Literatur zur Informationserschließung

Diese Datenbank enthält über 40.000 Dokumente zu Themen aus den Bereichen Formalerschließung – Inhaltserschließung – Information Retrieval.

© 2015 W. Gödert, TH Köln, Institut für Informationswissenschaft / Powered by litecat, BIS Oldenburg (Stand: 04. Juni 2021)

Suchergebnisse

• 1
  Nguyen-Kim, M.T.: ¬Die kleinste gemeinsame Wirklichkeit : wahr, falsch, plausibel? : die größten Streitfragen wissenschaftlich geprüft.
  München : Dromer, 2021. 367 S.
  ISBN 978-3-426-27822-2
  
  Abstract: Die bekannte Wissenschaftsjournalistin Dr. Mai Thi Nguyen-Kim untersucht mit analytischem Scharfsinn und unbestechlicher Logik brennende Streitfragen unserer Gesellschaft. Mit Fakten und wissenschaftlichen Erkenntnissen kontert sie Halbwahrheiten, Fakes und Verschwörungsmythen - und zeigt, wo wir uns mangels Beweisen noch zurecht munter streiten dürfen. Themen: Die Legalisierung von Drogen, Videospiele, Gewalt, Gender Pay Gap, systemrelevante Berufe, Care-Arbeit, Lohngerechtigkeit, Big Pharma vs. Alternative Medizin, Homöopathie, klinische Studien, Impfpflicht, die Erblichkeit von Intelligenz, Gene vs. Umwelt, männliche und weibliche Gehirne, Tierversuche und von Corona bis Klimawandel: Wie politisch darf Wissenschaft sein? ; Fakten, wissenschaftlich fundiert und eindeutig belegt, sind Gold wert. Gerade dann, wenn in Gesellschaft und Politik über Reizthemen hitzig gestritten wird, braucht es einen Faktencheck, um die Dinge klarzustellen und Irrtümer und Fakes aus der Welt schaffen. Leider aber werden Fakten oft verkürzt, missverständlich präsentiert oder gerne auch mit subjektiver Meinung wild gemischt. Ein sachlicher Diskurs? Nicht mehr möglich. Dr. Mai Thi Nguyen-Kim räumt bei den derzeit beliebtesten Streitthemen mit diesem Missstand auf. Bestechend klarsichtig, wunderbar unaufgeregt und herrlich kurzweilig ermittelt sie anhand wissenschaftlicher Erkenntnisse das, was faktisch niemand in Abrede stellen kann, wenn es beispielsweise um Erblichkeit von Intelligenz, Gender Pay Gap, Klimawandel oder Legalisierung von Drogen geht. Mai Thi Nguyen-Kims Suche nach dem Kern der Wahrheit zeigt dabei nicht nur, was unanfechtbar ist und worauf wir uns alle einigen können. Mehr noch: Sie macht deutlich, wo die Fakten aufhören, wo Zahlen und wissenschaftliche Belege fehlen - wo wir also völlig berechtigt uns gegenseitig persönliche Meinungen an den Kopf werfen dürfen. Ein spannender und informativer Fakten- und Reality-Check, der beste Bullshit-Detektor für unsere angeblich postfaktische Zeit.
  
  
  Compass: Knowledge, Theory of
  LCSH: Communication in science
  Precis: Fake news
  BK: 02.10 (Wissenschaft und Gesellschaft)
  GHBS: AGO (DU-E)
  RVK: CC 2500 ; AK 22000
  
• 2
  Kim, M. ; Baek, I. ; Song, M.: Topic diffusion analysis of a weighted citation network in biomedical literature.
  In: Journal of the Association for Information Science and Technology. 69(2018) no.2, S.329-342.
  
  Abstract: In this study, we propose a framework for detecting topic evolutions in weighted citation networks. Citation networks are important in studying knowledge flows; however, citation network analysis has primarily focused on binary networks in which the individual citation influences of each cited paper in a citing paper are considered identical, even though not all cited papers have a significant influence on the cited publication. Accordingly, it is necessary to build and analyze a citation network comprising scholarly publications that notably impact one another, thus identifying topic evolution in a more precise manner. To measure the strength of citation influence and identify paper topics, we employ a citation influence topic model primarily based on topical inheritance between cited and citing papers. Using scholarly publications in the field of the protein p53 as a case study, we build a citation network, filter it using citation influence values, and examine the diffusion of topics not only in the field but also in the subfields of p53.
  
  Inhalt: Vgl.: http://onlinelibrary.wiley.com/doi/10.1002/asi.23960/full.
  
  Themenfeld: Informetrie
  Wissenschaftsfach: Medizin
  
  
• 3
  Lim, J. ; Kang, S. ; Kim, M.: Automatic user preference learning for personalized electronic program guide applications.
  In: Journal of the American Society for Information Science and Technology. 58(2007) no.9, S.1346-1356.
  
