Titlebook: Web-Age Information Management; 17th International C Bin Cui,Nan Zhang,Dexi Liu Conference proceedings 2016 Springer International Publishi

Hangar

Preserving the ,-Reachability When Anonymizing Social Networks, and keep it unchanged during anonymization. We show that .-RPA can efficiently find such a subgraph and anonymize the releasing graph with low information loss. Extensive experiments on real datasets illustrate that anonymized social networks generated by our method can be used to answer .-reachable queries with high accuracy.

Vital-Signs

Preserving the ,-Reachability When Anonymizing Social Networks, and keep it unchanged during anonymization. We show that .-RPA can efficiently find such a subgraph and anonymize the releasing graph with low information loss. Extensive experiments on real datasets illustrate that anonymized social networks generated by our method can be used to answer .-reachable queries with high accuracy.

Plaque

蝕刻

Personalized Location Anonymity - A Kernel Density Estimation Approache selected based on both the entropy of personal visit probability and the area of Cloaking Region (CR). We conduct extensive experiments on the real dataset to verify the performance of privacy protection degree, where the privacy properties are measured by the location information entropy and the area of CR.

冥想后

Detecting Data-model-oriented Anomalies in Parallel Business Processallel-process model and the data model. Then, an anomaly detection method under the divide-and-conquer framework is proposed to ensure efficiency in detecting anomalies in business processes. Both theoretical analysis and experimental results prove this method to be highly efficient and effective in detecting data model oriented anomalies.

Incorporate

Detecting Data-model-oriented Anomalies in Parallel Business Processallel-process model and the data model. Then, an anomaly detection method under the divide-and-conquer framework is proposed to ensure efficiency in detecting anomalies in business processes. Both theoretical analysis and experimental results prove this method to be highly efficient and effective in detecting data model oriented anomalies.

Presbycusis

Learning User Credibility on Aspects from Review Textse aspect ratings are assigned by mining semantic polarity. Then, an iteration algorithm is designed for estimating credibilities by considering the consistency between individual ratings and overall ratings on aspects. Finally, experiments on the real dataset demonstrate that our method outperforms baseline systems.

terazosin

Learning User Credibility on Aspects from Review Textse aspect ratings are assigned by mining semantic polarity. Then, an iteration algorithm is designed for estimating credibilities by considering the consistency between individual ratings and overall ratings on aspects. Finally, experiments on the real dataset demonstrate that our method outperforms baseline systems.

agglomerate

Herpetologist