Matches in SemOpenAlex for { <https://semopenalex.org/work/W2890924154> ?p ?o ?g. }
- W2890924154 abstract "Argument mining is a core technology for automating argument search in large document collections. Despite its usefulness for this task, most current approaches are designed for use only with specific text types and fall short when applied to heterogeneous texts. In this paper, we propose a new sentential annotation scheme that is reliably applicable by crowd workers to arbitrary Web texts. We source annotations for over 25,000 instances covering eight controversial topics. We show that integrating topic information into bidirectional long short-term memory networks outperforms vanilla BiLSTMs by more than 3 percentage points in F1 in two- and three-label cross-topic settings. We also show that these results can be further improved by leveraging additional data for topic relevance using multi-task learning." @default.
- W2890924154 created "2018-09-27" @default.
- W2890924154 creator A5027450194 @default.
- W2890924154 creator A5036941456 @default.
- W2890924154 creator A5038798618 @default.
- W2890924154 creator A5085860502 @default.
- W2890924154 creator A5086551373 @default.
- W2890924154 date "2018-01-01" @default.
- W2890924154 modified "2023-10-16" @default.
- W2890924154 title "Cross-topic Argument Mining from Heterogeneous Sources" @default.
- W2890924154 cites W1136076469 @default.
- W2890924154 cites W1544827683 @default.
- W2890924154 cites W2019842155 @default.
- W2890924154 cites W2060622042 @default.
- W2890924154 cites W2064675550 @default.
- W2890924154 cites W2086109875 @default.
- W2890924154 cites W2095705004 @default.
- W2890924154 cites W2097794246 @default.
- W2890924154 cites W2100649405 @default.
- W2890924154 cites W2110267514 @default.
- W2890924154 cites W2118463056 @default.
- W2890924154 cites W2123442489 @default.
- W2890924154 cites W2144232471 @default.
- W2890924154 cites W2153579005 @default.
- W2890924154 cites W2153804780 @default.
- W2890924154 cites W2165698076 @default.
- W2890924154 cites W2250309026 @default.
- W2890924154 cites W2250762536 @default.
- W2890924154 cites W2251647857 @default.
- W2890924154 cites W2251818274 @default.
- W2890924154 cites W2275625487 @default.
- W2890924154 cites W2343649478 @default.
- W2890924154 cites W2395678543 @default.
- W2890924154 cites W2460159515 @default.
- W2890924154 cites W2466330544 @default.
- W2890924154 cites W2513522653 @default.
- W2890924154 cites W2607158754 @default.
- W2890924154 cites W2758824081 @default.
- W2890924154 cites W2759858869 @default.
- W2890924154 cites W2807405475 @default.
- W2890924154 cites W2889059840 @default.
- W2890924154 cites W2962878247 @default.
- W2890924154 cites W2962897020 @default.
- W2890924154 cites W2963355640 @default.
- W2890924154 cites W2963542836 @default.
- W2890924154 cites W2963591087 @default.
- W2890924154 cites W2963940534 @default.
- W2890924154 cites W2964116507 @default.
- W2890924154 cites W2964121744 @default.
- W2890924154 cites W2964308564 @default.
- W2890924154 cites W329130461 @default.
- W2890924154 doi "https://doi.org/10.18653/v1/d18-1402" @default.
- W2890924154 hasPublicationYear "2018" @default.
- W2890924154 type Work @default.
- W2890924154 sameAs 2890924154 @default.
- W2890924154 citedByCount "76" @default.
- W2890924154 countsByYear W28909241542019 @default.
- W2890924154 countsByYear W28909241542020 @default.
- W2890924154 countsByYear W28909241542021 @default.
- W2890924154 countsByYear W28909241542022 @default.
- W2890924154 countsByYear W28909241542023 @default.
- W2890924154 crossrefType "proceedings-article" @default.
- W2890924154 hasAuthorship W2890924154A5027450194 @default.
- W2890924154 hasAuthorship W2890924154A5036941456 @default.
- W2890924154 hasAuthorship W2890924154A5038798618 @default.
- W2890924154 hasAuthorship W2890924154A5085860502 @default.
- W2890924154 hasAuthorship W2890924154A5086551373 @default.
- W2890924154 hasBestOaLocation W28909241541 @default.
- W2890924154 hasConcept C134306372 @default.
- W2890924154 hasConcept C154945302 @default.
- W2890924154 hasConcept C158154518 @default.
- W2890924154 hasConcept C162324750 @default.
- W2890924154 hasConcept C17744445 @default.
- W2890924154 hasConcept C185592680 @default.
- W2890924154 hasConcept C187736073 @default.
- W2890924154 hasConcept C199539241 @default.
- W2890924154 hasConcept C204321447 @default.
- W2890924154 hasConcept C23123220 @default.
- W2890924154 hasConcept C2522767166 @default.
- W2890924154 hasConcept C2776321320 @default.
- W2890924154 hasConcept C2780451532 @default.
- W2890924154 hasConcept C33923547 @default.
- W2890924154 hasConcept C41008148 @default.
- W2890924154 hasConcept C55493867 @default.
- W2890924154 hasConcept C77618280 @default.
- W2890924154 hasConcept C98184364 @default.
- W2890924154 hasConceptScore W2890924154C134306372 @default.
- W2890924154 hasConceptScore W2890924154C154945302 @default.
- W2890924154 hasConceptScore W2890924154C158154518 @default.
- W2890924154 hasConceptScore W2890924154C162324750 @default.
- W2890924154 hasConceptScore W2890924154C17744445 @default.
- W2890924154 hasConceptScore W2890924154C185592680 @default.
- W2890924154 hasConceptScore W2890924154C187736073 @default.
- W2890924154 hasConceptScore W2890924154C199539241 @default.
- W2890924154 hasConceptScore W2890924154C204321447 @default.
- W2890924154 hasConceptScore W2890924154C23123220 @default.
- W2890924154 hasConceptScore W2890924154C2522767166 @default.
- W2890924154 hasConceptScore W2890924154C2776321320 @default.
- W2890924154 hasConceptScore W2890924154C2780451532 @default.
- W2890924154 hasConceptScore W2890924154C33923547 @default.