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: 28. April 2022)

Suchergebnisse

• 1
  Deardorff, A. ; Masterton, K. ; Roberts, K. ; Kilicoglu, H. ; Demner-Fushman, D.: ¬A protocol-driven approach to automatically finding authoritative answers to consumer health questions in online resources.
  In: Journal of the Association for Information Science and Technology. 68(2017) no.7, S.1724-1736.
  
  Abstract: The purpose of this research was to establish an upper bound on finding answers to health-related questions in MedlinePlus and other online resources. Seven reference librarians tested a set of protocols to determine whether it was possible to use the types and foci of the questions extracted from customer requests submitted to the National Library of Medicine to find authoritative answers to these questions. Librarians tested the protocols manually to determine if the process was sufficiently robust and accurate to later automate. Results indicated that the extracted terms provide enough information to find authoritative answers for about 60% of questions and that certain question types are more likely to result in authoritative answers than others. The question corpus and analysis performed for this project will inform automatic question answering systems, and could lead to suggestions for new content to include in MedlinePlus. This approach can serve as an example to researchers interested in methods of evaluating question answering tools and the contents of online databases.
  
  Inhalt: Vgl.: http://onlinelibrary.wiley.com/doi/10.1002/asi.23806/full.
  
  Themenfeld: Informationsmittel
  Wissenschaftsfach: Medizin
  
  
• 2
  Apostolova, E. ; You, D. ; Xue, Z. ; Antani, S. ; Demner-Fushman, D. ; Thoma, G.R.: Image retrieval from scientific publications : text and image content processing to separate multipanel figures.
  In: Journal of the American Society for Information Science and Technology. 64(2013) no.5, S.893-908.
  
  Abstract: Images contained in scientific publications are widely considered useful for educational and research purposes, and their accurate indexing is critical for efficient and effective retrieval. Such image retrieval is complicated by the fact that figures in the scientific literature often combine multiple individual subfigures (panels). Multipanel figures are in fact the predominant pattern in certain types of scientific publications. The goal of this work is to automatically segment multipanel figures-a necessary step for automatic semantic indexing and in the development of image retrieval systems targeting the scientific literature. We have developed a method that uses the image content as well as the associated figure caption to: (1) automatically detect panel boundaries; (2) detect panel labels in the images and convert them to text; and (3) detect the labels and textual descriptions of each panel within the captions. Our approach combines the output of image-content and text-based processing steps to split the multipanel figures into individual subfigures and assign to each subfigure its corresponding section of the caption. The developed system achieved precision of 81% and recall of 73% on the task of automatic segmentation of multipanel figures.
  
  Behandelte Form: Bilder
  
  
• 3
  Humphrey, S.M. ; Rogers, W.J. ; Kilicoglu, H. ; Demner-Fushman, D. ; Rindflesch, T.C.: Word sense disambiguation by selecting the best semantic type based on journal descriptor indexing : preliminary experiment.
  In: Journal of the American Society for Information Science and Technology. 57(2006) no.1, S.96-113.
  
  Abstract: An experiment was performed at the National Library of Medicine® (NLM®) in word sense disambiguation (WSD) using the Journal Descriptor Indexing (JDI) methodology. The motivation is the need to solve the ambiguity problem confronting NLM's MetaMap system, which maps free text to terms corresponding to concepts in NLM's Unified Medical Language System® (UMLS®) Metathesaurus®. If the text maps to more than one Metathesaurus concept at the same high confidence score, MetaMap has no way of knowing which concept is the correct mapping. We describe the JDI methodology, which is ultimately based an statistical associations between words in a training set of MEDLINE® citations and a small set of journal descriptors (assigned by humans to journals per se) assumed to be inherited by the citations. JDI is the basis for selecting the best meaning that is correlated to UMLS semantic types (STs) assigned to ambiguous concepts in the Metathesaurus. For example, the ambiguity transport has two meanings: "Biological Transport" assigned the ST Cell Function and "Patient transport" assigned the ST Health Care Activity. A JDI-based methodology can analyze text containing transport and determine which ST receives a higher score for that text, which then returns the associated meaning, presumed to apply to the ambiguity itself. We then present an experiment in which a baseline disambiguation method was compared to four versions of JDI in disambiguating 45 ambiguous strings from NLM's WSD Test Collection. Overall average precision for the highest-scoring JDI version was 0.7873 compared to 0.2492 for the baseline method, and average precision for individual ambiguities was greater than 0.90 for 23 of them (51%), greater than 0.85 for 24 (53%), and greater than 0.65 for 35 (79%). On the basis of these results, we hope to improve performance of JDI and test its use in applications.
  
  Themenfeld: Computerlinguistik
  Wissenschaftsfach: Medizin
  Objekt: Medline ; UMLS
  
  
• 4
  Fushman, D. Demner- => Demner-Fushman, D.: