Assessing Concept Novelty Potential with Lexical and Distributional Word Similarity for Innovative Design

Directional distributional similarity for lexical inference

Distributional word similarity is most commonly perceived as a symmetric relation. Yet, directional relations are abundant in lexical semantics and in many Natural Language Processing (NLP) settings that require lexical inference, making symmetric similarity measures less suitable for their identification. This paper investigates the nature of directional (asymmetric) similarity measures that a...

Directional Distributional Similarity for Lexical Expansion

Distributional word similarity is most commonly perceived as a symmetric relation. Yet, one of its major applications is lexical expansion, which is generally asymmetric. This paper investigates the nature of directional (asymmetric) similarity measures, which aim to quantify distributional feature inclusion. We identify desired properties of such measures, specify a particular one based on ave...

Measures and applications of lexical distributional similarity

Characterising Measures of Lexical Distributional Similarity

This work investigates the variation in a word’s distributionally nearest neighbours with respect to the similarity measure used. We identify one type of variation as being the relative frequency of the neighbour words with respect to the frequency of the target word. We then demonstrate a three-way connection between relative frequency of similar words, a concept of distributional gnerality an...

Using Distributional Similarity for Lexical Expansion in Knowledge-based Word Sense Disambiguation

We explore the contribution of distributional information for purely knowledge-based word sense disambiguation. Specifically, we use a distributional thesaurus, computed from a large parsed corpus, for lexical expansion of context and sense information. This bridges the lexical gap that is seen as the major obstacle for word overlap–based approaches. We apply this mechanism to two traditional k...