Search (2 results, page 1 of 1)

  • × theme_ss:"Internet"
  • × author_ss:"Spink, A."
  1. Zhang, Y.; Jansen, B.J.; Spink, A.: Identification of factors predicting clickthrough in Web searching using neural network analysis (2009) 0.02 
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    Abstract
    In this research, we aim to identify factors that significantly affect the clickthrough of Web searchers. Our underlying goal is determine more efficient methods to optimize the clickthrough rate. We devise a clickthrough metric for measuring customer satisfaction of search engine results using the number of links visited, number of queries a user submits, and rank of clicked links. We use a neural network to detect the significant influence of searching characteristics on future user clickthrough. Our results show that high occurrences of query reformulation, lengthy searching duration, longer query length, and the higher ranking of prior clicked links correlate positively with future clickthrough. We provide recommendations for leveraging these findings for improving the performance of search engine retrieval and result ranking, along with implications for search engine marketing.
    Date
    22. 3.2009 17:49:11
  2. Goodrum, A.; Spink, A.: Visual information seeking : a study of image queries on the world wide web (1999) 0.00 
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    Abstract
    A growing body of research is beginning to explore the information-seeking behavior of Web users. The vast majority of these studies have concentrated on the area of textual information retrieval (IR). Little research has examined how people search for non-textual information on the Internet, and few large-scale studies have investigated visual information-seeking behavior with Web search engines. This study examined visual information needs as expressed in users' Web image queries. The data set examined consisted of 1,025,908 sequential queries from 211,058 users of EXCITE, a major Internet search service. Twenty-eight (28) terms were used to identify queries for both still and moving images, resulting in a subset of 33,149 image queries by 9,855 users. We provide data on: (1) image queries -- the number of queries and the number of search terms per user, (2) image search sessions -- the number of queries per user, modifications made to subsequent queries in a session, and (3) image terms -- their rank/frequency distribution and the most highly used search terms. On average, there were 3. 36 image queries per user containing an average of 3.74 terms per query. Image queries contained a large number of unique terms. The most frequently occurring image related terms appeared less than 10 percent of the time, with most terms occurring only once. This analysis is contrasted to earlier work by Enser (1995) who examined written queries for pictorial information in a non-digital environment. Implications for the development of models for visual information retrieval, and for the design of Web search engines are discussed

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