Search (4 results, page 1 of 1)

  • × theme_ss:"Suchtaktik"
  • × author_ss:"Jansen, B.J."
  1. Jansen, B.J.; Booth, D.L.; Spink, A.: Determining the informational, navigational, and transactional intent of Web queries (2008) 0.02
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    Abstract
    In this paper, we define and present a comprehensive classification of user intent for Web searching. The classification consists of three hierarchical levels of informational, navigational, and transactional intent. After deriving attributes of each, we then developed 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. Our findings show that more than 80% of Web queries are informational in nature, with about 10% each being navigational and transactional. In order to validate the accuracy of our algorithm, we manually coded 400 queries and compared the results from this manual classification to the results determined by the automated method. This comparison showed that the automatic classification has an accuracy of 74%. Of the remaining 25% of the queries, the user intent is vague or multi-faceted, pointing to the need for probabilistic classification. We discuss how search engines can use knowledge of user intent to provide more targeted and relevant results in Web searching.
  2. Jansen, B.J.; Resnick, M.: ¬An examination of searcher's perceptions of nonsponsored and sponsored links during ecommerce Web searching (2006) 0.02
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    Abstract
    In this article, we report results of an investigation into the effect of sponsored links on ecommerce information seeking on the Web. In this research, 56 participants each engaged in six ecommerce Web searching tasks. We extracted these tasks from the transaction log of a Web search engine, so they represent actual ecommerce searching information needs. Using 60 organic and 30 sponsored Web links, the quality of the Web search engine results was controlled by switching nonsponsored and sponsored links on half of the tasks for each participant. This allowed for investigating the bias toward sponsored links while controlling for quality of content. The study also investigated the relationship between searching self-efficacy, searching experience, types of ecommerce information needs, and the order of links on the viewing of sponsored links. Data included 2,453 interactions with links from result pages and 961 utterances evaluating these links. The results of the study indicate that there is a strong preference for nonsponsored links, with searchers viewing these results first more than 82% of the time. Searching self-efficacy and experience does not increase the likelihood of viewing sponsored links, and the order of the result listing does not appear to affect searcher evaluation of sponsored links. The implications for sponsored links as a long-term business model are discussed.
  3. Jansen, B.J.; Booth, D.L.; Spink, A.: Patterns of query reformulation during Web searching (2009) 0.02
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    Abstract
    Query reformulation is a key user behavior during Web search. Our research goal is to develop predictive models of query reformulation during Web searching. This article reports results from a study in which we automatically classified the query-reformulation patterns for 964,780 Web searching sessions, composed of 1,523,072 queries, to predict the next query reformulation. We employed an n-gram modeling approach to describe the probability of users transitioning from one query-reformulation state to another to predict their next state. We developed first-, second-, third-, and fourth-order models and evaluated each model for accuracy of prediction, coverage of the dataset, and complexity of the possible pattern set. The results show that Reformulation and Assistance account for approximately 45% of all query reformulations; furthermore, the results demonstrate that the first- and second-order models provide the best predictability, between 28 and 40% overall and higher than 70% for some patterns. Implications are that the n-gram approach can be used for improving searching systems and searching assistance.
  4. Jansen, B.J.; Booth, D.L.; Smith, B.K.: Using the taxonomy of cognitive learning to model online searching (2009) 0.01
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    Abstract
    In this research, we investigated whether a learning process has unique information searching characteristics. The results of this research show that information searching is a learning process with unique searching characteristics specific to particular learning levels. In a laboratory experiment, we studied the searching characteristics of 72 participants engaged in 426 searching tasks. We classified the searching tasks according to Anderson and Krathwohl's taxonomy of the cognitive learning domain. Research results indicate that applying and analyzing, the middle two of the six categories, generally take the most searching effort in terms of queries per session, topics searched per session, and total time searching. Interestingly, the lowest two learning categories, remembering and understanding, exhibit searching characteristics similar to the highest order learning categories of evaluating and creating. Our results suggest the view of Web searchers having simple information needs may be incorrect. Instead, we discovered that users applied simple searching expressions to support their higher-level information needs. It appears that searchers rely primarily on their internal knowledge for evaluating and creating information needs, using search primarily for fact checking and verification. Overall, results indicate that a learning theory may better describe the information searching process than more commonly used paradigms of decision making or problem solving. The learning style of the searcher does have some moderating effect on exhibited searching characteristics. The implication of this research is that rather than solely addressing a searcher's expressed information need, searching systems can also address the underlying learning need of the user.