2016 IEEE 17th International Conference on Information Reuse and Integration (IRI)最新文献_第2页

Semantic Concept Detection Using Weighted Discretization Multiple Correspondence Analysis for Disaster Information Management 基于加权离散化多对应分析的语义概念检测在灾害信息管理中的应用

2016 IEEE 17th International Conference on Information Reuse and Integration (IRI) Pub Date : 2016-07-28 DOI: 10.1109/IRI.2016.82

Samira Pouyanfar, Shu‐Ching Chen

引用次数: 13

Spekl: A Layered System for Specification Authoring, Sharing, and Usage Spekl:规范创作、共享和使用的分层系统

2016 IEEE 17th International Conference on Information Reuse and Integration (IRI) Pub Date : 2016-07-28 DOI: 10.1109/IRI.2016.24

J. Singleton, Gary T. Leavens

引用次数: 0

Algorithmic Decision Support for Personalized Education (Invited Paper) 个性化教育的算法决策支持(特邀论文)

2016 IEEE 17th International Conference on Information Reuse and Integration (IRI) Pub Date : 2016-07-28 DOI: 10.1109/IRI.2016.32

Tyler Morrow, Sahra Sedigh Sarvestani, A. Hurson

引用次数: 4

Monitoring Classification Blindspots to Detect Drifts from Unlabeled Data 监测分类盲点以检测未标记数据的漂移

2016 IEEE 17th International Conference on Information Reuse and Integration (IRI) Pub Date : 2016-07-28 DOI: 10.1109/IRI.2016.26

Tegjyot Singh Sethi, M. Kantardzic, Elaheh Arabmakki

{"title":"Monitoring Classification Blindspots to Detect Drifts from Unlabeled Data","authors":"Tegjyot Singh Sethi, M. Kantardzic, Elaheh Arabmakki","doi":"10.1109/IRI.2016.26","DOIUrl":"https://doi.org/10.1109/IRI.2016.26","url":null,"abstract":"Machine learning models deployed in real world applications, operate in a dynamic environment where the data distribution can change constantly. These changes, called concept drifts, cause the performance of the learned model to degrade over time. As such it is essential to detect and adapt to changes in the data, for the model to be of any real use. While, model adaptation requires labeled data (for retraining), the detection process does not have to. Labeling data is time consuming and expensive, and if data changes are infrequent, most of the labeling effort, spent on verification, is wasted. In this paper, an ensemble based detection method is proposed, which tracks the number of samples in the critical disagreement regions of the ensemble, to detect concept drift from unlabeled data. The proposed algorithm, is-distribution and model independent, unsupervised and can be used in an online incremental fashion. Experimental analysis on 4 real world concept drift datasets shows that the proposed methodology gives high prediction performance, low false alarm rate and uses only 11.3% overall labeling, on average.","PeriodicalId":319129,"journal":{"name":"2016 IEEE 17th International Conference on Information Reuse and Integration (IRI)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121765735","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

General Methods for Access Control Policy Verification (Application Paper) 访问控制策略验证的一般方法(申请文件)

2016 IEEE 17th International Conference on Information Reuse and Integration (IRI) Pub Date : 2016-07-28 DOI: 10.1109/IRI.2016.49

Vincent C. Hu, D. R. Kuhn

{"title":"General Methods for Access Control Policy Verification (Application Paper)","authors":"Vincent C. Hu, D. R. Kuhn","doi":"10.1109/IRI.2016.49","DOIUrl":"https://doi.org/10.1109/IRI.2016.49","url":null,"abstract":"Access control systems are among the most critical of computer security components. Faulty policies, misconfigurations, or flaws in software implementations can result in serious vulnerabilities. To formally and precisely capture the security properties that access control should adhere to, access control models are usually written, bridging the gap in abstraction between policies and mechanisms. Identifying discrepancies between policy specifications and their intended function is crucial because correct implementation and enforcement of policies by applications is based on the premise that the policy specifications are correct. As a result, policy specifications represented by models must undergo rigorous verification and validation through systematic verification and testing to ensure that the policy specifications truly encapsulate the desires of the policy authors. Verifying the conformance of access control policies and models is a non-trivial and critical task, and one important aspect of such verification is to formally check the inconsistency and incompleteness of the model and safety requirements of the policy, because an access control model and its implementation do not necessarily explicitly express the policy, which can also be implicitly embedded by mixing with direct access constraints or other access control models.","PeriodicalId":319129,"journal":{"name":"2016 IEEE 17th International Conference on Information Reuse and Integration (IRI)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128151297","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: 2

Reusing Software Libraries Using Semantic Graphs 使用语义图重用软件库

2016 IEEE 17th International Conference on Information Reuse and Integration (IRI) Pub Date : 2016-07-28 DOI: 10.1109/IRI.2016.79

Awny Alnusair, Majdi Rawashdeh, Mohammed F. Alhamid, M. A. Hossain, Muhammad Ghulam

引用次数: 3

A Data Driven Approach for the Science of Cyber Security: Challenges and Directions 网络安全科学的数据驱动方法:挑战与方向

2016 IEEE 17th International Conference on Information Reuse and Integration (IRI) Pub Date : 2016-07-28 DOI: 10.1109/IRI.2016.10

B. Thuraisingham, Murat Kantarcioglu, Kevin W. Hamlen, L. Khan, Timothy W. Finin, A. Joshi, T. Oates, E. Bertino

引用次数: 23

Knowledge Induction Based on Randomization in Case-Based Reasoning 案例推理中基于随机化的知识归纳

2016 IEEE 17th International Conference on Information Reuse and Integration (IRI) Pub Date : 2016-07-28 DOI: 10.1109/IRI.2016.80

T. Bouabana-Tebibel, S. Rubin, Asmaa Chebba, Sofiane Bediar, Syphax Iskounen

引用次数: 10

Predicting Cancer Relapse with Clinical Data: A Survey of Current Techniques 用临床数据预测癌症复发:当前技术综述

2016 IEEE 17th International Conference on Information Reuse and Integration (IRI) Pub Date : 2016-07-28 DOI: 10.1109/IRI.2016.56

Aaron N. Richter, T. Khoshgoftaar

引用次数: 3

A Risk-Benefit Driven Architecture for Personal Data Release (Invited Paper) 以风险-利益为导向的个人资料公布架构(诚邀论文)

2016 IEEE 17th International Conference on Information Reuse and Integration (IRI) Pub Date : 2016-07-28 DOI: 10.1109/IRI.2016.14

B. C. Singh, B. Carminati, E. Ferrari

引用次数: 6