In this paper we propose a system to solve a language game, called Guillotine, which requires a player with a strong cultural and linguistic background knowledge. The player observes a set of five words, generally unrelated to each other, and in one minute she has to provide a sixth word, semantically connected to the others. Several knowledge sources, such as a dictionary and a set of proverbs, have been modeled and integrated in order to realize a knowledge infusion process into the system. The main motivation for designing an artificial player for Guillotine is the challenge of providing the machine with the cultural and linguistic background knowledge which makes it similar to a human being, with the ability of interpreting natural language documents and reasoning on their content. Experiments carried out showed promising results, and both the knowledge source modeling and the reasoning mechanisms (implementing a spreading activation algorithm to find out the solution) seem to be appropriate. We are convinced that the approach has a great potential for other more practical applications besides solving a language game, such as semantic search.

On the Tip of my Thought: Playing the Guillotine Game / SEMERARO G.; LOPS P.; P. BASILE; M. DEGEMMIS. - In: IJCAI. - ISSN 1045-0823. - (2009), pp. 1543-1548. ((Intervento presentato al convegno Twenty-first International Joint Conference on Artificial Intelligence IJCAI-09 tenutosi a Pasadena, California nel July 11-17, 2009.

On the Tip of my Thought: Playing the Guillotine Game

SEMERARO, Giovanni;LOPS, PASQUALE;BASILE, PIERPAOLO;DEGEMMIS, MARCO
2009

Abstract

In this paper we propose a system to solve a language game, called Guillotine, which requires a player with a strong cultural and linguistic background knowledge. The player observes a set of five words, generally unrelated to each other, and in one minute she has to provide a sixth word, semantically connected to the others. Several knowledge sources, such as a dictionary and a set of proverbs, have been modeled and integrated in order to realize a knowledge infusion process into the system. The main motivation for designing an artificial player for Guillotine is the challenge of providing the machine with the cultural and linguistic background knowledge which makes it similar to a human being, with the ability of interpreting natural language documents and reasoning on their content. Experiments carried out showed promising results, and both the knowledge source modeling and the reasoning mechanisms (implementing a spreading activation algorithm to find out the solution) seem to be appropriate. We are convinced that the approach has a great potential for other more practical applications besides solving a language game, such as semantic search.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11586/115024
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