Skip to Main Content
Generally speaking, two conditions make cognitive search possible: (a) symbolic structures must be present in the environment and (b) these structures must be detectable by a searcher, whose behavior changes based on the structures detected. In this chapter, information search on the Internet is used to illustrate how a theoretical framework of these two conditions can assist our understanding of cognitive search. Discussion begins with information foraging theory (IFT), which predicts how general symbolic structures may exist in an information environment and how the searcher may use these structures to search for information. A computational model called SNIF-ACT (developed based on IFT) is then presented and provides a good match to online information search for specific target information. Because a further component important to cognitive search is the ability to detect and learn useful structures in the environment, discussion follows on how IFT can be extended to explain search behavior that involves incremental learning of the search environment. Illustration is provided on how different forms of semantic structures may exist in the World Wide Web, and how human searchers can learn from these structures to improve their search. Finally, the SNIFACT model is extended to characterize directed and exploratory information foraging behavior in information environments.