Search Results for author: Lina Rojas-Barahona

Found 15 papers, 2 papers with code

Hyperbolic Temporal Knowledge Graph Embeddings with Relational and Time Curvatures

no code implementations Findings (ACL) 2021 Sebastien Montella, Lina Rojas-Barahona, Johannes Heinecke

We further propose Hercules, a time-aware extension of AttH model, which defines the curvature of a Riemannian manifold as the product of both relation and time.

Knowledge Graph Embeddings Link Prediction

Addressing Objects and Their Relations: The Conversational Entity Dialogue Model

no code implementations WS 2018 Stefan Ultes, Paweł\ Budzianowski, Iñigo Casanueva, Lina Rojas-Barahona, Bo-Hsiang Tseng, Yen-chen Wu, Steve Young, Milica Gašić

Statistical spoken dialogue systems usually rely on a single- or multi-domain dialogue model that is restricted in its capabilities of modelling complex dialogue structures, e. g., relations.

Spoken Dialogue Systems

Deep learning for language understanding of mental health concepts derived from Cognitive Behavioural Therapy

1 code implementation WS 2018 Lina Rojas-Barahona, Bo-Hsiang Tseng, Yinpei Dai, Clare Mansfield, Osman Ramadan, Stefan Ultes, Michael Crawford, Milica Gasic

In recent years, we have seen deep learning and distributed representations of words and sentences make impact on a number of natural language processing tasks, such as similarity, entailment and sentiment analysis.

Sentence Embeddings Sentiment Analysis +1

Counter-fitting Word Vectors to Linguistic Constraints

2 code implementations NAACL 2016 Nikola Mrkšić, Diarmuid Ó Séaghdha, Blaise Thomson, Milica Gašić, Lina Rojas-Barahona, Pei-Hao Su, David Vandyke, Tsung-Hsien Wen, Steve Young

In this work, we present a novel counter-fitting method which injects antonymy and synonymy constraints into vector space representations in order to improve the vectors' capability for judging semantic similarity.

Dialogue State Tracking Semantic Similarity +1

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