Search (187 results, page 2 of 10)

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  1. Maaten, L. van den: Accelerating t-SNE using Tree-Based Algorithms (2014) 0.03 
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    Theme
    Data Mining
  2. Wolfe, EW.: a case study in automated metadata enhancement : Natural Language Processing in the humanities (2019) 0.03 
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    Abstract
    The Black Book Interactive Project at the University of Kansas (KU) is developing an expanded corpus of novels by African American authors, with an emphasis on lesser known writers and a goal of expanding research in this field. Using a custom metadata schema with an emphasis on race-related elements, each novel is analyzed for a variety of elements such as literary style, targeted content analysis, historical context, and other areas. Librarians at KU have worked to develop a variety of computational text analysis processes designed to assist with specific aspects of this metadata collection, including text mining and natural language processing, automated subject extraction based on word sense disambiguation, harvesting data from Wikidata, and other actions.
  3. Cohen, D.J.: From Babel to knowledge : data mining large digital collections (2006) 0.03 
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    Abstract
    In Jorge Luis Borges's curious short story The Library of Babel, the narrator describes an endless collection of books stored from floor to ceiling in a labyrinth of countless hexagonal rooms. The pages of the library's books seem to contain random sequences of letters and spaces; occasionally a few intelligible words emerge in the sea of paper and ink. Nevertheless, readers diligently, and exasperatingly, scan the shelves for coherent passages. The narrator himself has wandered numerous rooms in search of enlightenment, but with resignation he simply awaits his death and burial - which Borges explains (with signature dark humor) consists of being tossed unceremoniously over the library's banister. Borges's nightmare, of course, is a cursed vision of the research methods of disciplines such as literature, history, and philosophy, where the careful reading of books, one after the other, is supposed to lead inexorably to knowledge and understanding. Computer scientists would approach Borges's library far differently. Employing the information theory that forms the basis for search engines and other computerized techniques for assessing in one fell swoop large masses of documents, they would quickly realize the collection's incoherence though sampling and statistical methods - and wisely start looking for the library's exit. These computational methods, which allow us to find patterns, determine relationships, categorize documents, and extract information from massive corpuses, will form the basis for new tools for research in the humanities and other disciplines in the coming decade. For the past three years I have been experimenting with how to provide such end-user tools - that is, tools that harness the power of vast electronic collections while hiding much of their complicated technical plumbing. In particular, I have made extensive use of the application programming interfaces (APIs) the leading search engines provide for programmers to query their databases directly (from server to server without using their web interfaces). In addition, I have explored how one might extract information from large digital collections, from the well-curated lexicographic database WordNet to the democratic (and poorly curated) online reference work Wikipedia. While processing these digital corpuses is currently an imperfect science, even now useful tools can be created by combining various collections and methods for searching and analyzing them. And more importantly, these nascent services suggest a future in which information can be gleaned from, and sense can be made out of, even imperfect digital libraries of enormous scale. A brief examination of two approaches to data mining large digital collections hints at this future, while also providing some lessons about how to get there.
    Theme
    Data Mining
  4. Information als Rohstoff für Innovation : Programm der Bundesregierung 1996-2000 (1996) 0.03 
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    Date
    22. 2.1997 19:26:34
  5. Ask me[@sk.me]: your global information guide : der Wegweiser durch die Informationswelten (1996) 0.03 
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    Date
    30.11.1996 13:22:37
  6. Kosmos Weltatlas 2000 : Der Kompass für das 21. Jahrhundert. Inklusive Welt-Routenplaner (1999) 0.03 
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    Date
    7.11.1999 18:22:39
  7. Mitchell, J.S.: DDC 22 : an introduction (2003) 0.03 
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    Abstract
    Dewey Decimal Classification and Relative Index, Edition 22 (DDC 22) will be issued simultaneously in print and web versions in July 2003. The new edition is the first full print update to the Dewey Decimal Classification system in seven years-it includes several significant updates and many new numbers and topics. DDC 22 also features some fundamental structural changes that have been introduced with the goals of promoting classifier efficiency and improving the DDC for use in a variety of applications in the web environment. Most importantly, the content of the new edition has been shaped by the needs and recommendations of Dewey users around the world. The worldwide user community has an important role in shaping the future of the DDC.
    Object
    DDC-22
  8. Kraker, P.; Kittel, C,; Enkhbayar, A.: Open Knowledge Maps : creating a visual interface to the world's scientific knowledge based on natural language processing (2016) 0.03 
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    Theme
    Data Mining
  9. Maaten, L. van den; Hinton, G.: Visualizing non-metric similarities in multiple maps (2012) 0.03 
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    Theme
    Data Mining
