Search (4 results, page 1 of 1)

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  • × subject_ss:"Information retrieval"
  1. Next generation search engines : advanced models for information retrieval (2012) 0.11
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    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
  2. Social information retrieval systems : emerging technologies and applications for searching the Web effectively (2008) 0.07
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    Content
    Inhalt Collaborating to search effectively in different searcher modes through cues and specialty search / Naresh Kumar Agarwal and Danny C.C. Poo -- Collaborative querying using a hybrid content and results-based approach / Chandrani Sinha Ray ... [et al.] -- Collaborative classification for group-oriented organization of search results / Keiichi Nakata and Amrish Singh -- A case study of use-centered descriptions : archival descriptions of what can be done with a collection / Richard Butterworth -- Metadata for social recommendations : storing, sharing, and reusing evaluations of learning resources / Riina Vuorikari, Nikos Manouselis, and Erik Duval -- Social network models for enhancing reference-based search engine rankings / Nikolaos Korfiatis ... [et al.] -- From PageRank to social rank : authority-based retrieval in social information spaces / Sebastian Marius Kirsch ... [et al.] -- Adaptive peer-to-peer social networks for distributed content-based Web search / Le-Shin Wu ... [et al.] -- The ethics of social information retrieval / Brendan Luyt and Chu Keong Lee -- The social context of knowledge / Daniel Memmi -- Social information seeking in digital libraries / George Buchanan and Annika Hinze -- Relevant intra-actions in networked environments / Theresa Dirndorfer Anderson -- Publication and citation analysis as a tool for information retrieval / Ronald Rousseau -- Personalized information retrieval in a semantic-based learning environment / Antonella Carbonaro and Rodolfo Ferrini -- Multi-agent tourism system (MATS) / Soe Yu Maw and Myo-Myo Naing -- Hybrid recommendation systems : a case study on the movies domain / Konstantinos Markellos ... [et al.].
    LCSH
    Web search engines
    Subject
    Web search engines
  3. ¬The thesaurus: review, renaissance and revision (2004) 0.03
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    Content
    Enthält u.a. folgende Aussage von J. Aitchison u. S. Dextre Clarke: "We face a paradox. Ostensibly, the need and the opportunity to apply thesauri to information retrieval are greater than ever before. On the other hand, users resist most efforts to persuade them to apply one. The drive for interoperability of systems means we must design our vocabularies for easy integration into downstream applications such as content management systems, indexing/metatagging interfaces, search engines, and portals. Summarizing the search for vocabularies that work more intuitively, we see that there are trends working in opposite directions. In the hugely popular taxonomies an the one hand, relationships between terms are more loosely defined than in thesauri. In the ontologies that will support computer-to-computer communications in AI applications such as the Semantic Web, we see the need for much more precisely defined term relationships."
  4. 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