Search (22 results, page 1 of 2)

  • × author_ss:"Jansen, B.J."
  1. Zhang, Y.; Jansen, B.J.; Spink, A.: Identification of factors predicting clickthrough in Web searching using neural network analysis (2009) 0.04 
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    Date
    22. 3.2009 17:49:11
    Source
    Journal of the American Society for Information Science and Technology. 60(2009) no.3, S.557-570
  2. Wolfram, D.; Spink, A.; Jansen, B.J.; Saracevic, T.: Vox populi : the public searching of the Web (2001) 0.02 
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    Source
    Journal of the American Society for Information Science and technology. 52(2001) no.12, S.1073-1074
  3. Jansen, B.J.; Rieh, S.Y.: ¬The seventeen theoretical constructs of information searching and information retrieval (2010) 0.01 
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    Abstract
    In this article, we identify, compare, and contrast theoretical constructs for the fields of information searching and information retrieval to emphasize the uniqueness of and synergy between the fields. Theoretical constructs are the foundational elements that underpin a field's core theories, models, assumptions, methodologies, and evaluation metrics. We provide a framework to compare and contrast the theoretical constructs in the fields of information searching and information retrieval using intellectual perspective and theoretical orientation. The intellectual perspectives are information searching, information retrieval, and cross-cutting; and the theoretical orientations are information, people, and technology. Using this framework, we identify 17 significant constructs in these fields contrasting the differences and comparing the similarities. We discuss the impact of the interplay among these constructs for moving research forward within both fields. Although there is tension between the fields due to contradictory constructs, an examination shows a trend toward convergence. We discuss the implications for future research within the information searching and information retrieval fields.
    Source
    Journal of the American Society for Information Science and Technology. 61(2010) no.8, S.1517-1534
  4. Koshman, S.; Spink, A.; Jansen, B.J.: Web searching on the Vivisimo search engine (2006) 0.01 
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    Abstract
    The application of clustering to Web search engine technology is a novel approach that offers structure to the information deluge often faced by Web searchers. Clustering methods have been well studied in research labs; however, real user searching with clustering systems in operational Web environments is not well understood. This article reports on results from a transaction log analysis of Vivisimo.com, which is a Web meta-search engine that dynamically clusters users' search results. A transaction log analysis was conducted on 2-week's worth of data collected from March 28 to April 4 and April 25 to May 2, 2004, representing 100% of site traffic during these periods and 2,029,734 queries overall. The results show that the highest percentage of queries contained two terms. The highest percentage of search sessions contained one query and was less than 1 minute in duration. Almost half of user interactions with clusters consisted of displaying a cluster's result set, and a small percentage of interactions showed cluster tree expansion. Findings show that 11.1% of search sessions were multitasking searches, and there are a broad variety of search topics in multitasking search sessions. Other searching interactions and statistics on repeat users of the search engine are reported. These results provide insights into search characteristics with a cluster-based Web search engine and extend research into Web searching trends.
    Source
    Journal of the American Society for Information Science and Technology. 57(2006) no.14, S.1875-1887
  5. Tjondronegoro, D.; Spink, A.; Jansen, B.J.: ¬A study and comparison of multimedia Web searching : 1997-2006 (2009) 0.01 
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    Abstract
    Searching for multimedia is an important activity for users of Web search engines. Studying user's interactions with Web search engine multimedia buttons, including image, audio, and video, is important for the development of multimedia Web search systems. This article provides results from a Weblog analysis study of multimedia Web searching by Dogpile users in 2006. The study analyzes the (a) duration, size, and structure of Web search queries and sessions; (b) user demographics; (c) most popular multimedia Web searching terms; and (d) use of advanced Web search techniques including Boolean and natural language. The current study findings are compared with results from previous multimedia Web searching studies. The key findings are: (a) Since 1997, image search consistently is the dominant media type searched followed by audio and video; (b) multimedia search duration is still short (>50% of searching episodes are <1 min), using few search terms; (c) many multimedia searches are for information about people, especially in audio search; and (d) multimedia search has begun to shift from entertainment to other categories such as medical, sports, and technology (based on the most repeated terms). Implications for design of Web multimedia search engines are discussed.
