Search (283 results, page 2 of 15)

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Date

22. 1.2017 16:45:48

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Abstract

With the proliferation of huge amounts of (heterogeneous) data on the Web, the importance of information retrieval (IR) has grown considerably over the last few years. Big players in the computer industry, such as Google, Microsoft and Yahoo!, are the primary contributors of technology for fast access to Web-based information; and searching capabilities are now integrated into most information systems, ranging from business management software and customer relationship systems to social networks and mobile phone applications. Ceri and his co-authors aim at taking their readers from the foundations of modern information retrieval to the most advanced challenges of Web IR. To this end, their book is divided into three parts. The first part addresses the principles of IR and provides a systematic and compact description of basic information retrieval techniques (including binary, vector space and probabilistic models as well as natural language search processing) before focusing on its application to the Web. Part two addresses the foundational aspects of Web IR by discussing the general architecture of search engines (with a focus on the crawling and indexing processes), describing link analysis methods (specifically Page Rank and HITS), addressing recommendation and diversification, and finally presenting advertising in search (the main source of revenues for search engines). The third and final part describes advanced aspects of Web search, each chapter providing a self-contained, up-to-date survey on current Web research directions. Topics in this part include meta-search and multi-domain search, semantic search, search in the context of multimedia data, and crowd search. The book is ideally suited to courses on information retrieval, as it covers all Web-independent foundational aspects. Its presentation is self-contained and does not require prior background knowledge. It can also be used in the context of classic courses on data management, allowing the instructor to cover both structured and unstructured data in various formats. Its classroom use is facilitated by a set of slides, which can be downloaded from www.search-computing.org.

Date

16.10.2013 19:22:44

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Date

28. 9.2016 18:22:22

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Content

Inhalt: A. Grundsätzliche Fragen (aus dem Umfeld) der Wissensorganisation Markus Gottwald, Matthias Klemm und Jan Weyand: Warum ist es schwierig, Wissen zu managen? Ein soziologischer Deutungsversuch anhand eines Wissensmanagementprojekts in einem Großunternehmen H. Peter Ohly: Wissenskommunikation und -organisation. Quo vadis? Helmut F. Spinner: Wissenspartizipation und Wissenschaftskommunikation in drei Wissensräumen: Entwurf einer integrierten Theorie B. Dokumentationssprachen in der Anwendung Felix Boteram: Semantische Relationen in Dokumentationssprachen vom Thesaurus zum semantischen Netz Jessica Hubrich: Multilinguale Wissensorganisation im Zeitalter der Globalisierung: das Projekt CrissCross Vivien Petras: Heterogenitätsbehandlung und Terminology Mapping durch Crosskonkordanzen - eine Fallstudie Manfred Hauer, Uwe Leissing und Karl Rädler: Query-Expansion durch Fachthesauri Erfahrungsbericht zu dandelon.com, Vorarlberger Parlamentsinformationssystem und vorarlberg.at
C. Begriffsarbeit in der Wissensorganisation Ingetraut Dahlberg: Begriffsarbeit in der Wissensorganisation Claudio Gnoli, Gabriele Merli, Gianni Pavan, Elisabetta Bernuzzi, and Marco Priano: Freely faceted classification for a Web-based bibliographic archive The BioAcoustic Reference Database Stefan Hauser: Terminologiearbeit im Bereich Wissensorganisation - Vergleich dreier Publikationen anhand der Darstellung des Themenkomplexes Thesaurus Daniel Kless: Erstellung eines allgemeinen Standards zur Wissensorganisation: Nutzen, Möglichkeiten, Herausforderungen, Wege D. Kommunikation und Lernen Gerald Beck und Simon Meissner: Strukturierung und Vermittlung von heterogenen (Nicht-)Wissensbeständen in der Risikokommunikation Angelo Chianese, Francesca Cantone, Mario Caropreso, and Vincenzo Moscato: ARCHAEOLOGY 2.0: Cultural E-Learning tools and distributed repositories supported by SEMANTICA, a System for Learning Object Retrieval and Adaptive Courseware Generation for e-learning environments Sonja Hierl, Lydia Bauer, Nadja Böller und Josef Herget: Kollaborative Konzeption von Ontologien in der Hochschullehre: Theorie, Chancen und mögliche Umsetzung Marc Wilhelm Küster, Christoph Ludwig, Yahya Al-Haff und Andreas Aschenbrenner: TextGrid: eScholarship und der Fortschritt der Wissenschaft durch vernetzte Angebote

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Abstract

Are art and science separated by an unbridgeable divide? Can they find common ground? In this new book, neuroscientist Eric R. Kandel, whose remarkable scientific career and deep interest in art give him a unique perspective, demonstrates how science can inform the way we experience a work of art and seek to understand its meaning. Kandel illustrates how reductionism?the distillation of larger scientific or aesthetic concepts into smaller, more tractable components?has been used by scientists and artists alike to pursue their respective truths. He draws on his Nobel Prize-winning work revealing the neurobiological underpinnings of learning and memory in sea slugs to shed light on the complex workings of the mental processes of higher animals. In Reductionism in Art and Brain Science, Kandel shows how this radically reductionist approach, applied to the most complex puzzle of our time?the brain?has been employed by modern artists who distill their subjective world into color, form, and light. Kandel demonstrates through bottom-up sensory and top-down cognitive functions how science can explore the complexities of human perception and help us to perceive, appreciate, and understand great works of art. At the heart of the book is an elegant elucidation of the contribution of reductionism to the evolution of modern art and its role in a monumental shift in artistic perspective. Reductionism steered the transition from figurative art to the first explorations of abstract art reflected in the works of Turner, Monet, Kandinsky, Schoenberg, and Mondrian. Kandel explains how, in the postwar era, Pollock, de Kooning, Rothko, Louis, Turrell, and Flavin used a reductionist approach to arrive at their abstract expressionism and how Katz, Warhol, Close, and Sandback built upon the advances of the New York School to reimagine figurative and minimal art. Featuring captivating drawings of the brain alongside full-color reproductions of modern art masterpieces, this book draws out the common concerns of science and art and how they illuminate each other.

