Cited By
View all- Liu HDou D(2011)Breaking the deadlockProceedings of the 2011th Confederated international conference on On the move to meaningful internet systems - Volume Part II10.5555/2075764.2075794(698-715)Online publication date: 17-Oct-2011
Ontology-Based mining of brainwaves: a sequence similarity technique for mapping alternative features in event-related potentials (ERP) data
Pages 43 - 54
Abstract
In this paper, we present a method for identifying correspondences, or mappings, between alternative features of brainwave activity in event-related potentials (ERP) data The goal is to simulate mapping across results from heterogeneous methods that might be used in different neuroscience research labs The input to the mapping consists of two ERP datasets whose spatiotemporal characteristics are captured by alternative sets of features, that is, summary spatial and temporal measures capturing distinct neural patterns that are linked to concepts in a set of ERP ontologies, called NEMO (Neural ElectroMagnetic Ontologies) [3, 6] The feature value vector of each summary metric is transformed into a point-sequence curve, and clustering is performed to extract similar subsequences (clusters) representing the neural patterns that can then be aligned across datasets Finally, the similarity between measures is derived by calculating the similarity between corresponding point-sequence curves Experiment results showed that the proposed approach is robust and has achieved significant improvement on precision than previous algorithms.
References
[1]
Agrawal, R., Faloutsos, C., Swami, A.N.: Efficient similarity search in sequence databases In: Lomet, D.B (ed.) FODO 1993 LNCS, vol 730, pp 69-84 Springer, Heidelberg (1993)
[2]
Brinkhoff, T., Kriegel, H.-P., Seeger, B.: Efficient processing of spatial joins using r-trees In: SIGMOD '93: Proceedings of the 1993 ACM SIGMOD international conference on Management of data, pp 237-246 ACM, New York (1993)
[3]
Dou, D., Frishkoff, G., Rong, J., Frank, R., Malony, A., Tucker, D.: Development of NeuroElectroMagnetic Ontologies (NEMO): A Framework for Mining Brain Wave Ontologies In: Proceedings of the 13th ACM International Conference on Knowledge Discovery and Data Mining (KDD 2007), pp 270-279 (2007)
[4]
Faloutsos, C., Seeger, B., Traina, A., Traina Jr., C.: Spatial join selectivity using power laws In: SIGMOD '00: Proceedings of the 2000 ACM SIGMOD international conference on Management of data, pp 177-188 ACM, New York (2000)
[5]
Frishkoff, G.A., Frank, R.M., Rong, J., Dou, D., Dien, J., Halderman, L.K.: A Framework to Support Automated Classification and Labeling of Brain Electromagnetic Patterns Computational Intelligence and Neuroscience (CIN), Special Issue, EEG/MEG Analysis and Signal Processing 2007 13 (2007)
[6]
Frishkoff, G., Le Pendu, P., Frank, R., Liuand, H., Dou, D.: Development of Neural Electromagnetic Ontologies (NEMO): Ontology-based Tools for Representation and Integration of Event-related Brain Potentials In: Proceedings of the International Conference on Biomedical Ontology, ICBO 2009 (2009)
[7]
Keogh, E., Kasetty, S.: On the need for time series data mining benchmarks: A survey and empirical demonstration Data Min Knowl Discov 7(4), 349-371 (2003)
[8]
Wache, H., Vogele, T., Visser, U., Stuckenschmidt, H., Schuster, G., Neumann, H., Hubner, S.: Ontology-based integration of information: A survey of existing approaches In: IJCAI-01 Workshop: Ontologies and Information Sharing, pp 108-117 (2001)
[9]
Dhamankar, R., Lee, Y., Doan, A., Halevy, A.Y., Domingos, P.: iMAP: Discovering Complex Mappings between Database Schemas In: Proceedings of the ACM Conference on Management of Data, pp 383-394 (2004)
[10]
Larson, J., Navathe, S., Elmasri, R.: A theory of attributed equivalence in databases with application to schema integration IEEE Transactions on Software Engineering 15(4), 449-463 (1989)
[11]
