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Word embeddings are one of the most fundamental technologies used in naturallanguage processing. Existing word embeddings are high-dimensional and consumeconsiderable computational resources. In this study, we propose WordTour,unsupervised one-dimensional word embeddings. To achieve the challenging goal,we propose a decomposition of the desiderata of word embeddings into two parts,completeness and soundness, and focus on soundness in this paper. Owing to thesingle dimensionality, WordTour is extremely efficient and provides a minimalmeans to handle word embeddings. We experimentally confirmed the effectivenessof the proposed method via user study and document classification.

Word Tour: One-dimensional Word Embeddings via the Traveling Salesman Problem