
doi: 10.1007/11846406_12
In this paper we describe in detail two dependency parsing techniques developed and evaluated using the Prague Dependency Treebank 2.0 Then we propose two approaches for combining various existing parsers in order to obtain better accuracy The highest parsing accuracy reported in this paper is 85.84 %, which represents 1.86 % improvement compared to the best single state-of-the-art parser To our knowledge, no better result achieved on the same data has been published yet.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 7 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
