Search (29 results, page 1 of 2)

  • × theme_ss:"Suchmaschinen"
  • × year_i:[2010 TO 2020}
  1. Chen, L.-C.: Next generation search engine for the result clustering technology (2012) 0.05 
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    Abstract
    Result clustering has recently attracted a lot of attention to provide the users with a succinct overview of relevant search results than traditional search engines. This chapter proposes a mixed clustering method to organize all returned search results into a hierarchical tree structure. The clustering method accomplishes two main tasks, one is label construction and the other is tree building. This chapter uses precision to measure the quality of clustering results. According to the results of experiments, the author preliminarily concluded that the performance of the system is better than many other well-known commercial and academic systems. This chapter makes several contributions. First, it presents a high performance system based on the clustering method. Second, it develops a divisive hierarchical clustering algorithm to organize all returned snippets into hierarchical tree structure. Third, it performs a wide range of experimental analyses to show that almost all commercial systems are significantly better than most current academic systems.
    Date
    17. 4.2012 15:22:11
  2. Bouidghaghen, O.; Tamine, L.: Spatio-temporal based personalization for mobile search (2012) 0.04 
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    Abstract
    The explosion of the information available on the Internet has made traditional information retrieval systems, characterized by one size fits all approaches, less effective. Indeed, users are overwhelmed by the information delivered by such systems in response to their queries, particularly when the latter are ambiguous. In order to tackle this problem, the state-of-the-art reveals that there is a growing interest towards contextual information retrieval (CIR) which relies on various sources of evidence issued from the user's search background and environment, in order to improve the retrieval accuracy. This chapter focuses on mobile context, highlights challenges they present for IR, and gives an overview of CIR approaches applied in this environment. Then, the authors present an approach to personalize search results for mobile users by exploiting both cognitive and spatio-temporal contexts. The experimental evaluation undertaken in front of Yahoo search shows that the approach improves the quality of top search result lists and enhances search result precision.
    Date
    20. 4.2012 13:19:22
  3. Chaudiron, S.; Ihadjadene, M.: Studying Web search engines from a user perspective : key concepts and main approaches (2012) 0.03 
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    Abstract
    This chapter shows that the wider use of Web search engines, reconsidering the theoretical and methodological frameworks to grasp new information practices. Beginning with an overview of the recent challenges implied by the dynamic nature of the Web, this chapter then traces the information behavior related concepts in order to present the different approaches from the user perspective. The authors pay special attention to the concept of "information practice" and other related concepts such as "use", "activity", and "behavior" largely used in the literature but not always strictly defined. The authors provide an overview of user-oriented studies that are meaningful to understand the different contexts of use of electronic information access systems, focusing on five approaches: the system-oriented approaches, the theories of information seeking, the cognitive and psychological approaches, the management science approaches, and the marketing approaches. Future directions of work are then shaped, including social searching and the ethical, cultural, and political dimensions of Web search engines. The authors conclude considering the importance of Critical theory to better understand the role of Web Search engines in our modern society.
