engleski

Distributional Semantics Approach to Detecting Synonyms in Croatian Language

Identifying synonyms is important for many natural language processing and information retrieval applications. In this paper we address the task of automatically identifying synonyms in Croatian language using distributional semantic models (DSM). We build several DSMs using latent semantic analysis (LSA) and random indexing (RI) on the large hrWaC corpus. We evaluate the models on a dictionarybased similarity test – a set of synonymy questions generated automatically from a machine readable dictionary. Results indicate that LSA models outperform RI models on this task, with accuracy of 68.7%, 68.2%, and 61.6% on nouns, adjectives, and verbs, respectively. We analyze how word frequency and polysemy level affect the performance and discuss common causes of synonym misidentification.

Named Entities ; Extraction ; Classification

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