1996/01/23 by Hideki Kozima, Akira Itô, Kozima, Hideki +1 · 1 citation
Computer Science · #Advanced Text Analysis Techniques #Computation and Language (cs.CL) #FOS: Computer and information sciences #Speech and dialogue systems #Topic Modeling
paper · pdf · doi:10.48550/arxiv.cmp-lg/9601007
openalex publication_date 1996/01/23 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
The paper proposes a computationally feasible method for measuring context-sensitive semantic distance between words. The distance is computed by adaptive scaling of a semantic space. In the semantic space, each word in the vocabulary V is represented by a multi-dimensional vector which is obtained from an English dictionary through a principal component analysis. Given a word set C which specifies a context for measuring word distance, each dimension of the semantic space is scaled up or down according to the distribution of C in the semantic space. In the space thus transformed, distance between words in V becomes dependent on the context C. An evaluation through a word prediction task shows that the proposed measurement successfully extracts the context of a text.