Word order variation and string similarity algorithm to reduce pattern scripting in pattern matching conversational agents

Kaleem, M, O'Shea, J and Crockett, K (2014) Word order variation and string similarity algorithm to reduce pattern scripting in pattern matching conversational agents. In: 14th UK Workshop on Computational Intelligence (UKCI), 2014.

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Abstract

This paper presents a novel sentence similarity algorithm designed to tackle the issue of free word order in the Urdu language. Free word order in a language poses many challenges when implemented in a conversational agent, primarily due to the fact that it increases the amount of scripting time needed to script the domain knowledge. A language with free word order like Urdu means a single phrase/utterance can be expressed in many different ways using the same words and still be grammatically correct. This led to the research of a novel string similarity algorithm which was utilized in the development of an Urdu conversational agent. The algorithm was tested through a black box testing methodology which involved processing different variations of scripted patterns through the system to gauge the performance and accuracy of the algorithm with regards to recognizing word order variations of the related scripted patterns. Initial testing has highlighted that the algorithm is able to recognize legal word order variations and reduce the knowledge base scripting of conversational agents significantly. Thus saving great time and effort when scripting the knowledge base of a conversational agent.