Commenced in January 2007
Paper Count: 31529
Analyzing Multi-Labeled Data Based on the Roll of a Concept against a Semantic Range
Abstract:Classifying data hierarchically is an efficient approach to analyze data. Data is usually classified into multiple categories, or annotated with a set of labels. To analyze multi-labeled data, such data must be specified by giving a set of labels as a semantic range. There are some certain purposes to analyze data. This paper shows which multi-labeled data should be the target to be analyzed for those purposes, and discusses the role of a label against a set of labels by investigating the change when a label is added to the set of labels. These discussions give the methods for the advanced analysis of multi-labeled data, which are based on the role of a label against a semantic range.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1073229Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 956
 Bertino, E., Fan, J., Ferrari, E., Hachi, M., and Elamagarmid, A.: A Hierarchical Access Control Model for Video Database Systems, ACM Transactions on Information Systems, Vol. 21, No. 2, pp. 151-191 (2003).
 Chakrabarti, K., Ganti, V., Han, J., and Xin, D.: Rankig Objects by Exploiting, Relationships: Computing Top-K over Aggregation, Proc. ACM SIGMOD Int-l Conf. on Management of Data, pp. 371-382 (2006).
 Furukawa, T. and Kuzunishi, M.: Hierarchical Classification of Heterogeneous Data, Proc. IASTED Int-l Conf. on Databases and Applications (DBA2005), pp. 252-257 (2005).
 Furukawa, T. and Kuzunishi, M.: "Multi-labeled Data Expressed by a Set of Labels", Proc. World Academy of Science, Engineering and Technology, Vol. 65, pp. 857-863 (2010).
 Ghamrawi, N. and McMallum, A.: Collecticve Multi-Label Classification, Proc. Int-l Conf. on Information and Knowledge Management (CIKM-05), pp. 195-200 (2005).
 Kuzunishi, M. and Furukawa, T.: Representation for Multiple Classified Data, Proc. IASTED Int-l Conf. on Databases and Applications (DBA2006), pp. 135-142 (2006).
 Silva, A. and Barbosa, D: Labeling Data Extracted from the Web, Proc. On The Move to Meaningful Internet Systems 2007: CoopIS, DOA, and ODBASE, pp. 1099-1116 (2007).
 Sun, A. and Lim, E.: Hierarchical Text Classification and Evaluation, Proc. IEEE Int-l Conf. on Data Mining (ICDM2001), pp. 521-528 (2001).
 Toutanova, K., Chen, F., Popat K., and Hofmann, T.: Text Classification in a Hierarchical Mixture Model for Small Training Sets, Proc. Int-l Conf. on Information and Knowledge Management (CIKM-01), pp. 105- 112 (2001).
 Wang, K., Zhou, S., and He, Y.: Hierarchical Classification of Real Life Documents, Proc. SIAM Int-l Conf. on Data Mining, pp. 1-16 (2001).
 Wang, K., Zhou, S., and Liew, S. C.: Building Hierarchical Classifiers Using Class Proximity, Proc. Int-l Conf. on Very Large Data Bases (VLDB-99), pp. 363-374 (1999).