Sheth, A., Larson, J., Cornelio, A., Navathe, S.: A tool for integrating conceptual schemas and user views In: Proc 4th International Conference on Data Engineering (ICDE), Los Angeles, CA, US, pp 176-183 (1988)
[12]
Gratton, G., Coles, M.G.H., Donchin, E.: A procedure for using multielectrode information in the analysis of components of the event-related potential: Vector filter Psychophysiology 26(2), 222-232 (1989)
[13]
Spencer, K.M., Dien, J., Donchin, E.: A componential analysis of the ERP elicited by novel events using a dense electrode array Psychophysiology 36, 409-414 (1999)
[14]
Donchin, E., Heffley, E.: Multivariate analysis of event-related potential data: a tutorial review In: Otto, D (ed.) Multidisciplinary Perspectives in Event-Related Brain Potential Research, pp 555-572 U.S Government Printing Office, Washington (1978)
[15]
Picton, T.W., Bentin, S., Berg, P., et al.: Guidelines for using human event-related potentials to study cognition: recording standards and publication criteria Psychophysiology 37(2), 127-152 (2000)
[16]
Li, W., Clifton, C.: Semantic integration in heterogeneous databases using neural networks In: Proc 20th Intl Conf on Very Large Data Bases, pp 1-12 (1994)
[17]
Li, W., Clifton, C.: SemInt: a tool for identifying attribute correspondences in heterogeneous databases using neural network Data Knowl Eng 33(1), 49-84 (2000)
[18]
Rahm, E., Bernstein, P.: A survey of approaches to automatic schema matching The VLDB Journal 10(4), 334-350 (2001)
[19]
Doan, A.H., Domingos, P., Halevy, A.: Reconciling schemas of disparate data sources: a machine-learning approach In: Proc ACM SIGMOD Conf., pp 509-520 (2001)
[20]
LePendu, P., Dou, D., Frishkoff, G., Rong, J.: Ontology Database: A New Method for Semantic Modeling and an Application to Brainwave Data In: Ludäscher, B., Mamoulis, N (eds.) SSDBM 2008 LNCS, vol 5069, pp 313-330 Springer, Heidelberg (2008)
Recommendations
Assessing the Performance of a New Semantic Similarity Measure Designed for Schema Matching for Mediation Systems
Computational Collective IntelligenceAbstractRising adoption of mediation systems leading to plenty of room for improvement. As a matter of fact, schema matching is one of the biggest pressing challenges facing the improvement of mediation systems. The purpose of this research paper is to ...
Semantic web services discovery based on structural ontology matching
In this paper, we present an approach to semantic-based web service discovery and a prototypical tool based on syntactic and structural schema matching. It is based on matching an input ontology, describing a service request, to web services ...
Research on Ontology-Based Measuring Semantic Similarity
ICICSE '08: Proceedings of the 2008 International Conference on Internet Computing in Science and EngineeringOntology is an explicit specification of a conceptualization on semantic and knowledge. This paper presents a formal definition on ontology and gives an example. Then, a method to measuring semantic similarity is presented. Semantic similarity is ...
Comments
Please enable JavaScript to view thecomments powered by Disqus.Information & Contributors
Information
Published In
Sponsors
- AOARD: Asian Office of Aerospace Research and Development
- AFOSR: AFOSR
- ONRGlobal: U.S. Office of Naval Research Global
Publisher
Springer-Verlag
Berlin, Heidelberg
Publication History
Published: 21 June 2010
Author Tags
Qualifiers
- Article
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- View Citations1Total Citations
- 0Total Downloads
- Downloads (Last 12 months)0
- Downloads (Last 6 weeks)0
Reflects downloads up to 30 Nov 2024
Other Metrics
Citations
Cited By
View all- Liu HDou D(2011)Breaking the deadlockProceedings of the 2011th Confederated international conference on On the move to meaningful internet systems - Volume Part II10.5555/2075764.2075794(698-715)Online publication date: 17-Oct-2011