    Source
    Journal of the American Society for Information Science and Technology. 60(2009) no.9, S.1756-1768
  6. Jansen, B.J.; Pooch , U.: ¬A review of Web searching studies and a framework for future research (2001) 0.01 
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    Source
    Journal of the American Society for Information Science and technology. 52(2001) no.3, S.235-246
  7. Jansen, B.J.; Spink, A.; Pedersen, J.: ¬A temporal comparison of AItaVista Web searching (2005) 0.01 
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    Source
    Journal of the American Society for Information Science and Technology. 56(2005) no.6, S.559-570
  8. Reddy, M.C.; Jansen, B.J.: ¬A model for understanding collaborative information behavior in context : a study of two healthcare teams (2008) 0.01 
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    Abstract
    Collaborative information behavior is an essential aspect of organizational work; however, we have very limited understanding of this behavior. Most models of information behavior focus on the individual seeker of information. In this paper, we report the results from two empirical studies that investigate aspects of collaborative information behavior in organizational settings. From these studies, we found that collaborative information behavior differs from individual information behavior with respect to how individuals interact with each other, the complexity of the information need, and the role of information technology. There are specific triggers for transitioning from individual to collaborative information behavior, including lack of domain expertise. The information retrieval technologies used affect collaborative information behavior by acting as important supporting mechanisms. From these results and prior work, we develop a model of collaborative information behavior along the axes of participant behavior, situational elements, and contextual triggers. We also present characteristics of collaborative information system including search, chat, and sharing. We discuss implications for the design of collaborative information retrieval systems and directions for future work.
  9. Jansen, B.J.; Booth, D.L.; Spink, A.: Patterns of query reformulation during Web searching (2009) 0.01 
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    Source
    Journal of the American Society for Information Science and Technology. 60(2009) no.7, S.1358-1371
  10. Ortiz-Cordova, A.; Jansen, B.J.: Classifying web search queries to identify high revenue generating customers (2012) 0.01 
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    Source
    Journal of the American Society for Information Science and Technology. 63(2012) no.7, S.1426-1441
  11. Spink, A.; Jansen, B.J.; Pedersen , J.: Searching for people on Web search engines (2004) 0.01 
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    Abstract
    The Web is a communication and information technology that is often used for the distribution and retrieval of personal information. Many people and organizations mount Web sites containing large amounts of information on individuals, particularly about celebrities. However, limited studies have examined how people search for information on other people, using personal names, via Web search engines. Explores the nature of personal name searching on Web search engines. The specific research questions addressed in the study are: "Do personal names form a major part of queries to Web search engines?"; "What are the characteristics of personal name Web searching?"; and "How effective is personal name Web searching?". Random samples of queries from two Web search engines were analyzed. The findings show that: personal name searching is a common but not a major part of Web searching with few people seeking information on celebrities via Web search engines; few personal name queries include double quotations or additional identifying terms; and name searches on Alta Vista included more advanced search features relative to those on AlltheWeb.com. Discusses the implications of the findings for Web searching and search engines, and further research.
  12. Jansen, B.J.; McNeese, M.D.: Evaluating the Effectiveness of and Patterns of Interactions With Automated Searching Assistance (2005) 0.01 
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    Source
    Journal of the American Society for Information Science and Technology. 56(2005) no.14, S.1480-1503
  13. Jansen, B.J.; Resnick, M.: ¬An examination of searcher's perceptions of nonsponsored and sponsored links during ecommerce Web searching (2006) 0.01 
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    Journal of the American Society for Information Science and Technology. 57(2006) no.14, S.1949-1961
  14. Jansen, B.J.; Spink, A.; Koshman, S.: Web searcher interaction with the Dogpile.com metasearch engine (2007) 0.01 
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    Journal of the American Society for Information Science and Technology. 58(2007) no.5, S.744-755
  15. Jansen, B.J.; Spink, A.; Blakely, C.; Koshman, S.: Defining a session on Web search engines (2007) 0.01 
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    Journal of the American Society for Information Science and Technology. 58(2007) no.6, S.862-871
  16. Jansen, B.J.; Zhang, M.; Schultz, C.D.: Brand and its effect on user perception of search engine performance (2009) 0.01 
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    Journal of the American Society for Information Science and Technology. 60(2009) no.8, S.1572-1595
  17. Jansen, B.J.; Zhang, M.; Sobel, K.; Chowdury, A.: Twitter power : tweets as electronic word of mouth (2009) 0.01 
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    Journal of the American Society for Information Science and Technology. 60(2009) no.11, S.2169-2188
  18. Jansen, B.J.; Liu, Z.; Simon, Z.: ¬The effect of ad rank on the performance of keyword advertising campaigns (2013) 0.01 
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    Journal of the American Society for Information Science and Technology. 64(2013) no.10, S.2115-2132
  19. Coughlin, D.M.; Campbell, M.C.; Jansen, B.J.: ¬A web analytics approach for appraising electronic resources in academic libraries (2016) 0.01 
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    Journal of the Association for Information Science and Technology. 67(2016) no.3, S.518-534
  20. Coughlin, D.M.; Jansen, B.J.: Modeling journal bibliometrics to predict downloads and inform purchase decisions at university research libraries (2016) 0.01 
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    Source
    Journal of the Association for Information Science and Technology. 67(2016) no.9, S.2263-2273

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