| Full text | |
| Author(s): |
Total Authors: 2
|
| Affiliation: | [1] Univ Sao Paulo, Inst Math & Comp Sci, BR-13560970 Sao Carlos, SP - Brazil
[2] Univ Sao Paulo, Inst Phys Sao Carlos, BR-13560970 Sao Carlos, SP - Brazil
Total Affiliations: 2
|
| Document type: | Journal article |
| Source: | European Physical Journal B; v. 86, n. 7 JUL 2013. |
| Web of Science Citations: | 2 |
| Abstract | |
Patterns of topological arrangement are widely used for both animal and human brains in the learning process. Nevertheless, automatic learning techniques frequently overlook these patterns. In this paper, we apply a learning technique based on the structural organization of the data in the attribute space to the problem of discriminating the senses of 10 polysemous words. Using two types of characterization of meanings, namely semantical and topological approaches, we have observed significative accuracy rates in identifying the suitable meanings in both techniques. Most importantly, we have found that the characterization based on the deterministic tourist walk improves the disambiguation process when one compares with the discrimination achieved with traditional complex networks measurements such as assortativity and clustering coefficient. To our knowledge, this is the first time that such deterministic walk has been applied to such a kind of problem. Therefore, our finding suggests that the tourist walk characterization may be useful in other related applications. (AU) | |
| FAPESP's process: | 10/00927-9 - Using complex networks to classify texts |
| Grantee: | Diego Raphael Amancio |
| Support Opportunities: | Scholarships in Brazil - Doctorate (Direct) |
| FAPESP's process: | 09/12329-1 - Error propagation analysis in complex network based on semi-supervised learning |
| Grantee: | Thiago Christiano Silva |
| Support Opportunities: | Scholarships in Brazil - Doctorate (Direct) |