Name
Abstract | ||
|---|---|---|
This paper describes the construction methodology of a network of natural terms hierarchy based on the analysis of a homogeneous or heterogeneous text corpus. It also presents a criterion for the evaluation of paper relevance to a particular scientific conference. The proposed method is illustrated by the examples from the heterogeneous corpus of the STIDS 2013 conference proceedings. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/MICAI.2014.9 | 2014 13th Mexican International Conference on Artificial Intelligence |
Keywords | Field | DocType |
language network,compactified horizontal visibility graph,term hierarchy,scientific trend | Lightweight ontology,Ontology (information science),Data modeling,Homogeneous,Computer science,Text corpus,Artificial intelligence,Hierarchy,Big data,Semantics,Machine learning | Conference |
ISBN | Citations | PageRank |
978-1-4673-7010-3 | 0 | 0.34 |
References | Authors | |
8 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Dmitry V. Lande | 1 | 1 | 3.67 |
| Andrey Snarskii | 2 | 0 | 1.01 |
| Elena Yagunova | 3 | 3 | 5.18 |
| Ekaterina Pronoza | 4 | 0 | 2.70 |
| Svetlana Volskaya | 5 | 0 | 0.68 |