標題: Titlebook: Data Analysis and Pattern Recognition in Multiple Databases; Animesh Adhikari,Jhimli Adhikari,Witold Pedrycz Book 2014 Springer Internatio [打印本頁] 作者: cherub 時間: 2025-3-21 17:20
書目名稱Data Analysis and Pattern Recognition in Multiple Databases影響因子(影響力)
書目名稱Data Analysis and Pattern Recognition in Multiple Databases影響因子(影響力)學科排名
書目名稱Data Analysis and Pattern Recognition in Multiple Databases網(wǎng)絡(luò)公開度
書目名稱Data Analysis and Pattern Recognition in Multiple Databases網(wǎng)絡(luò)公開度學科排名
書目名稱Data Analysis and Pattern Recognition in Multiple Databases被引頻次
書目名稱Data Analysis and Pattern Recognition in Multiple Databases被引頻次學科排名
書目名稱Data Analysis and Pattern Recognition in Multiple Databases年度引用
書目名稱Data Analysis and Pattern Recognition in Multiple Databases年度引用學科排名
書目名稱Data Analysis and Pattern Recognition in Multiple Databases讀者反饋
書目名稱Data Analysis and Pattern Recognition in Multiple Databases讀者反饋學科排名
作者: nonchalance 時間: 2025-3-21 23:42 作者: 排名真古怪 時間: 2025-3-22 03:18
Clustering Local Frequency Items in Multiple Data Sources, based on local frequency items. A multi-branch company transacting from different branches often needs to extract global patterns from data distributed over the branches. Global decisions could be made effectively using such patterns. Thus it becomes important to cluster local frequency items in mu作者: Conquest 時間: 2025-3-22 07:27 作者: 虛弱的神經(jīng) 時間: 2025-3-22 11:22 作者: compel 時間: 2025-3-22 15:17 作者: compel 時間: 2025-3-22 17:33
Mining Calendar-Based Periodic Patterns in Time-Stamped Data,ant task. Recently, researchers have reported an algorithm for finding calendar-based periodic pattern in a time-stamped data and introduced the concept of certainty factor in association with an overlapped interval. In this chapter, we have extended the concept of certainty factor by incorporating 作者: 他去就結(jié)束 時間: 2025-3-22 23:38
Measuring Influence of an Item in Time-Stamped Databases,expressing influence of items on other items. In this chapter, we introduce the notion of an overall influence of a set of items on another set of items. We also propose an extension to the notion of overall association between two items in a database. Using this notion, we have designed two algorit作者: abracadabra 時間: 2025-3-23 04:44
Summary and Conclusions,resting as well as challenging when we are required to identify patterns and associations in multiple large data sources. While dealing with the domain of multiple large data sources, it has been observed that many patterns are specific to this domain; also some patterns are extensions of classical 作者: 合群 時間: 2025-3-23 09:01 作者: Finasteride 時間: 2025-3-23 10:30
J. A. L. Santos,M. Mateus,J. M. S. Cabral low quality from multiple databases, it becomes necessary to improve mining multiple databases. In this chapter, we present an idea of multi-database mining by making use of local pattern analysis. We elaborate on the existing specialized and generalized techniques which are used for mining multipl作者: diabetes 時間: 2025-3-23 16:17 作者: obstinate 時間: 2025-3-23 20:29
Trennung und Charakterisierung von Proteinenecomes of primordial relevance. In this chapter, we focus on the following issues. First, a model of mining global patterns of select items from multiple databases is presented. Second, a measure of quantifying an overall association between two items in a database is discussed. Third, we present an作者: BINGE 時間: 2025-3-23 23:15
https://doi.org/10.1007/978-3-662-29253-2the number of branches of a multi-branch company is increasing over time. Thus, it is important and timely to study data mining carried out on multiple data sources. A global exceptional pattern describes interesting individuality and specificity of few branches. Therefore, it is interesting to iden作者: legislate 時間: 2025-3-24 04:59
https://doi.org/10.1007/978-1-4684-8062-7er growth of the organizations. For instance, it might be of interest to learn about interesting changes in sales over time. In this chapter, we introduce a new pattern, called notch, of an item in time-stamped databases. Based on this notion, we propose a special kind of notch, called a generalized作者: AFFIX 時間: 2025-3-24 06:42
S. J. Murphy,E. D. Morgan,I. D. Wilsonant task. Recently, researchers have reported an algorithm for finding calendar-based periodic pattern in a time-stamped data and introduced the concept of certainty factor in association with an overlapped interval. In this chapter, we have extended the concept of certainty factor by incorporating 作者: pulmonary 時間: 2025-3-24 14:30 作者: drusen 時間: 2025-3-24 15:11
P. Leif Bergsagel,W. Michael Kuehlresting as well as challenging when we are required to identify patterns and associations in multiple large data sources. While dealing with the domain of multiple large data sources, it has been observed that many patterns are specific to this domain; also some patterns are extensions of classical 作者: 使成核 時間: 2025-3-24 23:04
Data Analysis and Pattern Recognition in Multiple Databases978-3-319-03410-2Series ISSN 1868-4394 Series E-ISSN 1868-4408 作者: 美麗的寫 時間: 2025-3-24 23:38
J. A. L. Santos,M. Mateus,J. M. S. Cabral low quality from multiple databases, it becomes necessary to improve mining multiple databases. In this chapter, we present an idea of multi-database mining by making use of local pattern analysis. We elaborate on the existing specialized and generalized techniques which are used for mining multiple large databases.作者: 臥虎藏龍 時間: 2025-3-25 07:13 作者: 天真 時間: 2025-3-25 08:42
