Titlebook: Computational Linguistics and IntelligentText Processing; 20th International C Alexander Gelbukh Conference proceedings 2023 Springer Natur

assail

,?hnlichkeitsgesetze der Str?mungslehre,arsing task. This paper investigates discourse connectives whose position in a text deviates from the usual setting – namely connectives that occur in neither of the two arguments – and as such present a challenge for discourse parsers. We find syntactic patterns for this phenomenon and describe it

抗生素

verdict

,Kinematik der instation?ren Str?mung,s were trained on parts of a large corpus extracted from English Wikipedia (enwik9) which was divided into two equal-sized datasets, from which PMI matrices were obtained. A repeated measures design was used in assigning a method of low-rank approximation (SVD, NMF, QR) and a dimensionality of the v

尖叫

無法治愈

,?hnlichkeitsgesetze der Str?mungslehre,spective. The assumption is that not only cross-lingual similarity can influence the successful word disambiguation in an unknown but related foreign language, but also that predictability in context contributes to better intelligibility of the target items. Experimental data were gathered for 149 P

記憶法

Tailor

,Potentialstr?mung inkompressibler Fluide,ially harmful situations. Although such situations are dangerous, patients usually do not report them to their physicians. Hence, it is necessary to study other sources of information. We propose to study online health fora with information retrieval methods in order to identify messages that contai

faddish

eulogize

,Umstr?mung und Durchstr?mung von K?rpern,cientific literature in order to extract these interactions. We consider this problem as a relation extraction task which can be solved with classification method. Since Food-Drug Interactions need a fine-grained description with many relation types, we face the data sparseness and the lack of examp

樹上結(jié)蜜糖

Wirbelinduzierte Geschwindigkeitsfelder,olarized issues. It proposes a pipeline approach centered around the detection and clustering of phrases, assimilated to argument facets using a novel Phrase Author Interaction Topic-Viewpoint model. The evaluation is based on the informativeness, the relevance and the clustering accuracy of extract