標(biāo)題: Titlebook: Data Mining: Foundations and Intelligent Paradigms; Volume 3: Medical, H Dawn E. Holmes,Lakhmi C Jain Book 20121st edition Springer-Verlag [打印本頁] 作者: duodenum 時(shí)間: 2025-3-21 16:24
書目名稱Data Mining: Foundations and Intelligent Paradigms影響因子(影響力)
書目名稱Data Mining: Foundations and Intelligent Paradigms影響因子(影響力)學(xué)科排名
書目名稱Data Mining: Foundations and Intelligent Paradigms網(wǎng)絡(luò)公開度
書目名稱Data Mining: Foundations and Intelligent Paradigms網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Data Mining: Foundations and Intelligent Paradigms被引頻次
書目名稱Data Mining: Foundations and Intelligent Paradigms被引頻次學(xué)科排名
書目名稱Data Mining: Foundations and Intelligent Paradigms年度引用
書目名稱Data Mining: Foundations and Intelligent Paradigms年度引用學(xué)科排名
書目名稱Data Mining: Foundations and Intelligent Paradigms讀者反饋
書目名稱Data Mining: Foundations and Intelligent Paradigms讀者反饋學(xué)科排名
作者: 信任 時(shí)間: 2025-3-21 22:51 作者: exclamation 時(shí)間: 2025-3-22 01:35 作者: 柔軟 時(shí)間: 2025-3-22 06:43
Gene Function Prediction and Functional Network: The Role of Gene Ontology,arity between genes is computed using gene ontology information and using Resniks formula, then our results show that we can model the PPI data as a mixture model predicated on the assumption that true protein-protein interactions will have higher support than the false positives in the data. Thus s作者: labile 時(shí)間: 2025-3-22 09:30
Mining Multiple Biological Data for Reconstructing Signal Transduction Networks,eatures, i.e., protein-protein interactions, signaling domains, domain-domain interactions, and protein functions. The gained results demonstrated that the method was promising to discover new STN and solve other related problems in computational and systems biology from large-scale protein interact作者: 組成 時(shí)間: 2025-3-22 12:57 作者: 組成 時(shí)間: 2025-3-22 17:02 作者: florid 時(shí)間: 2025-3-22 23:27 作者: tinnitus 時(shí)間: 2025-3-23 02:57 作者: ARBOR 時(shí)間: 2025-3-23 06:17
Ghislain Dubois,Femke Stoverinck,Bas Amelungarity between genes is computed using gene ontology information and using Resniks formula, then our results show that we can model the PPI data as a mixture model predicated on the assumption that true protein-protein interactions will have higher support than the false positives in the data. Thus s作者: Frisky 時(shí)間: 2025-3-23 10:23 作者: Mawkish 時(shí)間: 2025-3-23 16:12
https://doi.org/10.1007/978-3-319-74669-2 such as logistic regression due to the sparseness of the data and the non-linearity of the relationships. Second, the number of candidate models in a high-dimensional data set is forbiddingly large. This paper describes recent research addressing these two barriers. To address the first barrier, th作者: Crohns-disease 時(shí)間: 2025-3-23 20:55 作者: 共同生活 時(shí)間: 2025-3-23 22:43 作者: 投票 時(shí)間: 2025-3-24 03:49
https://doi.org/10.1007/978-3-642-23151-3Computational Intelligence; Data Mining; Financial Modelling; Intelligent Systems作者: Thyroid-Gland 時(shí)間: 2025-3-24 08:23
978-3-642-43546-1Springer-Verlag Berlin Heidelberg 2012作者: 植物茂盛 時(shí)間: 2025-3-24 11:14
Data Mining: Foundations and Intelligent Paradigms978-3-642-23151-3Series ISSN 1868-4394 Series E-ISSN 1868-4408 作者: 斗志 時(shí)間: 2025-3-24 18:38 作者: 表臉 時(shí)間: 2025-3-24 19:48 作者: SNEER 時(shí)間: 2025-3-25 01:40 作者: LAVE 時(shí)間: 2025-3-25 05:55
Monique Lewis,Kate Holland,Eliza Govenderrine, urinary, integumentary and reproductive systems [1]. Science shows how complex systems interoperate and have even mapped the human genome. This knowledge resulted through the exploitation of significant volumes of empirical data. The size of medical databases are many orders of magnitude those作者: 打火石 時(shí)間: 2025-3-25 11:21
https://doi.org/10.1007/978-3-031-41237-0ical data, which often contains time information. Temporal data mining aims at finding interesting correlations or sequential patterns in sets of temporal data and has recently been applied in the medical context. The purpose of this paper is to describe the most popular temporal data mining algorit作者: Affectation 時(shí)間: 2025-3-25 12:21 作者: 惰性女人 時(shí)間: 2025-3-25 19:53 作者: VEIL 時(shí)間: 2025-3-25 23:01
Uncertainty and Coping During COVID-19 interact with each other to perform vital functions for the survival of an organism. Three main types of biological networks are protein interaction networks, metabolic pathways and regulatory networks. In this work, we focus on alignment of metabolic networks..We particularly focus on two algorith作者: 惰性女人 時(shí)間: 2025-3-26 03:51 作者: SLUMP 時(shí)間: 2025-3-26 08:04 作者: 考得 時(shí)間: 2025-3-26 11:50
https://doi.org/10.1007/978-3-319-74669-2en little or no such effect can be observed statistically for one or even both of the genes individually. This is in contrast to Mendelian diseases like cystic fibrosis, which are associated with variation at a single genetic locus. This gene-gene interaction is called epistasis. To uncover this dar作者: 我要沮喪 時(shí)間: 2025-3-26 12:45 作者: 修飾 時(shí)間: 2025-3-26 20:23
