970 citations · 1.7k across the 49 of their papers we have counts for
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RelWalk A Latent Variable Model Approach to Knowledge Graph Embedding
Danushka Bollegala, Huda Hakami, Yuichi Yoshida +1
Embedding entities and relations of a knowledge graph in a low-dimensional space has shown impressive performance in predicting missing links between entities. Although progresses…
Query Obfuscation Semantic Decomposition
Danushka Bollegala, Tomoya Machide, Ken-ichi Kawarabayashi
We propose a method to protect the privacy of search engine users by decomposing the queries using semantically \emph{related} and unrelated \emph{distractor} terms. Instead of a s…
Are Girls Neko or Shōjo? Cross-Lingual Alignment of Non-Isomorphic Embeddings with Iterative Normalization
Mozhi Zhang, Keyulu Xu, Ken-ichi Kawarabayashi +2
Cross-lingual word embeddings (CLWE) underlie many multilingual natural language processing systems, often through orthogonal transformations of pre-trained monolingual embeddings.…
ClassiNet -- Predicting Missing Features for Short-Text Classification
Danushka Bollegala, Vincent Atanasov, Takanori Maehara +1
The fundamental problem in short-text classification is \emph{feature sparseness} -- the lack of feature overlap between a trained model and a test instance to be classified. We pr…
Think Globally, Embed Locally --- Locally Linear Meta-embedding of Words
Danushka Bollegala, Kohei Hayashi, Ken-ichi Kawarabayashi
Distributed word embeddings have shown superior performances in numerous Natural Language Processing (NLP) tasks. However, their performances vary significantly across different ta…
Using -way Co-occurrences for Learning Word Embeddings
Danushka Bollegala, Yuichi Yoshida, Ken-ichi Kawarabayashi
Co-occurrences between two words provide useful insights into the semantics of those words. Consequently, numerous prior work on word embedding learning have used co-occurrences be…