Efficient Sampling of Dependency Structure

Kód výsledku v IS VaVaI

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Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Efficient Sampling of Dependency Structure

Popis výsledku v původním jazyce

Probabilistic distributions over spanning trees in directed graphs are a fundamental model of dependency structure in natural language processing, syntactic dependency trees. In NLP, dependency trees often have an additional root constraint: only one edge may emanate from the root. However, no sampling algorithm has been presented in the literature to account for this additional constraint. In this paper, we adapt two spanning tree sampling algorithms to faithfully sample dependency trees from a graph subject to the root constraint. Wilson (1996(&apos;s sampling algorithm has a running time of O(H) where H is the mean hitting time of the graph. Colbourn (1996)&apos;s sampling algorithm has a running time of O(N^3), which is often greater than the mean hitting time of a directed graph. Additionally, we build upon Colbourn&apos;s algorithm and present a novel extension that can sample K trees without replacement in O(K N^3 + K^2 N) time. To the best of our knowledge, no algorithm has been given for sampling spanning trees without replacement from a directed graph.

Název v anglickém jazyce

Efficient Sampling of Dependency Structure

Popis výsledku anglicky

Probabilistic distributions over spanning trees in directed graphs are a fundamental model of dependency structure in natural language processing, syntactic dependency trees. In NLP, dependency trees often have an additional root constraint: only one edge may emanate from the root. However, no sampling algorithm has been presented in the literature to account for this additional constraint. In this paper, we adapt two spanning tree sampling algorithms to faithfully sample dependency trees from a graph subject to the root constraint. Wilson (1996(&apos;s sampling algorithm has a running time of O(H) where H is the mean hitting time of the graph. Colbourn (1996)&apos;s sampling algorithm has a running time of O(N^3), which is often greater than the mean hitting time of a directed graph. Additionally, we build upon Colbourn&apos;s algorithm and present a novel extension that can sample K trees without replacement in O(K N^3 + K^2 N) time. To the best of our knowledge, no algorithm has been given for sampling spanning trees without replacement from a directed graph.

Druh

D - Stať ve sborníku

CEP obor

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OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

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Návaznosti

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Rok uplatnění

2021

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing

ISBN

978-1-955917-09-4

ISSN

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e-ISSN

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Počet stran výsledku

12

Strana od-do

10558-10569

Název nakladatele

Association for Computational Linguistics

Místo vydání

Stroudsburg

Místo konání akce

Punta Cana

Datum konání akce

7. 11. 2021

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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