TY - RPRT U1 - Arbeitspapier A1 - Wartena, Christian T1 - Distributional Similarity of Words with Different Frequencies N2 - Distributional semantics tries to characterize the meaning of words by the contexts in which they occur. Similarity of words hence can be derived from the similarity of contexts. Contexts of a word are usually vectors of words appearing near to that word in a corpus. It was observed in previous research that similarity measures for the context vectors of two words depend on the frequency of these words. In the present paper we investigate this dependency in more detail for one similarity measure, the Jensen-Shannon divergence. We give an empirical model of this dependency and propose the deviation of the observed Jensen-Shannon divergence from the divergence expected on the basis of the frequencies of the words as an alternative similarity measure. We show that this new similarity measure is superior to both the Jensen-Shannon divergence and the cosine similarity in a task, in which pairs of words, taken from Wordnet, have to be classified as being synonyms or not. KW - Synonymie KW - Semantik KW - Computerlinguistik KW - Linguistische Informationswissenschaft KW - Korpus KW - Distributionelle Semantik KW - Distributional Semantics Y1 - 2013 UN - https://nbn-resolving.org/urn:nbn:de:bsz:960-opus-4077 U6 - https://doi.org/10.25968/opus-335 DO - https://doi.org/10.25968/opus-335 ER -