In: The Semantic Web – ISWC 2019, 2019, p. 453-469
Collaborative Knowledge Graph platforms allow humans and automated scripts to collaborate in creating, updating and interlinking entities and facts. To ensure both the completeness of the data as well as a uniform coverage of the different topics, it is crucial to identify underrepresented classes in the Knowledge Graph. In this paper, we tackle this problem by developing statistical techniques...
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In: Information Sciences, 2019, vol. 488, p. 257–271
When users search online for content, they are constantly exposed to rankings. For example, web search results are presented as a ranking of relevant websites, and online bookstores often show us lists of best-selling books. While popularity-based ranking algorithms (like Google’s PageRank) have been extensively studied in previous works, we still lack a clear understanding of their...
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In: Journal of Informetrics, 2019, vol. 13, no. 2, p. 717–725
Identifying the future influential papers among the newly published ones is an important yet challenging issue in bibliometrics. As newly published papers have no or limited citation history, linear extrapolation of their citation counts—which is motivated by the well-known preferential attachment mechanism—is not applicable. We translate the recently introduced notion of discoverers to...
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In: Personal and Ubiquitous Computing, 2014, vol. 18, no. 5, p. 1201-1211
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In: Journal of Time Series Econometrics, 2016, vol. 8, no. 2, p. 155-192
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In: Personal and Ubiquitous Computing, 2014, vol. 18, no. 5, p. 1047-1060
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In: International Journal of Legal Medicine, 2014, vol. 128, no. 4, p. 615-620
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In: IEEE Transactions on Knowledge and Data Engineering, 2019, vol. 31, no. 3, p. 507–520
Personalized recommendation is crucial to help users find pertinent information. It often relies on a large collection of user data, in particular users' online activity (e.g., tagging/rating/checking-in) on social media, to mine user preference. However, releasing such user activity data makes users vulnerable to inference attacks, as private data (e.g., gender) can often be inferred from...
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In: Entropy, 2019, vol. 21, no. 1, p. 39
GDP is a classic indicator of the extent of national economic development. Research based on the World Trade Network has found that a country’s GDP depends largely on the products it exports. In order to increase the competitiveness of a country and further increase its GDP, a crucial issue is finding the right direction to upgrade the industry so that the country can enhance its...
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In: International Journal of Electronic Commerce, 2019, vol. 23, no. 1, p. 85–109
The recent financial network analysis approach reveals that the topologies of financial markets have an important influence on market dynamics. However, the majority of existing Finance Big Data networks are built as undirected networks without information on the influence directions among prices. Rather than understanding the correlations, this research applies the Granger causality test to...
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