Search (4 results, page 1 of 1)

  • × year_i:[2010 TO 2020}
  • × subject_ss:"Information retrieval"
  1. Next generation search engines : advanced models for information retrieval (2012) 0.01
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    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. Interactive information seeking, behaviour and retrieval (2011) 0.01
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    Abstract
    Information retrieval (IR) is a complex human activity supported by sophisticated systems. Information science has contributed much to the design and evaluation of previous generations of IR system development and to our general understanding of how such systems should be designed and yet, due to the increasing success and diversity of IR systems, many recent textbooks concentrate on IR systems themselves and ignore the human side of searching for information. This book is the first text to provide an information science perspective on IR. Unique in its scope, the book covers the whole spectrum of information retrieval, including: history and background information; behaviour and seeking task-based information; searching and retrieval approaches to investigating information; interaction and behaviour information; representation access models; evaluation interfaces for IR; interactive techniques; web retrieval, ranking and personalization; and, recommendation, collaboration and social search multimedia: interfaces and access. A key text for senior undergraduates and masters' level students of all information and library studies courses, this book is also useful for practising LIS professionals who need to better appreciate how IR systems are designed, implemented and evaluated.
    Content
    Enthält die Beiträge: Interactive information retrieval: history and background / Colleen Cool and Nicholas J. Belkin - Information behavior and seeking / Peiling Wang - Task-based information searching and retrieval / Elaine G. Toms - Approaches to investigating information interaction and behaviour / Raya Fidel - Information representation / Mark D. Smucker - Access models / Edie Rasmussen - Evaluation / Kalervo Järvelin - Interfaces for information retrieval / Max Wilson - Interactive techniques / Ryen W. White - Web retrieval, ranking and personalization / Jaime Teevan and Susan Dumais - Recommendation, collaboration and social search / David M. Nichols and Michael B. Twidale - Multimedia: behaviour, interfaces and interaction / Haiming Liu, Suzanne Little and Stefan Rüger - Multimedia: information representation and access / Suzanne Little, Evan Brown and Stefan Rüger
  3. Arafat, S.; Ashoori, E.: Search foundations : toward a science of technology-mediated experience (2018) 0.01
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    Abstract
    This book contributes to discussions within Information Retrieval and Science (IR&S) by improving our conceptual understanding of the relationship between humans and technology. A call to redirect the intellectual focus of information retrieval and science (IR&S) toward the phenomenon of technology-mediated experience. In this book, Sachi Arafat and Elham Ashoori issue a call to reorient the intellectual focus of information retrieval and science (IR&S) away from search and related processes toward the more general phenomenon of technology-mediated experience. Technology-mediated experience accounts for an increasing proportion of human lived experience; the phenomenon of mediation gets at the heart of the human-machine relationship. Framing IR&S more broadly in this way generalizes its problems and perspectives, dovetailing them with those shared across disciplines dealing with socio-technical phenomena. This reorientation of IR&S requires imagining it as a new kind of science: a science of technology-mediated experience (STME). Arafat and Ashoori not only offer detailed analysis of the foundational concepts underlying IR&S and other technical disciplines but also boldly call for a radical, systematic appropriation of the sciences and humanities to create a better understanding of the human-technology relationship. Arafat and Ashoori discuss the notion of progress in IR&S and consider ideas of progress from the history and philosophy of science. They argue that progress in IR&S requires explicit linking between technical and nontechnical aspects of discourse. They develop a network of basic questions and present a discursive framework for addressing these questions. With this book, Arafat and Ashoori provide both a manifesto for the reimagining of their field and the foundations on which a reframed IR&S would rest.
  4. Gödert, W.; Hubrich, J.; Nagelschmidt, M.: Semantic knowledge representation for information retrieval (2014) 0.00
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    Date
    23. 7.2017 13:49:22