Proceedings of the 2017 ACM on Conference on Information and Knowledge Management最新文献_第6页

Semantic Rules for Machine Diagnostics: Execution and Management 机器诊断的语义规则:执行和管理

Proceedings of the 2017 ACM on Conference on Information and Knowledge Management Pub Date : 2017-11-06 DOI: 10.1145/3132847.3133159

E. Kharlamov, Ognjen Savkovic, Guohui Xiao, R. Peñaloza, G. Mehdi, M. Roshchin, Ian Horrocks

引用次数: 13

From Fingerprint to Footprint: Revealing Physical World Privacy Leakage by Cyberspace Cookie Logs 从指纹到足迹:通过网络空间Cookie日志揭示物理世界隐私泄露

Proceedings of the 2017 ACM on Conference on Information and Knowledge Management Pub Date : 2017-11-06 DOI: 10.1145/3132847.3132998

Huandong Wang, Chen Gao, Yong Li, Zhi-Li Zhang, Depeng Jin

{"title":"From Fingerprint to Footprint: Revealing Physical World Privacy Leakage by Cyberspace Cookie Logs","authors":"Huandong Wang, Chen Gao, Yong Li, Zhi-Li Zhang, Depeng Jin","doi":"10.1145/3132847.3132998","DOIUrl":"https://doi.org/10.1145/3132847.3132998","url":null,"abstract":"It is well-known that online services resort to various cookies to track users through users' online service identifiers (IDs) - in other words, when users access online services, various \"fingerprints\" are left behind in the cyberspace. As they roam around in the physical world while accessing online services via mobile devices, users also leave a series of \"footprints\" -- i.e., hints about their physical locations - in the physical world. This poses a potent new threat to user privacy: one can potentially correlate the \"fingerprints\" left by the users in the cyberspace with \"footprints\" left in the physical world to infer and reveal leakage of user physical world privacy, such as frequent user locations or mobility trajectories in the physical world - we refer to this problem as user physical world privacy leakage via user cyberspace privacy leakage. In this paper we address the following fundamental question: what kind - and how much - of user physical world privacy might be leaked if we could get hold of such diverse network datasets even without any physical location information. In order to conduct an in-depth investigation of these questions, we utilize the network data collected via a DPI system at the routers within one of the largest Internet operator in Shanghai, China over a duration of one month. We decompose the fundamental question into the three problems: i) linkage of various online user IDs belonging to the same person via mobility pattern mining; ii) physical location classification via aggregate user mobility patterns over time; and iii) tracking user physical mobility. By developing novel and effective methods for solving each of these problems, we demonstrate that the question of user physical world privacy leakage via user cyberspace privacy leakage is not hypothetical, but indeed poses a real potent threat to user privacy.","PeriodicalId":20449,"journal":{"name":"Proceedings of the 2017 ACM on Conference on Information and Knowledge Management","volume":"137 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2017-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76772906","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 16

Conflict of Interest Declaration and Detection System in Heterogeneous Networks 异构网络中的利益冲突声明与检测系统

Proceedings of the 2017 ACM on Conference on Information and Knowledge Management Pub Date : 2017-11-06 DOI: 10.1145/3132847.3133134

Siyuan Wu, Leong Hou U, S. Bhowmick, Wolfgang Gatterbauer

引用次数: 11

Hierarchical Module Classification in Mixed-initiative Conversational Agent System 混合主动会话代理系统中的分层模块分类

Proceedings of the 2017 ACM on Conference on Information and Knowledge Management Pub Date : 2017-11-06 DOI: 10.1145/3132847.3133185

Sia Xin Yun Suzanna, A. Li

引用次数: 0

Fast Algorithms for Pareto Optimal Group-based Skyline 基于Pareto最优群的Skyline快速算法

Proceedings of the 2017 ACM on Conference on Information and Knowledge Management Pub Date : 2017-11-06 DOI: 10.1145/3132847.3132950