    Date
    20. 4.2012 13:22:37
  4. Gossen, T.: Search engines for children : search user interfaces and information-seeking behaviour (2016) 0.03 
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    Content
    Inhalt: Acknowledgments; Abstract; Zusammenfassung; Contents; List of Figures; List of Tables; List of Acronyms; Chapter 1 Introduction ; 1.1 Research Questions; 1.2 Thesis Outline; Part I Fundamentals ; Chapter 2 Information Retrieval for Young Users ; 2.1 Basics of Information Retrieval; 2.1.1 Architecture of an IR System; 2.1.2 Relevance Ranking; 2.1.3 Search User Interfaces; 2.1.4 Targeted Search Engines; 2.2 Aspects of Child Development Relevant for Information Retrieval Tasks; 2.2.1 Human Cognitive Development; 2.2.2 Information Processing Theory; 2.2.3 Psychosocial Development 2.3 User Studies and Evaluation2.3.1 Methods in User Studies; 2.3.2 Types of Evaluation; 2.3.3 Evaluation with Children; 2.4 Discussion; Chapter 3 State of the Art ; 3.1 Children's Information-Seeking Behaviour; 3.1.1 Querying Behaviour; 3.1.2 Search Strategy; 3.1.3 Navigation Style; 3.1.4 User Interface; 3.1.5 Relevance Judgement; 3.2 Existing Algorithms and User Interface Concepts for Children; 3.2.1 Query; 3.2.2 Content; 3.2.3 Ranking; 3.2.4 Search Result Visualisation; 3.3 Existing Information Retrieval Systems for Children; 3.3.1 Digital Book Libraries; 3.3.2 Web Search Engines 3.4 Summary and DiscussionPart II Studying Open Issues ; Chapter 4 Usability of Existing Search Engines for Young Users ; 4.1 Assessment Criteria; 4.1.1 Criteria for Matching the Motor Skills; 4.1.2 Criteria for Matching the Cognitive Skills; 4.2 Results; 4.2.1 Conformance with Motor Skills; 4.2.2 Conformance with the Cognitive Skills; 4.2.3 Presentation of Search Results; 4.2.4 Browsing versus Searching; 4.2.5 Navigational Style; 4.3 Summary and Discussion; Chapter 5 Large-scale Analysis of Children's Queries and Search Interactions; 5.1 Dataset; 5.2 Results; 5.3 Summary and Discussion Chapter 6 Differences in Usability and Perception of Targeted Web Search Engines between Children and Adults 6.1 Related Work; 6.2 User Study; 6.3 Study Results; 6.4 Summary and Discussion; Part III Tackling the Challenges ; Chapter 7 Search User Interface Design for Children ; 7.1 Conceptual Challenges and Possible Solutions; 7.2 Knowledge Journey Design; 7.3 Evaluation; 7.3.1 Study Design; 7.3.2 Study Results; 7.4 Voice-Controlled Search: Initial Study; 7.4.1 User Study; 7.5 Summary and Discussion; Chapter 8 Addressing User Diversity ; 8.1 Evolving Search User Interface 8.1.1 Mapping Function8.1.2 Evolving Skills; 8.1.3 Detection of User Abilities; 8.1.4 Design Concepts; 8.2 Adaptation of a Search User Interface towards User Needs; 8.2.1 Design & Implementation; 8.2.2 Search Input; 8.2.3 Result Output; 8.2.4 General Properties; 8.2.5 Configuration and Further Details; 8.3 Evaluation; 8.3.1 Study Design; 8.3.2 Study Results; 8.3.3 Preferred UI Settings; 8.3.4 User satisfaction; 8.4 Knowledge Journey Exhibit; 8.4.1 Hardware; 8.4.2 Frontend; 8.4.3 Backend; 8.5 Summary and Discussion; Chapter 9 Supporting Visual Searchers in Processing Search Results 9.1 Related Work
    Date
    1. 2.2016 18:25:22
    LCSH
    User interfaces (Computer systems)
    Subject
    User interfaces (Computer systems)
  5. Lewandowski, D.: Wie "Next Generation Search Systems" die Suche auf eine neue Ebene heben und die Informationswelt verändern (2017) 0.02 
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    Abstract
    Suchmaschinen befinden sich einerseits in einem beständigen Wandel. Andererseits gibt es immer wieder Entwicklungen, die die Suche "auf eine neue Ebene" heben. Eine solche Entwicklung, die wir zurzeit erleben, wird unter dem Label "Next Generation Search Systems" geführt. Der Begriff fasst die Veränderungen durch eine Vielfalt von Geräten und Eingabemöglichkeiten, die Verfügbarkeit von Verhaltensdaten en masse und den Wandel von Dokumenten zu Antworten zusammen.
    Footnote
    Bezug zum Buch: White, R.: Interactions with search systems. New York ; Cambridge University Press ; 2016.
  6. White, R.W.: Interactions with search systems (2016) 0.02 
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    Abstract
    Information seeking is a fundamental human activity. In the modern world, it is frequently conducted through interactions with search systems. The retrieval and comprehension of information returned by these systems is a key part of decision making and action in a broad range of settings. Advances in data availability coupled with new interaction paradigms, and mobile and cloud computing capabilities, have created a broad range of new opportunities for information access and use. In this comprehensive book for professionals, researchers, and students involved in search system design and evaluation, search expert Ryen White discusses how search systems can capitalize on new capabilities and how next-generation systems must support higher order search activities such as task completion, learning, and decision making. He outlines the implications of these changes for the evolution of search evaluation, as well as challenges that extend beyond search systems in areas such as privacy and societal benefit.
