Examining the validity of the NeedlemanWunsch algorithm in identifying decision strategy with eye-movement data
A new generation of eye trackers shows us a promising alternative approach to tracing decision processes beyond the popular computerized-information-board approach. In order to exploit the eye-movement data, this study examined the validity of the NeedlemanWunsch algorithm (NWA) to characterize the decision process, and proposed an NWA-based classification method to predict which typical strategy an empirical search behavior might belong to. An eye-tracking based experiment was conducted. Our results showed that the resemblance score by NWA conformed to the assumption that the pair of information search behaviors based on the same strategy should have the closest resemblance. Moreover, with respect to our NWA-based classification method, our result showed that its overall prediction accuracy, hit-ratio, in identifying underlying strategies achieved 88%, significantly much higher than that gained from chance. On the whole, the combination of eye-fixation data and our NWA-based classification method is qualified.
needlemanwunsch algorithm information search behavior multi-attribute decision-making eye-tracking approach sequence alignment