Titlebook: Database Systems for Advanced Applications; 23rd International C Jian Pei,Yannis Manolopoulos,Jianxin Li Conference proceedings 2018 Spring

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結(jié)束

Novel Approaches to Accelerating the?Convergence Rate of Markov Decision Process for Search Result DP-DIV-kNN method adopts a . nearest neighbor strategy, i.e., discarding the . nearest neighbors of the recently-selected action (document), to reduce the diversification searching space. The MDP-DIV-NTN employs a pre-trained diversification neural tensor network (NTN-DIV) as the evaluation model, an

Tincture

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Interactive Transaction Processing for?In-Memory Database Systemd to schedule transaction conflicts without introducing many overhead; (4) experiments on both the TPC-C and a micro benchmark show that our method achieves better performance than existing solutions.

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Modeling Patient Visit Using Electronic Medical Records for Cost Profile Estimationng clinical approaches only focus on patient’s demographics and historical diagnoses but ignore ample information from clinical records. In this paper, we formulate the problem of patient’s cost profile estimation and use Electronic Medical Records (EMRs) to model patient visit for better estimating

駁船

Learning the Representation of Medical Features for Clinical Pathway Analysis be divided into several stages, usually in units of days. With the explosion of medical data, CP analysis is receiving increasing attention, which provides important support for CP design and optimization. However, these data-driven researches often suffer from the high complexity of medical data,

神化怪物

Adulterate

Publishing Graph Node Strength Histogram with Edge Differential Privacy combines the topological information with the weight distribution of the weighted graph in a natural way. Since an edge in graph data oftentimes represents relationship between two nodes, edge-differential privacy (edge-DP) can protect relationship between two entities from being disclosed. In this

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: Differentially Private Frequent Time-Constrained Sequential Pattern Mininge sequence dataset has been widely studied, in which the transition time between adjacent items should not be too large to form frequent sequential patterns. A wide spectrum of applications can greatly benefit from such patterns, such as movement behavior analysis, targeted advertising, and POI reco