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)
1Tang, L. ; Hu, G. ; Liu, W.: Funding acknowledgment analysis : queries and caveats.
In: Journal of the Association for Information Science and Technology. 68(2017) no.3, S.790-794.
Abstract: Thomson Reuters's Web of Science (WoS) began systematically collecting acknowledgment information in August 2008. Since then, bibliometric analysis of funding acknowledgment (FA) has been growing and has aroused intense interest and attention from both academia and policy makers. Examining the distribution of FA by citation index database, by language, and by acknowledgment type, we noted coverage limitations and potential biases in each analysis. We argue that despite its great value, bibliometric analysis of FA should be used with caution.
Inhalt: Vgl.: http://onlinelibrary.wiley.com/doi/10.1002/asi.23713/full.
2Xu, F. ; Liu, W.B. ; Mingers, J.: New journal classification methods based on the global h-index.
In: Information processing and management. 51(2015) no.2, S.50-61.
Abstract: In this work we develop new journal classification methods based on the h-index. The introduction of the h-index for research evaluation has attracted much attention in the bibliometric study and research quality evaluation. The main purpose of using an h-index is to compare the index for different research units (e.g. researchers, journals, etc.) to differentiate their research performance. However the h-index is defined by only comparing citations counts of one's own publications, it is doubtful that the h index alone should be used for reliable comparisons among different research units, like researchers or journals. In this paper we propose a new global h-index (Gh-index), where the publications in the core are selected in comparison with all the publications of the units to be evaluated. Furthermore, we introduce some variants of the Gh-index to address the issue of discrimination power. We show that together with the original h-index, they can be used to evaluate and classify academic journals with some distinct advantages, in particular that they can produce an automatic classification into a number of categories without arbitrary cut-off points. We then carry out an empirical study for classification of operations research and management science (OR/MS) journals using this index, and compare it with other well-known journal ranking results such as the Association of Business Schools (ABS) Journal Quality Guide and the Committee of Professors in OR (COPIOR) ranking lists.
Inhalt: Vgl.: doi: 10.1016/j.ipm.2014.10.011.
3Liu, W. ; Dog(an, R.I. ; Kim, S. ; Comeau, D.C. ; Kim, W. ; Yeganova, L. ; Lu, Z. ; Wilbur, W.J.: Author name disambiguation for PubMed.
In: Journal of the Association for Information Science and Technology. 65(2014) no.4, S.765-781.
Abstract: Log analysis shows that PubMed users frequently use author names in queries for retrieving scientific literature. However, author name ambiguity may lead to irrelevant retrieval results. To improve the PubMed user experience with author name queries, we designed an author name disambiguation system consisting of similarity estimation and agglomerative clustering. A machine-learning method was employed to score the features for disambiguating a pair of papers with ambiguous names. These features enable the computation of pairwise similarity scores to estimate the probability of a pair of papers belonging to the same author, which drives an agglomerative clustering algorithm regulated by 2 factors: name compatibility and probability level. With transitivity violation correction, high precision author clustering is achieved by focusing on minimizing false-positive pairing. Disambiguation performance is evaluated with manual verification of random samples of pairs from clustering results. When compared with a state-of-the-art system, our evaluation shows that among all the pairs the lumping error rate drops from 10.1% to 2.2% for our system, while the splitting error rises from 1.8% to 7.7%. This results in an overall error rate of 9.9%, compared with 11.9% for the state-of-the-art method. Other evaluations based on gold standard data also show the increase in accuracy of our clustering. We attribute the performance improvement to the machine-learning method driven by a large-scale training set and the clustering algorithm regulated by a name compatibility scheme preferring precision. With integration of the author name disambiguation system into the PubMed search engine, the overall click-through-rate of PubMed users on author name query results improved from 34.9% to 36.9%.
4Wong, W. ; Liu, W. ; Bennamoun, M.: Ontology learning from text : a look back and into the future.
Abstract: Ontologies are often viewed as the answer to the need for inter-operable semantics in modern information systems. The explosion of textual information on the "Read/Write" Web coupled with the increasing demand for ontologies to power the Semantic Web have made (semi-)automatic ontology learning from text a very promising research area. This together with the advanced state in related areas such as natural language processing have fuelled research into ontology learning over the past decade. This survey looks at how far we have come since the turn of the millennium, and discusses the remaining challenges that will define the research directions in this area in the near future.
Inhalt: Pre-publication version für: ACM Computing Surveys, Vol. X, No. X, Article X, Publication date: X 2011.
Themenfeld: Wissensrepräsentation ; Computerlinguistik
5Samoylenko, I. ; Chao, T.-C. ; Liu, W.-C. ; Chen, C.-M.: Visualizing the scientific world and its evolution.
In: Journal of the American Society for Information Science and Technology. 57(2006) no.11, S.1461-1469.
Abstract: We propose an approach to visualizing the scientific world and its evolution by constructing minimum spanning trees (MSTs) and a two-dimensional map of scientific journals using the database of the Science Citation Index (SCI) during 1994-2001. The structures of constructed MSTs are consistent with the sorting of SCI categories. The map of science is constructed based on our MST results. Such a map shows the relation among various knowledge clusters and their citation properties. The temporal evolution of the scientific world can also be delineated in the map. In particular, this map clearly shows a linear structure of the scientific world, which contains three major domains including physical sciences, life sciences, and medical sciences. The interaction of various knowledge fields can be clearly seen from this scientific world map. This approach can be applied to various levels of knowledge domains.
Themenfeld: Informetrie ; Visualisierung
Objekt: Science Citation Index ; Map of Science
6Liu, W. ; Weichselbraun, A. ; Scharl, A. ; Chang, E.: Semi-automatic ontology extension using spreading activation.
In: Journal of universal knowledge management. 0(2005) no.1, S.50-58.
Abstract: This paper describes a system to semi-automatically extend and refine ontologies by mining textual data from the Web sites of international online media. Expanding a seed ontology creates a semantic network through co-occurrence analysis, trigger phrase analysis, and disambiguation based on the WordNet lexical dictionary. Spreading activation then processes this semantic network to find the most probable candidates for inclusion in an extended ontology. Approaches to identifying hierarchical relationships such as subsumption, head noun analysis and WordNet consultation are used to confirm and classify the found relationships. Using a seed ontology on "climate change" as an example, this paper demonstrates how spreading activation improves the result by naturally integrating the mentioned methods.
Themenfeld: Data Mining
7Ma, Y.-L. ; Liu, W.: Digital resources and metadata application in Shanghai Library.
In: Cataloging and classification quarterly. 36(2003) nos.3/4, S.57-70.
Abstract: The Shanghai Digital Library (SDL) is a component of the China Digital Library Project. This paper introduces the framework, goals, and contents of the China Digital Library Project. The vision, mission, system architecture, digital resources, and related major technology of the SDL project are discussed. Also, the background of the Chinese metadata application and the metadata scheme of the SDL are described, and the features of metadata application in practical cases are analyzed. Finally, current issues of metadata application and their solutions are suggested.
Inhalt: Beitrag in einem Themenheft "Electronic cataloging: AACR2 and metadata for serials and monographs"
Anmerkung: Vgl. auch: http://catalogingandclassificationquarterly.com/
Themenfeld: Formalerschließung ; Metadaten
Land/Ort: China ; Shanghai