Cory Young,Aditi Rao,Alexis Rosamilianity of Internet forum users. We discuss issues involved in Internet forum data acquisition and processing, and we outline some of the challenges that need to be addressed. Then, we present a framework for analysis and mining of Internet forum data for social role discovery. Our framework consists o作者: 協(xié)議 時(shí)間: 2025-3-27 00:34 作者: 使?jié)M足 時(shí)間: 2025-3-27 04:06 作者: 殺人 時(shí)間: 2025-3-27 07:16 作者: 載貨清單 時(shí)間: 2025-3-27 10:49 作者: consolidate 時(shí)間: 2025-3-27 14:08 作者: Cursory 時(shí)間: 2025-3-27 20:05 作者: 沒有準(zhǔn)備 時(shí)間: 2025-3-28 00:48
BioKeySpotter: An Unsupervised Keyphrase Extraction Technique in the Biomedical Full-Text Collectio in full-text. In this chapter, we proposes a novel unsupervised keyphrase extraction system, BioKeySpotter, which incorporates lexical syntactic features to weigh candidate keyphrases. The main contribution of our study is that BioKeySpotter is an innovative approach for combining Natural Language 作者: 危機(jī) 時(shí)間: 2025-3-28 03:19 作者: PACK 時(shí)間: 2025-3-28 06:35 作者: 拋物線 時(shí)間: 2025-3-28 13:00 作者: hypotension 時(shí)間: 2025-3-28 18:10 作者: 手榴彈 時(shí)間: 2025-3-28 19:01
Mining Epistatic Interactions from High-Dimensional Data Sets,en little or no such effect can be observed statistically for one or even both of the genes individually. This is in contrast to Mendelian diseases like cystic fibrosis, which are associated with variation at a single genetic locus. This gene-gene interaction is called epistasis. To uncover this dar作者: 圣人 時(shí)間: 2025-3-28 23:19
Knowledge Discovery in Adversarial Settings,unterterrorism but, increasingly, also more mainstream domains such as customer relationship management. The conventional strategy, maximizing the fit of a model to the available data, does not work in adversarial settings because the data cannot all be trusted, and because it makes the results too 作者: 說明 時(shí)間: 2025-3-29 06:39
Analysis and Mining of Online Communities of Internet Forum Users,nity of Internet forum users. We discuss issues involved in Internet forum data acquisition and processing, and we outline some of the challenges that need to be addressed. Then, we present a framework for analysis and mining of Internet forum data for social role discovery. Our framework consists o作者: rectum 時(shí)間: 2025-3-29 08:39 作者: 農(nóng)學(xué) 時(shí)間: 2025-3-29 12:25
Rule Extraction from Neural Networks and Support Vector Machines for Credit Scoring, SVM are two very popular techniques for pattern classification. In the business intelligence application domain of credit scoring, they have been shown to be effective tools for distinguishing between good credit risks and bad credit risks. The accuracy obtained by these two techniques is often hig作者: 修剪過的樹籬 時(shí)間: 2025-3-29 15:40
Using Self-Organizing Map for Data Mining: A Synthesis with Accounting Applications, pertinent literature as well as demonstrate, via a case study, how SOM can be applied in clustering accounting databases. The synthesis explicates SOM’s theoretical foundations, presents metrics for evaluating its performance, explains the main extensions of SOM, and discusses its main financial ap作者: 類型 時(shí)間: 2025-3-29 20:20
Applying Data Mining Techniques to Assess Steel Plant Operation Conditions,se. This work discusses data mining approach to this problem. We flattened the time series data of the whole operation into the form which is suitable for conventional data mining methods. This paper describes the methodology for transformation of the time series data and discusses the possible appl作者: 止痛藥 時(shí)間: 2025-3-30 01:53 作者: 否認(rèn) 時(shí)間: 2025-3-30 05:26 作者: 蟄伏 時(shí)間: 2025-3-30 10:04
Analysis and Mining of Online Communities of Internet Forum Users,f a multi-tier model, with statistical, index and network analysis tiers serving as knowledge discovery tools at different levels of analysis. We also show how using methods of social network analysis, in particular, the analysis of egocentric graphs of Internet forum users, may help in understanding social role attribution between users.作者: 門閂 時(shí)間: 2025-3-30 16:24 作者: 貴族 時(shí)間: 2025-3-30 18:24
1868-4394 ns” we wish to introduce some of the latest developments to a broad audience of both specialists and non-specialists in this field..978-3-642-43546-1978-3-642-23151-3Series ISSN 1868-4394 Series E-ISSN 1868-4408 作者: Arresting 時(shí)間: 2025-3-30 22:59 作者: Insufficient 時(shí)間: 2025-3-31 03:14
https://doi.org/10.1007/978-3-319-20161-0at we have developed to overcome this difficulty. These rule extraction methods enable the users to obtain comprehensible propositional rules from ANN and SVM. Such rules can be easily verified by the domain experts and would lead to a better understanding about the data in hand.作者: 偏離 時(shí)間: 2025-3-31 08:13
Data Mining for Information Literacy,s of current Web-based tools within this framework, investigating how they can further critical data literacy and privacy literacy. We conclude with an outlook on next steps in the proposed new field of Data Mining for Information Literacy.