    Footnote
    Vgl. auch den Beitrag: Lewandowski, D.: Wie "Next Generation Search Systems" die Suche auf eine neue Ebene heben und die Informationswelt verändern. In: http://www.password-online.de/?wysija-page=1&controller=email&action=view&email_id=254&wysijap=subscriptions&user_id=1045..
  7. Ke, W.: Decentralized search and the clustering paradox in large scale information networks (2012) 0.01 
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    Abstract
    Amid the rapid growth of information today is the increasing challenge for people to navigate its magnitude. Dynamics and heterogeneity of large information spaces such as the Web raise important questions about information retrieval in these environments. Collection of all information in advance and centralization of IR operations are extremely difficult, if not impossible, because systems are dynamic and information is distributed. The chapter discusses some of the key issues facing classic information retrieval models and presents a decentralized, organic view of information systems pertaining to search in large scale networks. It focuses on the impact of network structure on search performance and discusses a phenomenon we refer to as the Clustering Paradox, in which the topology of interconnected systems imposes a scalability limit.
  8. Lewandowski, D.: Query understanding (2011) 0.01 
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    Date
    18. 9.2018 18:22:18
  9. Bensman, S.J.: Eugene Garfield, Francis Narin, and PageRank : the theoretical bases of the Google search engine (2013) 0.01 
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    Date
    17.12.2013 11:02:22
  10. Tober, M.; Hennig, L.; Furch, D.: SEO Ranking-Faktoren und Rang-Korrelationen 2014 : Google Deutschland (2014) 0.01 
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    Date
    13. 9.2014 14:45:22
  11. Schaat, S.: Von der automatisierten Manipulation zur Manipulation der Automatisierung (2019) 0.01 
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    Date
    19. 2.2019 17:22:00
  12. Fluhr, C.: Crosslingual access to photo databases (2012) 0.01 
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    Date
    17. 4.2012 14:25:22
  13. Lewandowski, D.: ¬Die Macht der Suchmaschinen und ihr Einfluss auf unsere Entscheidungen (2014) 0.01 
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    Date
    22. 9.2014 18:54:11
  14. Huvila, I.: Affective capitalism of knowing and the society of search engine (2016) 0.01 
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    Date
    20. 1.2015 18:30:22
  15. Rieh, S.Y.; Kim, Y.-M.; Markey, K.: Amount of invested mental effort (AIME) in online searching (2012) 0.01 
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    Abstract
    This research investigates how people's perceptions of information retrieval (IR) systems, their perceptions of search tasks, and their perceptions of self-efficacy influence the amount of invested mental effort (AIME) they put into using two different IR systems: a Web search engine and a library system. It also explores the impact of mental effort on an end user's search experience. To assess AIME in online searching, two experiments were conducted using these methods: Experiment 1 relied on self-reports and Experiment 2 employed the dual-task technique. In both experiments, data were collected through search transaction logs, a pre-search background questionnaire, a post-search questionnaire and an interview. Important findings are these: (1) subjects invested greater mental effort searching a library system than searching the Web; (2) subjects put little effort into Web searching because of their high sense of self-efficacy in their searching ability and their perception of the easiness of the Web; (3) subjects did not recognize that putting mental effort into searching was something needed to improve the search results; and (4) data collected from multiple sources proved to be effective for assessing mental effort in online searching.
  16. Lewandowski, D.; Spree, U.: Ranking of Wikipedia articles in search engines revisited : fair ranking for reasonable quality? (2011) 0.01 
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  17. Aloteibi, S.; Sanderson, M.: Analyzing geographic query reformulation : an exploratory study (2014) 0.01 
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  19. Alqaraleh, S.; Ramadan, O.; Salamah, M.: Efficient watcher based web crawler design (2015) 0.01 
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  20. epd: Kaiserslauterer Forscher untersuchen Google-Suche (2017) 0.01 
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