Name
Abstract | ||
|---|---|---|
Authorship attribution is the task of determining the real author of a given anonymous document. Even though different approaches exist in literature, this problem has been barely dealt with by using document representations that employ graph structures. Actually, most research works in literature handle this problem by employing simple sequences of n words (n-grams), such as bigrams and trigrams. In this paper, an exploration in the use of graphs for representing document sentences is presented. These structures are used for carrying out experiments for solving the problem of Authorship attribution. The experiments that are presented here attain approximately a 79% of accuracy, showing that the graph-based representation could be a way of encapsulating various levels of natural language descriptions in a simple structure. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1109/CONIELECOMP.2015.7086940 | CONIELECOMP |
Field | DocType | Citations |
Graph,Computer science,Trigram,Attribution,Natural language,Artificial intelligence,Natural language processing,Bigram | Conference | 1 |
PageRank | References | Authors |
0.35 | 11 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Esteban Castillo | 1 | 19 | 6.58 |
| Darnes Vilariño Ayala | 2 | 21 | 10.84 |
| Ofelia Cervantes | 3 | 24 | 7.28 |
| David Pinto | 4 | 9 | 1.57 |