Name
Abstract | ||
|---|---|---|
Methods for mining graph sequences have recently attracted considerable interest from researchers in the data-mining field. A graph sequence is one of the data structures that represent changing networks. The objective of graph sequence mining is to enumerate common changing patterns appearing more frequently than a given threshold from graph sequences. Syntactic dependency analysis has been recognized as a basic process in natural language processing. In a transition-based parser for dependency analysis, a transition sequence can be represented by a graph sequence where each graph, vertex, and edge respectively correspond to a state, word, and dependency. In this paper, we propose a method for mining rules for rewriting states reaching incorrect final states to states reaching the correct final state, and propose a dependency parser that uses rewriting rules. The proposed parser is comparable to conventional dependency parsers in terms of computational complexity. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1007/978-3-642-32695-0_14 | PRICAI |
Keywords | Field | DocType |
transition-based dependency parser,mining graph sequence,syntactic dependency analysis,dependency analysis,conventional dependency parsers,graph sequence,proposed parser,dependency parser,graph sequence mining,mining rule,transition sequence | Computer science,Join dependency,Dependency grammar,GLR parser,Null graph,Natural language processing,Graph rewriting,Artificial intelligence,Parsing,Dependency graph,Graph (abstract data type) | Conference |
Citations | PageRank | References |
1 | 0.35 | 17 |
Authors | ||
7 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Akihiro Inokuchi | 1 | 1262 | 101.77 |
| Ayumu Yamaoka | 2 | 2 | 0.73 |
| Takashi Washio | 3 | 1775 | 190.58 |
| yuji matsumoto | 4 | 3008 | 300.05 |
| Masayuki ASAHARA | 5 | 420 | 42.78 |
| Masakazu Iwatate | 6 | 19 | 2.82 |
| Hideto Kazawa | 7 | 709 | 37.48 |