NAFIPS 2007 - 2007 Annual Meeting of the North American Fuzzy Information Processing Society最新文献_第6页

Fuzzy Classification of Genome Sequences Prior to Assembly Based on Similarity Measures 基于相似性度量的基因组序列装配前模糊分类

NAFIPS 2007 - 2007 Annual Meeting of the North American Fuzzy Information Processing Society Pub Date : 2007-06-24 DOI: 10.1109/NAFIPS.2007.383864

S. Nasser, G. Vert, A. Breland, M. Nicolescu

引用次数: 1

An Automated Domain-Specific Answer Ontology Construction 一个自动化的领域特定答案本体构建

NAFIPS 2007 - 2007 Annual Meeting of the North American Fuzzy Information Processing Society Pub Date : 2007-06-24 DOI: 10.1109/NAFIPS.2007.383868

Wei-Min Ko, Huan-ChungLi

{"title":"An Automated Domain-Specific Answer Ontology Construction","authors":"Wei-Min Ko, Huan-ChungLi","doi":"10.1109/NAFIPS.2007.383868","DOIUrl":"https://doi.org/10.1109/NAFIPS.2007.383868","url":null,"abstract":"Recently, with the fast development of interactive information sharing on the internet, the query-oriented answer search services are more and more popular, such as Yahoo Answers, Google Answers and so on. Their common advantages are high precision, domain-specific search, clear format, etc. However towards domain-specific search, people usually are unable to determine suitable concept terms as queries to submit on account of their lack of domain knowledge. In this paper, we propose an approach for constructing a domain-specific answer ontology automatically in respect of Chinese queries to solve the said problem. First, queries and their answers are collected from a web search space. Second, for extracting implicated concept terms from collected queries and answers, the CKIP system is utilized to make a Chinese part-of-speech tagging procedure to segment. Thirdly, use a similarity measure to converge duplicate queries with their corresponding answers and take fuzzy clustering method and degree of membership to describe the relationships between converged queries and their corresponding answers. Finally, to generate a domain-specific ontology is based on an improved hierarchical agglomerative clustering algorithm to hierarchically group queries.","PeriodicalId":292853,"journal":{"name":"NAFIPS 2007 - 2007 Annual Meeting of the North American Fuzzy Information Processing Society","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133937237","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

Using Consensus to Measure Weighted Targeted Agreement 用共识衡量加权目标协议

NAFIPS 2007 - 2007 Annual Meeting of the North American Fuzzy Information Processing Society Pub Date : 2007-06-24 DOI: 10.1109/NAFIPS.2007.383806

W. J. Tastle, M. J. Wierman

引用次数: 15

Applying Novel Resampling Strategies To Software Defect Prediction 重新采样策略在软件缺陷预测中的应用

NAFIPS 2007 - 2007 Annual Meeting of the North American Fuzzy Information Processing Society Pub Date : 2007-06-24 DOI: 10.1109/NAFIPS.2007.383813

Lourdes Pelayo, S. Dick

{"title":"Applying Novel Resampling Strategies To Software Defect Prediction","authors":"Lourdes Pelayo, S. Dick","doi":"10.1109/NAFIPS.2007.383813","DOIUrl":"https://doi.org/10.1109/NAFIPS.2007.383813","url":null,"abstract":"Due to the tremendous complexity and sophistication of software, improving software reliability is an enormously difficult task. We study the software defect prediction problem, which focuses on predicting which modules will experience a failure during operation. Numerous studies have applied machine learning to software defect prediction; however, skewness in defect-prediction datasets usually undermines the learning algorithms. The resulting classifiers will often never predict the faulty minority class. This problem is well known in machine learning and is often referred to as learning from unbalanced datasets. We examine stratification, a widely used technique for learning unbalanced data that has received little attention in software defect prediction. Our experiments are focused on the SMOTE technique, which is a method of over-sampling minority-class examples. Our goal is to determine if SMOTE can improve recognition of defect-prone modules, and at what cost. Our experiments demonstrate that after SMOTE resampling, we have a more balanced classification. We found an improvement of at least 23% in the average geometric mean classification accuracy on four benchmark datasets.","PeriodicalId":292853,"journal":{"name":"NAFIPS 2007 - 2007 Annual Meeting of the North American Fuzzy Information Processing Society","volume":"206 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133892509","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: 136