Content

The emergence of a reductionist school of abstract art in New York -- The Beginning of a Scientific Approach to Art -- The Biology of the Beholder's Share: Visual Perception and Bottom-Up Processing in Art -- The Biology of Learning and Memory: Top-Down Processing in Art -- A Reductionist Approach to Art. Reductionism in the Emergence of Abstract Art -- Mondrian and the Radical Reduction of the Figurative Image -- The New York School of Painters -- How the Brain Processes and Perceives Abstract Images -- From Figuration to Color Abstraction -- Color and the Brain -- A Focus on Light -- A Reductionist Influence on Figuration -- The Emerging Dialogue Between Abstract Art and Science. Why Is Reductionism Successful in Art? -- A Return to the Two Cultures

Date

14. 6.2019 12:22:37

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Abstract

The debate about access to scientific research raises questions about the current effectiveness of scholarly communication processes. This book explores, from an independent point of view, the current state of the STM publishing market, new publishing technologies and business models as well as the information habit of researchers, the politics of research funders, and the demand for scientific research as a public good. The book also investigates the democratisation of science including how the information needs of knowledge workers outside academia can be embraced in future.

Content

Inhalt: Chapter 1. Background -- Chapter 2. Definitions -- Chapter 3. Aims, Objectives, and Methodology -- Chapter 4. Setting the Scene -- Chapter 5. Information Society -- Chapter 6. Drivers for Change -- Chapter 7 A Dysfunctional STM Scene? -- Chapter 8. Comments on the Dysfunctionality of STM Publishing -- Chapter 9. The Main Stakeholders -- Chapter 10. Search and Discovery -- Chapter 11. Impact of Google -- Chapter 12. Psychological Issues -- Chapter 13. Users of Research Output -- Chapter 14. Underlying Sociological Developments -- Chapter 15. Social Media and Social Networking -- Chapter 16. Forms of Article Delivery -- Chapter 17. Future Communication Trends -- Chapter 18. Academic Knowledge Workers -- Chapter 19. Unaffiliated Knowledge Workers -- Chapter 20. The Professions -- Chapter 21. Small and Medium Enterprises -- Chapter 22. Citizen Scientists -- Chapter 23. Learned Societies -- Chapter 24. Business Models -- Chapter 25. Open Access -- Chapter 26. Political Initiatives -- Chapter 27. Summary and Conclusions -- Chapter 28. Research Questions Addressed

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Date

22. 6.2016 16:08:54

Footnote

Rez. in: Economist vom Jun 18.06.2016 [http://www.economist.com/news/books-and-arts/21700611-circle-circle]: "Everyone by nature desires to know," wrote Aristotle more than 2,000 years ago. But are there limits to what human beings can know? This is the question that Marcus du Sautoy, the British mathematician who succeeeded Richard Dawkins as the Simonyi professor for the public understanding of science at Oxford University, explores in "What We Cannot Know", his fascinating book on the limits of scientific knowledge. As Mr du Sautoy argues, this is a golden age of scientific knowledge. Remarkable achievements stretch across the sciences, from the Large Hadron Collider and the sequencing of the human genome to the proof of Fermat's Last Theorem. And the rate of progress is accelerating: the number of scientific publications has doubled every nine years since the second world war. But even bigger challenges await. Can cancer be cured? Ageing beaten? Is there a "Theory of Everything" that will include all of physics? Can we know it all? One limit to people's knowledge is practical. In theory, if you throw a die, Newton's laws of motion make it possible to predict what number will come up. But the calculations are too long to be practicable. What is more, many natural systems, such as the weather, are "chaotic" or sensitive to small changes: a tiny nudge now can lead to vastly different behaviour later. Since people cannot measure with complete accuracy, they can't forecast far into the future. The problem was memorably articulated by Edward Lorenz, an American scientist, in 1972 in a famous paper called "Does the Flap of a Butterfly's Wings in Brazil Set Off a Tornado in Texas?"
Even if the future cannot be predicted, people can still hope to uncover the laws of physics. As Stephen Hawking wrote in his 1988 bestseller "A Brief History of Time", "I still believe there are grounds for cautious optimism that we may be near the end of the search for the ultimate laws of nature." But how can people know when they have got there? They have been wrong before: Lord Kelvin, a great physicist, confidently announced in 1900: "There is nothing new to be discovered in physics now." Just a few years later, physics was upended by the new theories of relativity and quantum physics. Quantum physics presents particular limits on human knowledge, as it suggests that there is a basic randomness or uncertainty in the universe. For example, electrons exist as a "wave function", smeared out across space, and do not have a definite position until you observe them (which "collapses" the wave function). At the same time there seems to be an absolute limit on how much people can know. This is quantified by Heisenberg's Uncertainty Principle, which says that there is a trade-off between knowing the position and momentum of a particle. So the more you know about where an electron is, the less you know about which way it is going. Even scientists find this weird. As Niels Bohr, a Danish physicist, said: "If quantum physics hasn't profoundly shocked you, you haven't understood it yet."

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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

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Date

22. 1.2017 17:12:50

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Date

23. 9.2010 11:15:22

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Classification

MBL 22

SSD

MBL 22

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22. 2.2013 12:09:34

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19.12.2015 11:57:22

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2.10.2017 12:22:26

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22. 1.2018 17:33:05

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18. 9.2018 12:57:22

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22. 8.2016 16:06:54