Search (5 results, page 1 of 1)

  • × subject_ss:"User interfaces (Computer systems)"
  1. Gossen, T.: Search engines for children : search user interfaces and information-seeking behaviour (2016) 0.06
    0.06007237 = product of:
      0.12014474 = sum of:
        0.109524645 = weight(_text_:engines in 2752) [ClassicSimilarity], result of:
          0.109524645 = score(doc=2752,freq=12.0), product of:
            0.22757743 = queryWeight, product of:
              5.080822 = idf(docFreq=746, maxDocs=44218)
              0.04479146 = queryNorm
            0.48126322 = fieldWeight in 2752, product of:
              3.4641016 = tf(freq=12.0), with freq of:
                12.0 = termFreq=12.0
              5.080822 = idf(docFreq=746, maxDocs=44218)
              0.02734375 = fieldNorm(doc=2752)
        0.010620093 = product of:
          0.021240186 = sum of:
            0.021240186 = weight(_text_:22 in 2752) [ClassicSimilarity], result of:
              0.021240186 = score(doc=2752,freq=2.0), product of:
                0.15685207 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.04479146 = queryNorm
                0.1354154 = fieldWeight in 2752, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.02734375 = fieldNorm(doc=2752)
          0.5 = coord(1/2)
      0.5 = coord(2/4)
    
    Abstract
    The doctoral thesis of Tatiana Gossen formulates criteria and guidelines on how to design the user interfaces of search engines for children. In her work, the author identifies the conceptual challenges based on own and previous user studies and addresses the changing characteristics of the users by providing a means of adaptation. Additionally, a novel type of search result visualisation for children with cartoon style characters is developed taking children's preference for visual information into account.
    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
  2. Next generation search engines : advanced models for information retrieval (2012) 0.03
    0.030923871 = product of:
      0.123695485 = sum of:
        0.123695485 = weight(_text_:engines in 357) [ClassicSimilarity], result of:
          0.123695485 = score(doc=357,freq=30.0), product of:
            0.22757743 = queryWeight, product of:
              5.080822 = idf(docFreq=746, maxDocs=44218)
              0.04479146 = queryNorm
            0.5435314 = fieldWeight in 357, product of:
              5.477226 = tf(freq=30.0), with freq of:
                30.0 = termFreq=30.0
              5.080822 = idf(docFreq=746, maxDocs=44218)
              0.01953125 = fieldNorm(doc=357)
      0.25 = coord(1/4)
    
    Abstract
    The main goal of this book is to transfer new research results from the fields of advanced computer sciences and information science to the design of new search engines. The readers will have a better idea of the new trends in applied research. The achievement of relevant, organized, sorted, and workable answers- to name but a few - from a search is becoming a daily need for enterprises and organizations, and, to a greater extent, for anyone. It does not consist of getting access to structural information as in standard databases; nor does it consist of searching information strictly by way of a combination of key words. It goes far beyond that. Whatever its modality, the information sought should be identified by the topics it contains, that is to say by its textual, audio, video or graphical contents. This is not a new issue. However, recent technological advances have completely changed the techniques being used. New Web technologies, the emergence of Intranet systems and the abundance of information on the Internet have created the need for efficient search and information access tools.
    Recent technological progress in computer science, Web technologies, and constantly evolving information available on the Internet has drastically changed the landscape of search and access to information. Web search has significantly evolved in recent years. In the beginning, web search engines such as Google and Yahoo! were only providing search service over text documents. Aggregated search was one of the first steps to go beyond text search, and was the beginning of a new era for information seeking and retrieval. These days, new web search engines support aggregated search over a number of vertices, and blend different types of documents (e.g., images, videos) in their search results. New search engines employ advanced techniques involving machine learning, computational linguistics and psychology, user interaction and modeling, information visualization, Web engineering, artificial intelligence, distributed systems, social networks, statistical analysis, semantic analysis, and technologies over query sessions. Documents no longer exist on their own; they are connected to other documents, they are associated with users and their position in a social network, and they can be mapped onto a variety of ontologies. Similarly, retrieval tasks have become more interactive and are solidly embedded in a user's geospatial, social, and historical context. It is conjectured that new breakthroughs in information retrieval will not come from smarter algorithms that better exploit existing information sources, but from new retrieval algorithms that can intelligently use and combine new sources of contextual metadata.
    With the rapid growth of web-based applications, such as search engines, Facebook, and Twitter, the development of effective and personalized information retrieval techniques and of user interfaces is essential. The amount of shared information and of social networks has also considerably grown, requiring metadata for new sources of information, like Wikipedia and ODP. These metadata have to provide classification information for a wide range of topics, as well as for social networking sites like Twitter, and Facebook, each of which provides additional preferences, tagging information and social contexts. Due to the explosion of social networks and other metadata sources, it is an opportune time to identify ways to exploit such metadata in IR tasks such as user modeling, query understanding, and personalization, to name a few. Although the use of traditional metadata such as html text, web page titles, and anchor text is fairly well-understood, the use of category information, user behavior data, and geographical information is just beginning to be studied. This book is intended for scientists and decision-makers who wish to gain working knowledge about search engines in order to evaluate available solutions and to dialogue with software and data providers.
    Content
    Enthält die Beiträge: Das, A., A. Jain: Indexing the World Wide Web: the journey so far. Ke, W.: Decentralized search and the clustering paradox in large scale information networks. Roux, M.: Metadata for search engines: what can be learned from e-Sciences? Fluhr, C.: Crosslingual access to photo databases. Djioua, B., J.-P. Desclés u. M. Alrahabi: Searching and mining with semantic categories. Ghorbel, H., A. Bahri u. R. Bouaziz: Fuzzy ontologies building platform for Semantic Web: FOB platform. Lassalle, E., E. Lassalle: Semantic models in information retrieval. Berry, M.W., R. Esau u. B. Kiefer: The use of text mining techniques in electronic discovery for legal matters. Sleem-Amer, M., I. Bigorgne u. S. Brizard u.a.: Intelligent semantic search engines for opinion and sentiment mining. Hoeber, O.: Human-centred Web search.
    Vert, S.: Extensions of Web browsers useful to knowledge workers. Chen, L.-C.: Next generation search engine for the result clustering technology. Biskri, I., L. Rompré: Using association rules for query reformulation. Habernal, I., M. Konopík u. O. Rohlík: Question answering. Grau, B.: Finding answers to questions, in text collections or Web, in open domain or specialty domains. Berri, J., R. Benlamri: Context-aware mobile search engine. Bouidghaghen, O., L. Tamine: Spatio-temporal based personalization for mobile search. Chaudiron, S., M. Ihadjadene: Studying Web search engines from a user perspective: key concepts and main approaches. Karaman, F.: Artificial intelligence enabled search engines (AIESE) and the implications. Lewandowski, D.: A framework for evaluating the retrieval effectiveness of search engines.
    Footnote
    Vgl.: http://www.igi-global.com/book/next-generation-search-engines/59723.
    LCSH
    Search engines
    Subject
    Search engines
  3. Hearst, M.A.: Search user interfaces (2009) 0.02
    0.022127323 = product of:
      0.08850929 = sum of:
        0.08850929 = weight(_text_:engines in 4029) [ClassicSimilarity], result of:
          0.08850929 = score(doc=4029,freq=6.0), product of:
            0.22757743 = queryWeight, product of:
              5.080822 = idf(docFreq=746, maxDocs=44218)
              0.04479146 = queryNorm
            0.38891944 = fieldWeight in 4029, product of:
              2.4494898 = tf(freq=6.0), with freq of:
                6.0 = termFreq=6.0
              5.080822 = idf(docFreq=746, maxDocs=44218)
              0.03125 = fieldNorm(doc=4029)
      0.25 = coord(1/4)
    
