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)
1Jiang, T. ; Liu, F. ; Chi, Y.: Online information encountering : modeling the process and influencing factors.
In: Journal of documentation. 71(2015) no.6, S.1135-1157.
Abstract: Purpose - Information encountering is the serendipitous acquisition of information that requires low or no involvement and expectation of users. The purpose of this paper is to model the explicit process and the implicit factors of online information encountering, i.e. how and why it occurs. Design/methodology/approach - The critical incident technique was adopted to collect qualitative data from 16 interview participants. They contributed 27 true incidents of online information encountering which were used to identify the key phases of the encountering process. They also commented on the factors that they thought had an influence on the chance of the occurrence of encountering. Findings - The macro-process of information encountering is composed of three phases. First, browsing, searching, or social interaction provides the context for encountering; second, the encountering occurrence consists of three steps - noticing the stimuli, examining the content, and acquiring interesting or useful content; and third, the information encountered will be explored further, saved, used, or shared. The 14 influencing factors of information encountering obtained divide into three clusters. User-related factors include sensitivity, emotions, expertise, attitudes, intentionality, curiosity, activity diversity; information-related factors include type, relevance, quality, visibility, and sources; and environment-related factors include time limits and interface usability. Originality/value - This study engenders useful implications for designing information encountering experience. The changeable nature of some influencing factors suggests that encountering can be elicited through the purposive design of encountering support features or even encountering systems, and the macro-process depicts the natural occurring mechanisms of encountering for the design to follow.
Inhalt: Vgl.: http://www.emeraldinsight.com/doi/abs/10.1108/JD-07-2014-0100.
2Wan, X. ; Liu, F.: Are all literature citations equally important? : automatic citation strength estimation and its applications.
In: Journal of the Association for Information Science and Technology. 65(2014) no.9, S.1929-1938.
Abstract: Literature citation analysis plays a very important role in bibliometrics and scientometrics, such as the Science Citation Index (SCI) impact factor, h-index. Existing citation analysis methods assume that all citations in a paper are equally important, and they simply count the number of citations. Here we argue that the citations in a paper are not equally important and some citations are more important than the others. We use a strength value to assess the importance of each citation and propose to use the regression method with a few useful features for automatically estimating the strength value of each citation. Evaluation results on a manually labeled data set in the computer science field show that the estimated values can achieve good correlation with human-labeled values. We further apply the estimated citation strength values for evaluating paper influence and author influence, and the preliminary evaluation results demonstrate the usefulness of the citation strength values.
3Wan, X. ; Liu, F.: WL-index : leveraging citation mention number to quantify an individual's scientific impact.
In: Journal of the Association for Information Science and Technology. 65(2014) no.12, S.2509-2517.
Abstract: A number of bibliometric indices have been developed to evaluate an individual's scientific impact, and the most popular are the h-index and its variants. However, existing bibliometric indices are computed based on the number of citations received by each article, but they do not consider the frequency with which individual citations are mentioned in an article. We use "citation mention" to denote a unique occurrence of a cited reference mentioned in the citing article, and thus some citations may have more than one mention in an article. According to our analysis of the ACL Anthology Network corpus in the natural language processing field, more than 40% of cited references have been mentioned twice or in corresponding citing articles. We argue that citation mention is a preferable for representing the citation relationships between articles, that is, a reference article mentioned m times in the citing article will be considered to have received m citations, rather than one citation. Based on this assumption, we revise the h-index and propose a new bibliometric index, the WL-index, to evaluation an individual's scientific impact. According to our empirical analysis, the proposed WL-index more accurately discriminates between program committee chairs of reputable conferences and ordinary authors.
4Liu, S. ; Liu, F. ; Yu, C. ; Meng, W.: ¬An effective approach to document retrieval via utilizing WordNet and recognizing phrases.
In: SIGIR'04: Proceedings of the 27th Annual International ACM-SIGIR Conference an Research and Development in Information Retrieval. Ed.: K. Järvelin, u.a. New York, NY : ACM Press, 2004. S.266-272.