Heuristic Algorithm for Interpretation of Non-Atomic Categorical Attributes in Similarity-based Fuzzy Databases Scalability Evaluation 基于相似度的模糊数据库可扩展性评价中非原子分类属性解释的启发式算法

NAFIPS 2007 - 2007 Annual Meeting of the North American Fuzzy Information Processing Society Pub Date : 2007-06-24 DOI: 10.1109/NAFIPS.2007.383843

M. S. Hossain, R. Angryk

引用次数: 0

A Fuzzy Associative Memory for the Classification of Chemical Warfare Agent Simulants 基于模糊联想记忆的化学战剂模拟物分类

NAFIPS 2007 - 2007 Annual Meeting of the North American Fuzzy Information Processing Society Pub Date : 2007-06-24 DOI: 10.1109/NAFIPS.2007.383837

R. Hammell, R. J. Schafer

{"title":"A Fuzzy Associative Memory for the Classification of Chemical Warfare Agent Simulants","authors":"R. Hammell, R. J. Schafer","doi":"10.1109/NAFIPS.2007.383837","DOIUrl":"https://doi.org/10.1109/NAFIPS.2007.383837","url":null,"abstract":"This paper presents the development and testing of a fuzzy associative memory (FAM) architecture for use in the classification of chemical warfare agent simulants. A hybrid ion mobility spectrometry time-of-flight mass spectrometry (IMS(tof)MS) instrument was used to collect data for two chemical warfare agent simulants: dimethyl methyl phosphonate (DMMP) and tributyl phosphate (TBP). A preprocessor was developed to convert the raw IMS(tof)MS data file into a set of triplets containing the values for the mass, K0 (reduced mobility), and intensity for each point in the original 2-dimensional data set. Due to the small amount of available real data, synthetic data sets were also created. A classification system was constructed consisting of a FAM trained by either DMMP data or TBP data. Repeated experiments were run using different sample set configurations for training and testing. Experiment scenarios included instances where real data sets were used for training, and cases where synthetic data were used for training; the test sets contained a mixture of both real and synthetic data each time. Training was done with training sets as small as only a single sample. The results were excellent: the system was able to correctly classify the DMMP and TBP data, both real and simulated, 100% of the time.","PeriodicalId":292853,"journal":{"name":"NAFIPS 2007 - 2007 Annual Meeting of the North American Fuzzy Information Processing Society","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129605306","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: 1

Design of Hybrid Intelligent Systems 混合智能系统的设计

NAFIPS 2007 - 2007 Annual Meeting of the North American Fuzzy Information Processing Society Pub Date : 2007-06-24 DOI: 10.1109/NAFIPS.2007.383905

P. Melin, Oscar Castillo, Janusz Kacprzyk, Witold Pedrycz

引用次数: 5

Interval Type-2 Fuzzy Logic for Intelligent Control Applications 区间2型模糊逻辑在智能控制中的应用

NAFIPS 2007 - 2007 Annual Meeting of the North American Fuzzy Information Processing Society Pub Date : 2007-06-24 DOI: 10.1109/NAFIPS.2007.383907

J. R. Castro, O. Castillo

引用次数: 17

Influence of the Migration Process on the Learning Performances of Fuzzy Knowledge Bases 迁移过程对模糊知识库学习性能的影响

NAFIPS 2007 - 2007 Annual Meeting of the North American Fuzzy Information Processing Society Pub Date : 2007-06-24 DOI: 10.1109/NAFIPS.2007.383887

Khaled Akrout, L. Baron, M. Balazinski, S. Achiche

引用次数: 2

Relational Factor Analysis with o-Matrix Decomposition 基于0矩阵分解的相关因子分析

NAFIPS 2007 - 2007 Annual Meeting of the North American Fuzzy Information Processing Society Pub Date : 2007-06-24 DOI: 10.1109/NAFIPS.2007.383828

R. Belohlávek, Vilém Vychodil

引用次数: 0