    Abstract
    This book outlines the human side of the information seeking process, and focuses on the aspects of this process that can best be supported by the user interface. It describes the methods behind user interface design generally, and search interface design in particular, with an emphasis on how best to evaluate search interfaces. It discusses research results and current practices surrounding user interfaces for query specification, display of retrieval results, grouping retrieval results, navigation of information collections, query reformulation, search personalization, and the broader tasks of sensemaking and text analysis. Much of the discussion pertains to Web search engines, but the book also covers the special considerations surrounding search of other information collections.
    LCSH
    Web search engines
    Subject
    Web search engines
  4. Semantic keyword-based search on structured data sources : First COST Action IC1302 International KEYSTONE Conference, IKC 2015, Coimbra, Portugal, September 8-9, 2015. Revised Selected Papers (2016) 0.00
    0.0042911656 = product of:
      0.017164662 = sum of:
        0.017164662 = product of:
          0.034329325 = sum of:
            0.034329325 = weight(_text_:22 in 2753) [ClassicSimilarity], result of:
              0.034329325 = score(doc=2753,freq=4.0), product of:
                0.15685207 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.04479146 = queryNorm
                0.21886435 = fieldWeight in 2753, product of:
                  2.0 = tf(freq=4.0), with freq of:
                    4.0 = termFreq=4.0
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.03125 = fieldNorm(doc=2753)
          0.5 = coord(1/2)
      0.25 = coord(1/4)
    
    Abstract
    This book constitutes the thoroughly refereed post-conference proceedings of the First COST Action IC1302 International KEYSTONE Conference on semantic Keyword-based Search on Structured Data Sources, IKC 2015, held in Coimbra, Portugal, in September 2015. The 13 revised full papers, 3 revised short papers, and 2 invited papers were carefully reviewed and selected from 22 initial submissions. The paper topics cover techniques for keyword search, semantic data management, social Web and social media, information retrieval, benchmarking for search on big data.
    Date
    1. 2.2016 18:25:22
  5. Thissen, F.: Screen-Design-Manual : Communicating Effectively Through Multimedia (2003) 0.00
    0.0037928906 = product of:
      0.015171562 = sum of:
        0.015171562 = product of:
          0.030343125 = sum of:
            0.030343125 = weight(_text_:22 in 1397) [ClassicSimilarity], result of:
              0.030343125 = score(doc=1397,freq=2.0), product of:
                0.15685207 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.04479146 = queryNorm
                0.19345059 = fieldWeight in 1397, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=1397)
          0.5 = coord(1/2)
      0.25 = coord(1/4)
    
    Date
    22. 3.2008 14:29:25

Types