An evaluation of classification models for question topic categorization
Journal of the American Society for Information Science and Technology
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This paper analyzes and compares the data gathered from two previously conducted artificial linguistic Internet chat entity (ALICE) chatterbot studies that were focused on response accuracy and user satisfaction measures for six chatterbots. These chatterbots were further loaded with varying degrees of conversational, telecommunications, and terrorism knowledge. From our prior experiments using 347 participants, we obtained 33 446 human/chatterbot interactions. It was found that asking the ALICE chatterbots ??are?? and ??where?? questions resulted in higher response satisfaction levels, as compared to other interrogative-style inputs because of their acceptability to vague, binary, or clichE??d chatterbot responses. We also found a relationship between the length of a query and the users perceived satisfaction of the chatterbot response, where shorter queries led to more satisfying responses.