Search (2 results, page 1 of 1)

  • × subject_ss:"Information retrieval"
  • × subject_ss:"Information behavior"
  1. Next generation search engines : advanced models for information retrieval (2012) 0.01
    0.013457636 = product of:
      0.053830545 = sum of:
        0.053830545 = weight(_text_:social in 357) [ClassicSimilarity], result of:
          0.053830545 = score(doc=357,freq=14.0), product of:
            0.1847249 = queryWeight, product of:
              3.9875789 = idf(docFreq=2228, maxDocs=44218)
              0.046325076 = queryNorm
            0.29140925 = fieldWeight in 357, product of:
              3.7416575 = tf(freq=14.0), with freq of:
                14.0 = termFreq=14.0
              3.9875789 = idf(docFreq=2228, maxDocs=44218)
              0.01953125 = fieldNorm(doc=357)
      0.25 = coord(1/4)
    
    Abstract
    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.
  2. New directions in human information behavior (2006) 0.01
    0.011373779 = product of:
      0.045495115 = sum of:
        0.045495115 = weight(_text_:social in 577) [ClassicSimilarity], result of:
          0.045495115 = score(doc=577,freq=10.0), product of:
            0.1847249 = queryWeight, product of:
              3.9875789 = idf(docFreq=2228, maxDocs=44218)
              0.046325076 = queryNorm
            0.24628578 = fieldWeight in 577, product of:
              3.1622777 = tf(freq=10.0), with freq of:
                10.0 = termFreq=10.0
              3.9875789 = idf(docFreq=2228, maxDocs=44218)
              0.01953125 = fieldNorm(doc=577)
      0.25 = coord(1/4)
    
    Abstract
    New Directions in Human Information Behavior, co-edited by Drs. Amanda Spink and Charles Cole provides an understanding of the new directions, leading edge theories and models in human information behavior. Information behavior is conceptualized as complex human information related processes that are embedded within an individual's everyday social and life processes. The book presents chapters by an interdisciplinary range of scholars who show new directions that often challenge the established views and paradigms of information behavior studies. Beginning with an evolutionary framework, the book examines information behaviors over various epochs of human existence from the Palaeolithic Era and within pre-literate societies, to contemporary behaviors by 21st century humans. Drawing upon social and psychological science theories the book presents a more integrated and holistic approach to the understanding of information behaviors that include multitasking and non-linear longitudinal processes, individuals' information ground, information practices and information sharing, digital behaviors and human information organizing behaviors. The final chapter of the book integrates these new approaches and presents an overview of the key trends, theories and models for further research. This book is directly relevant to information scientists, librarians, social and evolutionary psychologists. Undergraduate and graduate students, academics and information professionals interested in human information behavior will find this book of particular benefit.
    Content
    Inhalt: Introduction: New Directions in Human Information Behavior, Amanda Spink and Charles Cole.- Emerging Evolutionary Approach to Human Information Behavior, Amanda Spink and James Currier.- Information Behavior in Pre-Literate Societies, Andrew D. Madden, Jared Bryson and Joe Palimi.- Towards a Social Framework for Information Seeking, Eszter Hargittai and Amanda Hinnant.- Mapping Textually-Mediated Information Practice in Clinical Midwifery Care, Pamela McKenzie.- Information Grounds: Theoretical Basis and Empirical Findings on Information Flow in Social Settings, Karen E. Fisher and Charles M. Naumer.-Information Sharing, Sanna Talja and Preben Hansen.- Multitasking and Coordinating Framework for Human Information Behavior, Amanda Spink, Minsoo Park and Charles Cole.- A Nonlinear Perspective on Information Seeking, Allen Foster.- A Cognitive Framework for Human Information Behavior: The Place of Metaphor in Human Information Organizing Behavior, Charles Cole and John Leide.- The Digital Information Consumer, David Nicholas, Paul Huntingron, Peter Williams and Tom Dubrowolski.- Integrating Framework and Further Research.