  10. Wongthontham, P.; Abu-Salih, B.: Ontology-based approach for semantic data extraction from social big data : state-of-the-art and research directions (2018) 0.03 
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    Theme
    Data Mining
  11. Loonus, Y.: Einsatzbereiche der KI und ihre Relevanz für Information Professionals (2017) 0.03 
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    Theme
    Data Mining
  12. Datentracking in der Wissenschaft : Aggregation und Verwendung bzw. Verkauf von Nutzungsdaten durch Wissenschaftsverlage. Ein Informationspapier des Ausschusses für Wissenschaftliche Bibliotheken und Informationssysteme der Deutschen Forschungsgemeinschaft (2021) 0.03 
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    Theme
    Data Mining
  13. Search Engines and Beyond : Developing efficient knowledge management systems, April 19-20 1999, Boston, Mass (1999) 0.03 
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    Content
    Ramana Rao (Inxight, Palo Alto, CA) 7 ± 2 Insights on achieving Effective Information Access Session One: Updates and a twelve month perspective Danny Sullivan (Search Engine Watch, US / England) Portalization and other search trends Carol Tenopir (University of Tennessee) Search realities faced by end users and professional searchers Session Two: Today's search engines and beyond Daniel Hoogterp (Retrieval Technologies, McLean, VA) Effective presentation and utilization of search techniques Rick Kenny (Fulcrum Technologies, Ontario, Canada) Beyond document clustering: The knowledge impact statement Gary Stock (Ingenius, Kalamazoo, MI) Automated change monitoring Gary Culliss (Direct Hit, Wellesley Hills, MA) User popularity ranked search engines Byron Dom (IBM, CA) Automatically finding the best pages on the World Wide Web (CLEVER) Peter Tomassi (LookSmart, San Francisco, CA) Adding human intellect to search technology Session Three: Panel discussion: Human v automated categorization and editing Ev Brenner (New York, NY)- Chairman James Callan (University of Massachusetts, MA) Marc Krellenstein (Northern Light Technology, Cambridge, MA) Dan Miller (Ask Jeeves, Berkeley, CA) Session Four: Updates and a twelve month perspective Steve Arnold (AIT, Harrods Creek, KY) Review: The leading edge in search and retrieval software Ellen Voorhees (NIST, Gaithersburg, MD) TREC update Session Five: Search engines now and beyond Intelligent Agents John Snyder (Muscat, Cambridge, England) Practical issues behind intelligent agents Text summarization Therese Firmin, (Dept of Defense, Ft George G. Meade, MD) The TIPSTER/SUMMAC evaluation of automatic text summarization systems Cross language searching Elizabeth Liddy (TextWise, Syracuse, NY) A conceptual interlingua approach to cross-language retrieval. Video search and retrieval Armon Amir (IBM, Almaden, CA) CueVideo: Modular system for automatic indexing and browsing of video/audio Speech recognition Michael Witbrock (Lycos, Waltham, MA) Retrieval of spoken documents Visualization James A. Wise (Integral Visuals, Richland, WA) Information visualization in the new millennium: Emerging science or passing fashion? Text mining David Evans (Claritech, Pittsburgh, PA) Text mining - towards decision support
  14. Van der Veer Martens, B.: Do citation systems represent theories of truth? (2001) 0.02 
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    Date
    22. 7.2006 15:22:28
  15. Wolchover, N.: Wie ein Aufsehen erregender Beweis kaum Beachtung fand (2017) 0.02 
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    Date
    22. 4.2017 10:42:05
    22. 4.2017 10:48:38
  16. Hafner, R.; Schelling, B.: Automatisierung der Sacherschließung mit Semantic Web Technologie (2015) 0.02 
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    Date
    22. 6.2015 16:08:38
  17. Vögel unserer Heimat (1999) 0.02 
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    Date
    7.11.1999 18:22:54
  18. Dunning, A.: Do we still need search engines? (1999) 0.02 
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    Source
    Ariadne. 1999, no.22
  19. Dextre Clarke, S.G.: Challenges and opportunities for KOS standards (2007) 0.02 
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    Date
    22. 9.2007 15:41:14
  20. Hofmann-Apitius, M.: Direct use of information extraction from scientific text for modeling and simulation in the life sciences (2009) 0.02 
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    Abstract
    Scientific biomedical publications are a rich source of information about diseases and the molecules that play a role in the molecular etiology of a disease. With the development of automated methods for the identification of named biomedical entities in scientific text ("text mining") we are now able to automatically screen millions of publications for genes, their relationships to other genes, their role in the development of a disease and their role as potential targets for therapeutic cures. In fact, modern advanced search engines are now able to extract various terms in scientific text that represent entities which can be directly used for modeling of diseases and simulation of disease-relevant molecular networks. In my presentation, I will demonstrate how scientific text can be analyzed using a combination of algorithmic approaches (dictionary- and rule-based as well as machine learning - based methods). I will furthermore demonstrate, how scientific information extracted from text can be applied in disease modeling approaches that combine heterogeneous information types (protein-protein-interactions, allelic variants of genes, clinical phenotype information) extracted from scientific publications. I will furthermore show how the analysis of scientific text can be used to construct "knowledge descriptors" that allow a completely new way of predicting the activity of small pharmaceutical molecules. Taken together, the talk will hopefully provide a clue how far we really are from using text analytics for direct modeling and simulation in the life sciences.

Authors

Years

Languages

  • d 93
  • e 88
  • el 2
  • a 1
  • nl 1
  • More… Less…

Types

  • a 88
  • i 10
  • m 5
  • r 3
  • b 2
  • s 2
  • n 1
  • p 1
  • x 1
  • More… Less…

Themes

Subjects