  Abstract: In this article, we introduce a user preference model contained in the User Interaction Tools Clause of the MPEG-7 Multimedia Description Schemes, which is described by a UserPreferences description scheme (DS) and a UsageHistory description scheme (DS). Then we propose a user preference learning algorithm by using a Bayesian network to which weighted usage history data on multimedia consumption is taken as input. Our user preference learning algorithm adopts a dynamic learning method for learning real-time changes in a user's preferences from content consumption history data by weighting these choices in time. Finally, we address a user preference-based television program recommendation system on the basis of the user preference learning algorithm and show experimental results for a large set of realistic usage-history data of watched television programs. The experimental results suggest that our automatic user reference learning method is well suited for a personalized electronic program guide (EPG) application.
  
  Inhalt: In-depth articles: Applications of MPEG-7 tools
  
  Anmerkung: Beitrag eines Themenschwerpunktes
  
  Themenfeld: Multimedia
  Objekt: MPEG-7
  
  
• 4
  Chang, Y. ; Ounis, I. ; Kim, M.: Query reformulation using automatically generated query concepts from a document space.
  In: Information processing and management. 42(2006) no.2, S.453-468.
  
  Abstract: We propose a new query reformulation approach, using a set of query concepts that are introduced to precisely denote the user's information need. Since a document collection is considered to be a domain which includes latent primitive concepts, we identify those concepts through a local pattern discovery and a global modeling using data mining techniques. For a new query, we select its most associated primitive concepts and choose the most probable interpretations as query concepts. We discuss the issue of constructing the primitive concepts from either the whole corpus or from the retrieved set of documents. Our experiments are performed on the TREC8 collection. The experimental evaluation shows that our approach is as good as current query reformulation approaches, while being particularly effective for poorly performing queries. Moreover, we find that the approach using the primitive concepts generated from the set of retrieved documents leads to the most effective performance.
  
  
  
• 5
  Kantor, P. ; Kim, M.H. ; Ibraev, U. ; Atasoy, K.: Estimating the number of relevant documents in enormous collections.
  In: Knowledge: creation, organization and use. Proceedings of the 62nd Annual Meeting of the American Society for Information Science, 31.10.-4.11.1999. Ed.: L. Woods. Medford, NJ : Information Today, 1999. S.507-514.
  (Proceedings of the American Society for Information Science; vol.36)
  
  Abstract: In assessing information retrieval systems, it is important to know not only the precision of the retrieved set, but also to compare the number of retrieved relevant items to the total number of relevant items. For large collections, such as the TREC test collections, or the World Wide Web, it is not possible to enumerate the entire set of relevant documents. If the retrieved documents are evaluated, a variant of the statistical "capture-recapture" method can be used to estimate the total number of relevant documents, providing the several retrieval systems used are sufficiently independent. We show that the underlying signal detection model supporting such an analysis can be extended in two ways. First, assuming that there are two distinct performance characteristics (corresponding to the chance of retrieving a relevant, and retrieving a given non-relevant document), we show that if there are three or more independent systems available it is possible to estimate the number of relevant documents without actually having to decide whether each individual document is relevant. We report applications of this 3-system method to the TREC data, leading to the conclusion that the independence assumptions are not satisfied. We then extend the model to a multi-system, multi-problem model, and show that it is possible to include statistical dependencies of all orders in the model, and determine the number of relevant documents for each of the problems in the set. Application to the TREC setting will be presented
  
  Themenfeld: Retrievalalgorithmen ; Retrievalstudien
  Objekt: TREC
  
  
• 6
  Lee, J.H. ; Kim, M.H.: Ranking documents in thesaurus-based Boolean retrieval systems.
  In: Information processing and management. 30(1994) no.1, S.79-91.
  
  Abstract: Investigates document ranking methods in thesaurus-based Boolean retrieval systems and proposes a new thesaurus-based ranking algorithm, the Extended Relevance (E-Relevance) algorithm. The E-Relevance algorithm integrates the extended Boolean model and the thesaurus-based relevance algorithm. Since the E-Relevance algorithm has all the desirable properties of previous thesauri-based ranking algorithms. It also ranks documents effectively by uisng terms dependence information from the thesaurus. Through performance comparison shows that the proposed algorithm achieved higher retrieval effectiveness than the others proposed earlier
  
  
  
• 7
  Lee, J.H. ; Kim, M.H. ; Lee, Y.J.: Information retrieval based on conceptual distance in is-a hierarchies.
  In: Journal of documentation. 49(1993) no.2, S.188-207.
  
  Abstract: There have been several document ranking methods to calculate the conceptual distance or closeness between a Boolean query and a document. Though they provide good retrieval effectiveness in many cases, they do not support effective weighting schemes for queries and documents and also have several problems resulting from inappropriate evaluation of Boolean operators. We propose a new method called Knowledge-Based Extended Boolean Model (KB-EBM) in which Salton's extended Boolean model is incorporated. KB-EBM evaluates weighted queries and documents effectively, and avoids the problems of the previous methods. KB-EBM provides high quality document rankings by using term dependence information from is-a hierarchies. The performance experiments show that the proposed method closely simulates human behaviour
  
  Themenfeld: Computerlinguistik