real-life functional genomics scenarios of mining biological ontologies with the support of experimental microarray data.
KW - Semantic data mining
KW - background knowledge
KW - ontologies
KW - relational data mining
UR - http://www.scopus.com/inward/record.url?scp=80053950527&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-24477-3_15
DO - 10.1007/978-3-642-24477-3_15
M3 - Conference contribution
AN - SCOPUS:80053950527
SN - 9783642244766
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 165
EP - 178
BT - Discovery Science - 14th International Conference, DS 2011, Proceedings
T2 - 14th International Conference on Discovery Science, DS 2011, Co-located with the 22nd International Conference on Algorithmic Learning Theory, ALT 2011
Y2 - 5 October 2011 through 7 October 2011
ER -