Name
Abstract | ||
|---|---|---|
The aim of this paper is to introduce a system able to configure an automatic answer from a proposed question and summarize information from a causal graph. This procedure has three main steps. The first one is focused in the extraction, filtering and selection of those causal sentences that could have relevant information for the system. The second one is focused in the composition of a suitable causal graph, removing redundant information and solving ambiguity problems. The third step is a procedure able to read the causal graph to compose a suitable answer to a proposed causal question by summarizing the information contained in it. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1007/978-3-319-19719-7_31 | 10TH INTERNATIONAL CONFERENCE ON SOFT COMPUTING MODELS IN INDUSTRIAL AND ENVIRONMENTAL APPLICATIONS |
Keywords | Field | DocType |
Causal questions,Causality,Causal sentences,Causal representation,Causal summarization | Graph,Causality,Computer science,Filter (signal processing),Natural language processing,Artificial intelligence,Ambiguity | Conference |
Volume | ISSN | Citations |
368 | 2194-5357 | 0 |
PageRank | References | Authors |
0.34 | 4 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Cristina Puente | 1 | 19 | 5.60 |
| Alejandro Sobrino | 2 | 30 | 9.59 |
| E. Garrido | 3 | 10 | 2.27 |
| José Angel Olivas | 4 | 65 | 12.87 |