Attributes | Values |
---|
rdf:type
| |
rdfs:seeAlso
| |
Description
| - Dependency parsing has made many advancements in recent years, in particular for English. There are a few dependency parsers that achieve comparable accuracy scores with each other but with very different types of errors. This paper examines creating a new dependency structure through ensemble learning using a hybrid of the outputs of various parsers. We combine all tree outputs into a weighted edge graph, using 4 weighting mechanisms. The weighted edge graph is the input into our ensemble system and is a hybrid of very different parsing techniques (constituent parsers, transition-based dependency parsers, and a graph-based parser). From this graph we take a maximum spanning tree. We examine the new dependency structure in terms of accuracy and errors on individual part-of-speech values. The results indicate that using a greater number of more varied parsers will improve accuracy results. The combined ensemble system, using 5 parsers based on 3 different parsing techniques, achieves an accuracy score
- Dependency parsing has made many advancements in recent years, in particular for English. There are a few dependency parsers that achieve comparable accuracy scores with each other but with very different types of errors. This paper examines creating a new dependency structure through ensemble learning using a hybrid of the outputs of various parsers. We combine all tree outputs into a weighted edge graph, using 4 weighting mechanisms. The weighted edge graph is the input into our ensemble system and is a hybrid of very different parsing techniques (constituent parsers, transition-based dependency parsers, and a graph-based parser). From this graph we take a maximum spanning tree. We examine the new dependency structure in terms of accuracy and errors on individual part-of-speech values. The results indicate that using a greater number of more varied parsers will improve accuracy results. The combined ensemble system, using 5 parsers based on 3 different parsing techniques, achieves an accuracy score (en)
|
Title
| - Hybrid Combination of Constituency and Dependency Trees into an Ensemble Dependency Parser
- Hybrid Combination of Constituency and Dependency Trees into an Ensemble Dependency Parser (en)
|
skos:prefLabel
| - Hybrid Combination of Constituency and Dependency Trees into an Ensemble Dependency Parser
- Hybrid Combination of Constituency and Dependency Trees into an Ensemble Dependency Parser (en)
|
skos:notation
| - RIV/00216208:11320/12:10130050!RIV13-MSM-11320___
|
http://linked.open...avai/riv/aktivita
| |
http://linked.open...avai/riv/aktivity
| |
http://linked.open...vai/riv/dodaniDat
| |
http://linked.open...aciTvurceVysledku
| |
http://linked.open.../riv/druhVysledku
| |
http://linked.open...iv/duvernostUdaju
| |
http://linked.open...titaPredkladatele
| |
http://linked.open...dnocenehoVysledku
| |
http://linked.open...ai/riv/idVysledku
| - RIV/00216208:11320/12:10130050
|
http://linked.open...riv/jazykVysledku
| |
http://linked.open.../riv/klicovaSlova
| - parser; dependency; ensemble; into; trees; dependency; constituency; combination; hybrid (en)
|
http://linked.open.../riv/klicoveSlovo
| |
http://linked.open...ontrolniKodProRIV
| |
http://linked.open...v/mistoKonaniAkce
| |
http://linked.open...i/riv/mistoVydani
| |
http://linked.open...i/riv/nazevZdroje
| - Proceedings of the Workshop on Innovative Hybrid Approaches to the Processing of Textual Data
|
http://linked.open...in/vavai/riv/obor
| |
http://linked.open...ichTvurcuVysledku
| |
http://linked.open...cetTvurcuVysledku
| |
http://linked.open...UplatneniVysledku
| |
http://linked.open...iv/tvurceVysledku
| - Žabokrtský, Zdeněk
- Green, Nathan David
|
http://linked.open...vavai/riv/typAkce
| |
http://linked.open.../riv/zahajeniAkce
| |
number of pages
| |
http://purl.org/ne...btex#hasPublisher
| - Association for Computational Linguistics
|
https://schema.org/isbn
| |
http://localhost/t...ganizacniJednotka
| |