Danielle L. Booth

TL;DR: A software application was developed that automatically classified queries using a Web search engine log of over a million and a half queries submitted by several hundred thousand users and showed that the automatic classification has an accuracy of 74%.

TL;DR: In this article, the authors define and present a comprehensive classification of user intent for Web searching, which consists of three hierarchical levels of informational, navigational, and transactional intent, and then develop a software application that automatically classified queries using a web search engine log of over a million and a half queries submitted by several hundred thousand users.

TL;DR: This paper qualitatively analyzes samples of queries from seven transaction logs from three different Web search engines containing more than five million queries and identifies characteristics of user queries based on three broad classifications of user intent.

TL;DR: The results of this research show that information searching is a learning process with unique searching characteristics specific to particular learning levels, and indicate that a learning theory may better describe the information searching process than more commonly used paradigms of decision making or problem solving.

TL;DR: Results show that Reformulation and Assistance account for approximately 45p of all query reformulations; furthermore, the results demonstrate that the first- and second-order models provide the best predictability, between 28 and 40p overall and higher than 70p for some patterns.