Analyzing users’ search patterns to explore topic knowledge from aggregated search results

Abstract

Combining and assembling different search results to achieve a clearer focus and better organization is a challenging research issue of aggregated search. The goal of this research is to assemble useful and relevant in-formation from one or multiple sources and then present it via one interface, rather than as a ranked list. That is, we propose a framework and then develop the WikiMapp application based on the three main components of an aggregated search framework. In this research, we adopt the concept and principle of the program theory evaluation (PTE) and extended evaluation measure (EEM) to refine our application and use zero-order state transition (ZOST), and multiple lengths of maximal repeat patterns (m_MRPs) (i.e., a re-fined MRPs method) to observe and analyze users’ search move behaviors with the interface, as well as the relationship between those moves and task accomplishment. In this way, we aim to identify the best sequences of search move patterns that lead to successful searches. Our preliminary evaluation results show that WikiMapp actually helps users achieve better task performance by using the topic map tool in the interface.