2006 IEEE International Conference on Information Reuse & Integration最新文献_第8页

Software Quality Imputation in the Presence of Noisy Data 存在噪声数据的软件质量估算

2006 IEEE International Conference on Information Reuse & Integration Pub Date : 2006-12-04 DOI: 10.1109/IRI.2006.252462

T. Khoshgoftaar, A. Folleco, J. V. Hulse, Lofton A. Bullard

引用次数: 9

Hybrid Chinese Text Chunking 混合中文文本分块

2006 IEEE International Conference on Information Reuse & Integration Pub Date : 2006-12-04 DOI: 10.1109/IRI.2006.252475

PanPan Liao, Y. Liu, Lin Chen

引用次数: 3

A Flexible Architecture for Integrating Analysis Operations Into a Scientific Data Repository 将分析操作集成到科学数据存储库中的灵活架构

2006 IEEE International Conference on Information Reuse & Integration Pub Date : 2006-12-04 DOI: 10.1109/IRI.2006.252394

Brian Harrington, R. Brazile, K. Swigger

引用次数: 1

Using Markov Chain and Nearest Neighbor Criteria in an Experience Based Study Planning System with Linear Time Search and Scalability 基于马尔可夫链和最近邻准则的线性时间搜索和可扩展性经验学习计划系统

2006 IEEE International Conference on Information Reuse & Integration Pub Date : 2006-12-04 DOI: 10.1109/IRI.2006.252447

Juan Carlos Segura-Ramirez, Willie Chang

{"title":"Using Markov Chain and Nearest Neighbor Criteria in an Experience Based Study Planning System with Linear Time Search and Scalability","authors":"Juan Carlos Segura-Ramirez, Willie Chang","doi":"10.1109/IRI.2006.252447","DOIUrl":"https://doi.org/10.1109/IRI.2006.252447","url":null,"abstract":"Most automated rule-based expert systems developed to aid student study planning and advising have appeared to be ephemeral due to the dynamic property in the ever-changing curricular requirements and rules. We propose a novel case-based study planning system with the search criteria based on the experience-indicated probability in Markov chains and the nearest-neighbor measurement for matches. We provide query results of course sequences to students who need to meet certain constraints such as to graduate within a certain number of academic terms, maintaining a minimal grade-point average, etc., all drawn from past graduate records. The time complexity of computing the nearest-neighbor indices to find the maximum similarity can be very large. Our implementation method achieves a linear-time complexity in both searching and scaling the system. When updating with a new record, each parametric combination represented by a sorted list of the records is linearly looked up, and the new record value is inserted to keep the list sorted. Since each query input is a set of constraints in a pre-determined order, the parametric combinations have an associated sorted list to look up in a one-pass linear process. The first-order Markov chains can also be updated with a linear time complexity whenever a new graduate record is introduced. The probability matrix is first looked up by row and then column, representing a pair of courses taken in two adjacent academic terms, and the look-up time is also linear","PeriodicalId":402255,"journal":{"name":"2006 IEEE International Conference on Information Reuse & Integration","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121958032","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: 0

Labeling Network Event Records for Intrusion Detection in aWireless LAN 针对无线局域网入侵检测的网络事件记录标注

2006 IEEE International Conference on Information Reuse & Integration Pub Date : 2006-12-04 DOI: 10.1109/IRI.2006.252413

T. Khoshgoftaar, Chris Seiffert, Naeem Seliya

{"title":"Labeling Network Event Records for Intrusion Detection in aWireless LAN","authors":"T. Khoshgoftaar, Chris Seiffert, Naeem Seliya","doi":"10.1109/IRI.2006.252413","DOIUrl":"https://doi.org/10.1109/IRI.2006.252413","url":null,"abstract":"A data mining approach to network intrusion detection requires a training dataset of network event records labeled as either normal or an attack type. Since there are too many events to track, such datasets are typically very large. This is particularly so in a WLAN where number of non-wired devices communicating with the WLAN can be too many and adhoc. This creates a problem for the domain expert in labeling all records in the training dataset which is used to train a machine learner. We present a simple approach by which the number of network records the expert has to examine is a relatively small proportion of the given training dataset. A clustering algorithm is used to form relatively coherent groups which the expert examines as a whole to label records as one of four classes: red (definite intrusion), yellow (possibly intrusion), blue (probably normal), and green (definite normal). An ensemble classifier-based data cleansing approach is then used to detect records that were likely mislabeled by the expert. The proposed approach is investigated with a case study of a real-world WLAN. An ensemble classifier-based intrusion detection model built using the labeled training dataset demonstrates the effectiveness of the labeling approach and the good generalization accuracy","PeriodicalId":402255,"journal":{"name":"2006 IEEE International Conference on Information Reuse & Integration","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122383969","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: 3

Automatic Morphological Tagging of Contemporary Uighur Corpus 当代维吾尔语语料库的自动形态标注

2006 IEEE International Conference on Information Reuse & Integration Pub Date : 2006-12-04 DOI: 10.1109/IRI.2006.252474

G. Altenbek

引用次数: 1

Fuzzy Continuous Resource Allocation Mechanisms in Workflow Management Systems 工作流管理系统中的模糊连续资源分配机制

2006 IEEE International Conference on Information Reuse & Integration Pub Date : 2006-12-04 DOI: 10.1109/IRI.2006.252460

Joslaine Cristina Jeske de Freitas, S. Julia, R. Valette

引用次数: 7

Using JPL Micro-Imagers for the Johnson Space Center International Space Station Cell Growth Experiment 使用喷气推进实验室微成像仪进行约翰逊航天中心国际空间站细胞生长实验

2006 IEEE International Conference on Information Reuse & Integration Pub Date : 2006-12-04 DOI: 10.1109/IRI.2006.252384

A. Behar, F. Bruhn, J. Matthews, E. Means

引用次数: 0

Classification of Ships in Surveillance Video 监控视频中的船舶分类

2006 IEEE International Conference on Information Reuse & Integration Pub Date : 2006-12-04 DOI: 10.1109/IRI.2006.252453

Qiming Luo, T. Khoshgoftaar, A. Folleco

引用次数: 18

A Multi-world Intelligent Genetic Algorithm to Interactively Optimize Large-scale TSP 大规模TSP交互优化的多世界智能遗传算法

2006 IEEE International Conference on Information Reuse & Integration Pub Date : 2006-12-04 DOI: 10.1109/IRI.2006.252421

Yoshitaka Sakurai, T. Onoyama, S. Kubota, Yoshihiro Nakamura, S. Tsuruta

引用次数: 19