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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Page: 1 2 3 Hits 1 – 20 of 44 1 Learning to Borrow -- Relation Representation for Without-Mention Entity-Pairs for Knowledge Graph Completion ... Hakami, Huda; Hakami, Mona; Mandya, Angrosh; Bollegala, Danushka. - : arXiv, 2022 Abstract: Prior work on integrating text corpora with knowledge graphs (KGs) to improve Knowledge Graph Embedding (KGE) have obtained good performance for entities that co-occur in sentences in text corpora. Such sentences (textual mentions of entity-pairs) are represented as Lexicalised Dependency Paths (LDPs) between two entities. However, it is not possible to represent relations between entities that do not co-occur in a single sentence using LDPs. In this paper, we propose and evaluate several methods to address this problem, where we borrow LDPs from the entity pairs that co-occur in sentences in the corpus (i.e. with mention entity pairs) to represent entity pairs that do not co-occur in any sentence in the corpus (i.e. without mention entity pairs). We propose a supervised borrowing method, SuperBorrow, that learns to score the suitability of an LDP to represent a without-mention entity pair using pre-trained entity embeddings and contextualised LDP representations. Experimental results show that SuperBorrow ... : Accepted in NAACL 2022 ... Keyword: Computation and Language cs.CL; FOS Computer and information sciences URL: https://arxiv.org/abs/2204.13097 https://dx.doi.org/10.48550/arxiv.2204.13097 BASE Hide details 2 Learning Meta Word Embeddings by Unsupervised Weighted Concatenation of Source Embeddings ... Bollegala, Danushka. - : arXiv, 2022 BASE Show details 3 Sense Embeddings are also Biased--Evaluating Social Biases in Static and Contextualised Sense Embeddings Kaneko, Masahiro; Zhou, Yi; Bollegala, Danushka. - 2022 BASE Show details 4 I Wish I Would Have Loved This One, But I Didn't -- A Multilingual Dataset for Counterfactual Detection in Product Reviews ... O'Neill, James; Rozenshtein, Polina; Kiryo, Ryuichi. - : arXiv, 2021 BASE Show details 5 Detect and Classify – Joint Span Detection and Classification for Health Outcomes ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Abaho, Micheal; Bollegala, Danushka. - : Underline Science Inc., 2021 BASE Show details 6 Unsupervised Abstractive Opinion Summarization by Generating Sentences with Tree-Structured Topic Guidance ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Bollegala, Danushka; Isonuma, Masaru. - : Underline Science Inc., 2021 BASE Show details 7 Fine-Tuning Word Embeddings for Hierarchical Representation of Data Using a Corpus and a Knowledge Base for Various Machine Learning Applications Alsuhaibani, Mohammed; Bollegala, Danushka In: Comput Math Methods Med (2021) BASE Show details 8 RelWalk - A Latent Variable Model Approach to Knowledge Graph Embedding. Bollegala, Danushka; Kawarabayashi, Ken-ichi; Yoshida, Yuichi. - : Association for Computational Linguistics, 2021 BASE Show details 9 Dictionary-based Debiasing of Pre-trained Word Embeddings. Bollegala, Danushka; Kaneko, Masahiro. - : Association for Computational Linguistics, 2021 BASE Show details 10 Unsupervised Abstractive Opinion Summarization by Generating Sentences with Tree-Structured Topic Guidance Sakata, Ichiro; Mori, Junichiro; Bollegala, Danushka. - : Massachusetts Institute of Technology Press, 2021 BASE Show details 11 Unsupervised Abstractive Opinion Summarization by Generating Sentences with Tree-Structured Topic Guidance Bollegala, Danushka; Isonuma, Masaru; Mori, Junichiro. - 2021 BASE Show details 12 Debiasing Pre-trained Contextualised Embeddings. Kaneko, Masahiro; Bollegala, Danushka. - : Association for Computational Linguistics, 2021 BASE Show details 13 Autoencoding Improves Pre-trained Word Embeddings ... Kaneko, Masahiro; Bollegala, Danushka. - : arXiv, 2020 BASE Show details 14 Autoencoding Improves Pre-trained Word Embeddings ... The 28th International Conference on Computational Linguistics 2020; Bollegala, Danushka; Kaneko, Masahiro. - : Underline Science Inc., 2020 BASE Show details 15 Graph Convolution over Multiple Dependency Sub-graphs for Relation Extraction ... The 28th International Conference on Computational Linguistics 2020; Bollegala, Danushka; Coenen, Frans. - : Underline Science Inc., 2020 BASE Show details 16 Language-Independent Tokenisation Rivals Language-Specific Tokenisation for Word Similarity Prediction ... Bollegala, Danushka; Kiryo, Ryuichi; Tsujino, Kosuke. - : arXiv, 2020 BASE Show details 17 Graph Convolution over Multiple Dependency Sub-graphs for Relation Extraction. Mandya, Angrosh; Coenen, Frans; Bollegala, Danushka. - : International Committee on Computational Linguistics, 2020 BASE Show details 18 Multi-Source Attention for Unsupervised Domain Adaptation. Bollegala, Danushka; Cui, Xia. - : Association for Computational Linguistics, 2020 BASE Show details 19 Learning to Compose Relational Embeddings in Knowledge Graphs Hakami, Huda; Chen, Wenye; Bollegala, Danushka. - : Springer Singapore, 2020 BASE Show details 20 Tree-Structured Neural Topic Model Isonuma, Masaru; Mori, Junichiro; Bollegala, Danushka. - 2020 BASE Show details Page: 1 2 3

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