Associative Word Relations in Natural Language Processing

Abstract

Motivation for this work comes from the longest-running Serbian television quiz show called TV Slagalica and more specifically from one of its games named associations. In the associations game, two players attempt to guess a solution given several clue words. There is a large number of publicly available game scenarios that were used to evaluate applicability of trained artificial neural networks to predict possible solutions. Material used for the network training was obtained through unconventional sources as no professional text corpus exists for Serbian language. Under outlined schemes, it is observed that solution words come up within 2% or less of the training vocabulary, depending on the method of data preparation. Data preparation and neural network training specifics are further outlined to demonstrate effects of each technique used. Even though the results obtained are below human-level performance, they can nevertheless be useful for puzzle creation.