P. Leif Bergsagel,W. Michael Kuehlresting as well as challenging when we are required to identify patterns and associations in multiple large data sources. While dealing with the domain of multiple large data sources, it has been observed that many patterns are specific to this domain; also some patterns are extensions of classical patterns.作者: Grasping 時間: 2025-3-25 15:43
https://doi.org/10.1007/978-3-319-03410-2Data Analysis; Intelligent Systems; Multiple Databases; Pattern Recognition作者: OTTER 時間: 2025-3-25 19:20
978-3-319-37727-8Springer International Publishing Switzerland 2014作者: aggravate 時間: 2025-3-25 23:44 作者: thwart 時間: 2025-3-26 00:16 作者: Debark 時間: 2025-3-26 07:30
Synthesizing Global Patterns in Multiple Large Data Sources, low quality from multiple databases, it becomes necessary to improve mining multiple databases. In this chapter, we present an idea of multi-database mining by making use of local pattern analysis. We elaborate on the existing specialized and generalized techniques which are used for mining multiple large databases.作者: Adulate 時間: 2025-3-26 12:29
Synthesizing Global Exceptional Patterns in Different Data Sources,the number of branches of a multi-branch company is increasing over time. Thus, it is important and timely to study data mining carried out on multiple data sources. A global exceptional pattern describes interesting individuality and specificity of few branches. Therefore, it is interesting to identify such patterns.作者: 大門在匯總 時間: 2025-3-26 12:59 作者: Anal-Canal 時間: 2025-3-26 18:23
Histone Acetylation And MethylationOrganizations that collect data from their multiple branches are common. Also, many established organizations possess data for a long period of time. Due to a spectrum of analyses, such data often need to be sub-divided into smaller databases.作者: 歡樂中國 時間: 2025-3-26 21:29 作者: nonchalance 時間: 2025-3-27 04:48
Introduction,Organizations that collect data from their multiple branches are common. Also, many established organizations possess data for a long period of time. Due to a spectrum of analyses, such data often need to be sub-divided into smaller databases.作者: 表主動 時間: 2025-3-27 08:41
Synthesizing Different Extreme Association Rules from Multiple Databases,The model of local pattern analysis provides sound solutions to many multi-database mining problems. In this chapter we discuss different types of extreme association rules in multiple databases viz.作者: Amendment 時間: 2025-3-27 12:01
A. E. Rodrigues,M. M. Dias,J. C. B. Lopesg clustering technique might cluster a set of items at a low level since it estimates association among items in an itemset with low accuracy, and thus a new algorithm for clustering local frequency items is proposed. Due to the suitability of measure of association . ., on its basis, association am作者: 沉著 時間: 2025-3-27 16:49
Clustering Local Frequency Items in Multiple Data Sources,g clustering technique might cluster a set of items at a low level since it estimates association among items in an itemset with low accuracy, and thus a new algorithm for clustering local frequency items is proposed. Due to the suitability of measure of association . ., on its basis, association am作者: 表示問 時間: 2025-3-27 20:15
1868-4394 of select items provide different patterns discovery techniques in multiple data sources. Some interesting item-based data analyses are also covered in this book. Interesting patterns, such as exceptional patt978-3-319-37727-8978-3-319-03410-2Series ISSN 1868-4394 Series E-ISSN 1868-4408 作者: Airtight 時間: 2025-3-27 23:27 作者: lethargy 時間: 2025-3-28 03:44
Book 2014 encountered before. Association rule mining, global pattern discovery and mining patterns of select items provide different patterns discovery techniques in multiple data sources. Some interesting item-based data analyses are also covered in this book. Interesting patterns, such as exceptional patt作者: conception 時間: 2025-3-28 09:27
Mining Icebergs in Different Time-Stamped Data Sources, notch and subsequently, a specific type of generalized notch, called an iceberg, in time-stamped databases. We design an algorithm for mining interesting icebergs in time-stamped databases. We also present experimental results obtained for both synthetic and real-world databases.作者: HEED 時間: 2025-3-28 11:37
Measuring Influence of an Item in Time-Stamped Databases,hms of influence analysis involving specific items in a database. As the number of databases increases on a yearly basis, we have adopted incremental approach to these algorithms. Experimental results are reported for both synthetic and real-world databases.作者: Fluctuate 時間: 2025-3-28 16:41 作者: STANT 時間: 2025-3-28 21:37 作者: ABIDE 時間: 2025-3-29 00:23
1868-4394 ase Analysis.Written by experts in the field.Includes supple.Pattern recognition in data is a well known classical problem that falls under the ambit of data analysis. As we need to handle different data, the nature of patterns, their recognition and the types of data analyses are bound to change. S作者: CANDY 時間: 2025-3-29 04:23
A. E. Rodrigues,M. M. Dias,J. C. B. Lopesdegree of variation of a class, and designed an algorithm to find clusters among items in different data sources. The best cluster is determined by average degree of variation in a cluster. Experimental results are provided for three transactional databases.作者: BARGE 時間: 2025-3-29 10:04 作者: 討好女人 時間: 2025-3-29 14:31 作者: 使混合 時間: 2025-3-29 18:19
Mining Patterns of Select Items in Different Data Sources,e databases. Each group contains a select item called the . and the group grows while being centered around the nucleus item. Experimental results are concerned with some synthetic and real-world databases.
