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)
1Wang, C. ; Zhao, S. ; Kalra, A. ; Borcea, C. ; Chen, Y.: Predictive models and analysis for webpage depth-level dwell time.
In: Journal of the Association for Information Science and Technology. 69(2018) no.8, S.1007-1022.
Abstract: A half of online display ads are not rendered viewable because the users do not scroll deep enough or spend sufficient time at the page depth where the ads are placed. In order to increase the marketing efficiency and ad effectiveness, there is a strong demand for viewability prediction from both advertisers and publishers. This paper aims to predict the dwell time for a given urn:x-wiley:23301635:media:asi24025:asi24025-math-0001 triplet based on historic data collected by publishers. This problem is difficult because of user behavior variability and data sparsity. To solve it, we propose predictive models based on Factorization Machines and Field-aware Factorization Machines in order to overcome the data sparsity issue and provide flexibility to add auxiliary information such as the visible area of a user's browser. In addition, we leverage the prior dwell time behavior of the user within the current page view, that is, time series information, to further improve the proposed models. Experimental results using data from a large web publisher demonstrate that the proposed models outperform comparison models. Also, the results show that adding time series information further improves the performance.
Inhalt: Vgl.: https://onlinelibrary.wiley.com/doi/10.1002/asi.24025.
2Shen, X.-L. ; Zhang, K.Z.K. ; Zhao, S.J.: Herd behavior in consumers' adoption of online reviews.
In: Journal of the Association for Information Science and Technology. 67(2016) no.11, S.2754-2765.
Abstract: It has been demonstrated that online consumer reviews are an important source of information that affect individuals' purchase decision making. To understand the influence of online reviews, this study extends prior research on information adoption by incorporating the perspective of herd behavior. We develop and empirically test a research model using data collected from an existing book review site. We report 2 major findings. First, argument quality and source credibility predict information usefulness, which affects the adoption of online reviews. Second, we determine that the adoption of online reviews is also influenced by 2 herd factors, namely, discounting own information and imitating others. We further identify the key determinants of these herd factors, including background homophily and attitude homophily. The theoretical and practical implications are discussed.
Inhalt: Vgl.: http://onlinelibrary.wiley.com/doi/10.1002/asi.23602/full.
3Zhao, S.X. ; Zhang, P.L. ; Li, J. ; Tan, A.M. ; Ye, F.Y.: Abstracting the core subnet of weighted networks based on link strengths.
In: Journal of the Association for Information Science and Technology. 65(2014) no.5, S.984-994.
Abstract: Most measures of networks are based on the nodes, although links are also elementary units in networks and represent interesting social or physical connections. In this work we suggest an option for exploring networks, called the h-strength, with explicit focus on links and their strengths. The h-strength and its extensions can naturally simplify a complex network to a small and concise subnetwork (h-subnet) but retains the most important links with its core structure. Its applications in 2 typical information networks, the paper cocitation network of a topic (the h-index) and 5 scientific collaboration networks in the field of "water resources," suggest that h-strength and its extensions could be a useful choice for abstracting, simplifying, and visualizing a complex network. Moreover, we observe that the 2 informetric models, the Glänzel-Schubert model and the Hirsch model, roughly hold in the context of the h-strength for the collaboration networks.
4Zhao, S.X. ; Ye, F.Y.: Power-law link strength distribution in paper cocitation networks.
In: Journal of the American Society for Information Science and Technology. 64(2013) no.7, S.1480-1489.
Abstract: A network is constructed by nodes and links, thus the node degree and the link strength appear as underlying quantities in network analysis. While the power-law distribution of node degrees is verified as a basic feature of numerous real networks, we investigate whether the link strengths follow the power-law distribution in weighted networks. After testing 12 different paper cocitation networks with 2 methods, fitting in double-log scales and the Kolmogorov-Smirnov test (K-S test), we observe that, in most cases, the link strengths also follow the approximate power-law distribution. The results suggest that the power-law type distribution could emerge not only in nodes and informational entities, but also in links and informational connections.
5Zhao, S.X. ; Tan, A.M. ; Ye, F.Y.: Distributive h-indices for measuring multilevel impact.
In: Journal of the American Society for Information Science and Technology. 63(2012) no.10, S.2074-2086.
Abstract: For measuring multilevel impact, we introduce the distributive h-indices, which balance two important components (breadth and strength) of multilevel impact at various citing levels. After exploring the theoretical properties of these indices, we studied two cases: 57 library and information science (LIS) journals and social science research in 38 European countries/territories. Results reveal that there are approximate power-law relations between distributive h-indices and some underlying citation indicators, such as total citations, total citing entities, and the h-index. Distributive h-indices provide comprehensive measures for multilevel impact, and lead to a potential tool for citation analysis, particularly at aggregative levels.
6Belkin, N.J. ; Chang, S.J. ; Downs, T. ; Saracevic, T. ; Zhao, S.: Taking account of user tasks, goals and behavior for the design of online public access catalogs.
In: ASIS'90: Information in the year 2000: from research to application. Proc. 33rd Annual Meeting of the American Society for Information Science. Medford, NJ : Learned Information Inc., 1990. S.69-79.