Wenhui Yu, Zheng Qin, Jinfei Liu, Li Xiong, Xu Chen, Huidi Zhang

{"title":"Fast Algorithms for Pareto Optimal Group-based Skyline","authors":"Wenhui Yu, Zheng Qin, Jinfei Liu, Li Xiong, Xu Chen, Huidi Zhang","doi":"10.1145/3132847.3132950","DOIUrl":"https://doi.org/10.1145/3132847.3132950","url":null,"abstract":"Skyline, aiming at finding a Pareto optimal subset of points in a multi-dimensional dataset, has gained great interest due to its extensive use for multi-criteria analysis and decision making. Skyline consists of all points that are not dominated by, or not worse than other points. It is a candidate set of optimal solution, which depends on a specific evaluation criterion for optimum. However, conventional skyline queries, which return individual points, are inadequate in group querying case since optimal combinations are required. To address this gap, we study the skyline computation in group case and propose fast methods to find the group-based skyline (G-skyline), which contains Pareto optimal groups. For computing the front k skyline layers, we lay out an efficient approach that does the search concurrently on each dimension and investigates each point in subspace. After that, we present a novel structure to construct the G-skyline with a queue of combinations of the first-layer points. Experimental results show that our algorithms are several orders of magnitude faster than the previous work.","PeriodicalId":20449,"journal":{"name":"Proceedings of the 2017 ACM on Conference on Information and Knowledge Management","volume":"46 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2017-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86917147","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 26

Linking News across Multiple Streams for Timeliness Analysis 链接新闻跨多个流的时效性分析

Proceedings of the 2017 ACM on Conference on Information and Knowledge Management Pub Date : 2017-11-06 DOI: 10.1145/3132847.3132988

I. Mele, Seyed Ali Bahrainian, F. Crestani

引用次数: 10

Metacrate: Organize and Analyze Millions of Data Profiles Metacrate:组织和分析数以百万计的数据配置文件

Proceedings of the 2017 ACM on Conference on Information and Knowledge Management Pub Date : 2017-11-06 DOI: 10.1145/3132847.3133180

Sebastian Kruse, David Hahn, Marius Walter, Felix Naumann

{"title":"Metacrate: Organize and Analyze Millions of Data Profiles","authors":"Sebastian Kruse, David Hahn, Marius Walter, Felix Naumann","doi":"10.1145/3132847.3133180","DOIUrl":"https://doi.org/10.1145/3132847.3133180","url":null,"abstract":"Databases are one of the great success stories in IT. However, they have been continuously increasing in complexity, hampering operation, maintenance, and upgrades. To face this complexity, sophisticated methods for schema summarization, data cleaning, information integration, and many more have been devised that usually rely on data profiles, such as data statistics, signatures, and integrity constraints. Such data profiles are often extracted by automatic algorithms, which entails various problems: The profiles can be unfiltered and huge in volume; different profile types require different complex data structures; and the various profile types are not integrated with each other. We introduce Metacrate, a system to store, organize, and analyze data profiles of relational databases, thereby following the proven design of databases. In particular, we (i) propose a logical and a physical data model to store all kinds of data profiles in a scalable fashion; (ii) describe an analytics layer to query, integrate, and analyze the profiles efficiently; and (iii) implement on top a library of established algorithms to serve use cases, such as schema discovery, database refactoring, and data cleaning.","PeriodicalId":20449,"journal":{"name":"Proceedings of the 2017 ACM on Conference on Information and Knowledge Management","volume":"19 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2017-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87698284","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 14

Computing Betweenness Centrality in B-hypergraphs 计算b超图的中间中心性

Proceedings of the 2017 ACM on Conference on Information and Knowledge Management Pub Date : 2017-11-06 DOI: 10.1145/3132847.3133093

Kwang Hee Lee, Myoung-Ho Kim

引用次数: 1

AliMe Assist: An Intelligent Assistant for Creating an Innovative E-commerce Experience AliMe Assist:打造创新电子商务体验的智能助手

Proceedings of the 2017 ACM on Conference on Information and Knowledge Management Pub Date : 2017-11-06 DOI: 10.1145/3132847.3133169

Feng-Lin Li, Minghui Qiu, Haiqing Chen, Xiongwei Wang, Xing Gao, Jun Huang, Juwei Ren, Zhongzhou Zhao, Weipeng Zhao, Lei Wang, Guwei Jin, Wei Chu

引用次数: 99

pm-SCAN: an I/O Efficient Structural Clustering Algorithm for Large-scale Graphs pm-SCAN:大规模图形的I/O高效结构聚类算法

Proceedings of the 2017 ACM on Conference on Information and Knowledge Management Pub Date : 2017-11-06 DOI: 10.1145/3132847.3133121

J. Seo, Myoung-Ho Kim

引用次数: 11