Titlebook: Web Information Systems Engineering; WISE 2019 Workshop, Leong Hou U,Jian Yang,Xin Huang Conference proceedings 2020 Springer Nature Singa

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ReInCre: Enhancing Collaborative Filtering Recommendations by Incorporating User Rating Credibilityo enhance the recommendation performance. The credibility values of users are calculated according to their rating behavior and they are utilized in discovering the neighbors (Code available at .). To the best of our knowledge, it is the first work to incorporate the rating credibility of users in a

limber

演繹

commute

Efficient Privacy-Preserving Skyline Queries over Outsourced Cloudeavy storage and management tasks to the cloud server. However, sensitive data, such as medical or financial records, should be encrypted before uploading to the cloud server. Unfortunately, this will introduce new challenges to data utilization. In this paper, we study the problem of skyline querie

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Efficient Privacy-Preserving Skyline Queries over Outsourced Cloudeavy storage and management tasks to the cloud server. However, sensitive data, such as medical or financial records, should be encrypted before uploading to the cloud server. Unfortunately, this will introduce new challenges to data utilization. In this paper, we study the problem of skyline querie

BARB

Leveraging Pattern Mining Techniques for Efficient Keyword Search on Data Graphsta graphs and exploration. However, keyword search faces the so called performance scalability problem which hinders its widespread use on data graphs..In this paper, we address the performance scalability problem by leveraging techniques developed for graph pattern mining. We focus on avoiding the

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Range Nearest Neighbor Query with the Direction Constrainty). Traditional DCNN query retrieves the top-. nearest neighbors within an angular range. Our Range-DCNN query finds all nearest neighbors within an angular range for all points in a rectangle. Dissimilar to the traditional DCNN query, the user’s location in the Range-DCNN query is abstracted to a r