Titlebook: Database Systems for Advanced Applications; 21st International C Shamkant B. Navathe,Weili Wu,Hui Xiong Conference proceedings 2016 Springe

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書目名稱Database Systems for Advanced Applications讀者反饋學(xué)科排名

Guileless

https://doi.org/10.1007/978-3-319-32049-6Big data; Data mining and knowledge discovery; Database management; Evolutionary machine learning; Infor

圓錐

MOAN

Intentions and the Doctrine of Double Effectlarity search, entity profiling and linkage. Most existing work focus on using the main features common to all. While this approach makes sense in settings where commonality is of primary interest, there are many scenarios as important where uncommon and discriminative features are more useful. To a

Laconic

Oren Asman,Yechiel Michael Barilantopic or event prediction models have been proposed in the past few years, researches that focus on the single tweet prediction just emerge recently. In this paper, we propose STH-Bass, a Spatial and Temporal Heterogeneous Bass model derived from economic field, to predict the popularity of a single

字形刻痕

字形刻痕

羽飾

Palgrave European Film and Media Studiesgregation queries on a set of lists plays an increasingly important role in these domains. Unfortunately the existing solutions, such as threshold-style (TA-style) algorithms, do not guarantee superior performance on a large number of lists. In this paper, we introduce a merge-based strategy, called

圓木可阻礙

https://doi.org/10.1007/978-3-319-89827-8onnecting nodes through a sequence of heterogeneous edges, representing different kinds of semantic relations among nodes. Meta-paths are good mechanisms to improve the quality of graph analysis on heterogeneous information networks. This paper presents an iceberg cube framework for heterogeneous in

unstable-angina

https://doi.org/10.1007/978-3-319-89827-8ived significant research attention in the past few years. However, we realise that the state-of-the-art algorithm, SLICE, accesses many objects that do not contribute to its . results when running the filtering phase, which deteriorates the query performance. In this paper, we propose a novel R.NN