標(biāo)題: Titlebook: Case-Based Reasoning; A Textbook Michael M. Richter,Rosina O. Weber Textbook 2013 Springer-Verlag GmbH Germany 2013 Artificial intelligence [打印本頁] 作者: CANTO 時間: 2025-3-21 17:32
書目名稱Case-Based Reasoning影響因子(影響力)
書目名稱Case-Based Reasoning影響因子(影響力)學(xué)科排名
書目名稱Case-Based Reasoning網(wǎng)絡(luò)公開度
書目名稱Case-Based Reasoning網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Case-Based Reasoning被引頻次
書目名稱Case-Based Reasoning被引頻次學(xué)科排名
書目名稱Case-Based Reasoning年度引用
書目名稱Case-Based Reasoning年度引用學(xué)科排名
書目名稱Case-Based Reasoning讀者反饋
書目名稱Case-Based Reasoning讀者反饋學(xué)科排名
作者: 倫理學(xué) 時間: 2025-3-21 23:00 作者: 不在灌木叢中 時間: 2025-3-22 03:16 作者: 殘忍 時間: 2025-3-22 05:53 作者: Entrancing 時間: 2025-3-22 08:58
Oxyradicals as Signal Transducersing the search space. Transformational and derivational approaches are also described. This chapter is addressed to readers interested in adaptation of the query or the solution. Not all applications need that but it is of relevance to many. The understanding of this chapter assumes you have read th作者: 發(fā)出眩目光芒 時間: 2025-3-22 13:10 作者: 發(fā)出眩目光芒 時間: 2025-3-22 20:25 作者: Kidnap 時間: 2025-3-23 01:08 作者: Insubordinate 時間: 2025-3-23 01:41 作者: connoisseur 時間: 2025-3-23 06:22 作者: daredevil 時間: 2025-3-23 11:54
Introduction and the structure adopted in all chapters. The contents are presented via a description about each of the parts and a brief summary of each chapter. The description of the structure explains the role of the sections of the book such as Tools and Background Information.作者: 提煉 時間: 2025-3-23 14:50 作者: pancreas 時間: 2025-3-23 18:24 作者: 強(qiáng)所 時間: 2025-3-23 23:10 作者: 枕墊 時間: 2025-3-24 05:50 作者: 尋找 時間: 2025-3-24 10:04 作者: overrule 時間: 2025-3-24 13:41
Development and Maintenanceenance, we also discussed professional organisational structures such as the role of the participating agents. The individual steps are integrated into the systematic organisation. Because maintenance is an integral part of a system, the CBR cycle is extended to include it. Maintenance includes test作者: CALL 時間: 2025-3-24 16:55 作者: 邊緣帶來墨水 時間: 2025-3-24 21:33
Advanced Similarity Topics in the measure. For constructing a measure, we compare a bottom-up and a top-down approach. The introduction of weight diversity helps in choosing weights. The second part of this chapter discusses several aspects that can influence the use of similarity as noise, or as missing or redundant values.作者: HAUNT 時間: 2025-3-25 00:29 作者: 婚姻生活 時間: 2025-3-25 04:15 作者: 惹人反感 時間: 2025-3-25 10:45
s of CBR without assuming prior reader knowledge; Part II explains the core methods, in particu-lar case representations, similarity topics, retrieval, adaptation, evaluation, revisions, learning, develop-ment,978-3-662-52377-3978-3-642-40167-1作者: 整理 時間: 2025-3-25 12:36
er summaries, background notes, and exercises throughout.Inc.While it is relatively easy to record billions of experiences in a database, the wisdom of a system is not measured by the number of its experiences but rather by its ability to make use of them. Case-based rea-soning (CBR) can be viewed a作者: NEG 時間: 2025-3-25 17:14 作者: STIT 時間: 2025-3-25 21:08
Uncertaintyer-controlled way. Fuzzy sets and their logical descriptions are introduced. Examples show the relations between fuzzy sets and CBR. In addition, possibility and necessity are introduced. Both have a close relation to CBR. Formalisms are introduced insofar as they are needed for the relations to CBR.作者: 個阿姨勾引你 時間: 2025-3-26 03:08 作者: crescendo 時間: 2025-3-26 06:57
Multiplexing optical fiber sensors, domains typical of CBR. We recommend it to readers who have completed reading the previous chapters. The descriptions are intended to provide examples for illustrating the concepts and methods mentioned mostly in Chap. ., Basic CBR Elements. Throughout the chapter, we reference where to read further about new topics.作者: Alveoli 時間: 2025-3-26 09:01
Optical Fiber Sensor Technologyglobal principle. This principle allows describing all further representations, such as object-oriented, hierarchical, taxonomies, and graph-oriented representations. Trees are used for compact representations of attribute-value vectors. Graph structures often underlie more general object-oriented representations.作者: ABYSS 時間: 2025-3-26 15:01 作者: Perigee 時間: 2025-3-26 19:18 作者: 極肥胖 時間: 2025-3-26 22:22 作者: 迎合 時間: 2025-3-27 03:35 作者: evince 時間: 2025-3-27 08:12 作者: Contort 時間: 2025-3-27 12:38 作者: 動物 時間: 2025-3-27 16:58 作者: 繁榮中國 時間: 2025-3-27 21:23 作者: goodwill 時間: 2025-3-27 23:21 作者: 猛烈責(zé)罵 時間: 2025-3-28 05:39 作者: Gum-Disease 時間: 2025-3-28 07:33 作者: uveitis 時間: 2025-3-28 12:06 作者: 吊胃口 時間: 2025-3-28 17:58 作者: CUR 時間: 2025-3-28 19:38 作者: FAWN 時間: 2025-3-29 00:06 作者: 清晰 時間: 2025-3-29 05:34
Retrievalhat depends on the complexity of case representation and similarity assessment. It includes methods such as sequential retrieval, two-level retrieval, and retrieval methods with more complex indexing, geometric methods and Voronoi diagrams. As a major example of index-based retrieval, we consider kd作者: FELON 時間: 2025-3-29 09:22 作者: 大罵 時間: 2025-3-29 13:41
Evaluation, Revision, and Learningknowledge. It deals with revising the methods if something is definitely wrong and with improving CBR systems by machine learning if the results are weak. In this chapter methods for evaluating, revising and improving CBR are discussed in that order. Evaluation detects the weaknesses of a system. Re作者: 撕裂皮肉 時間: 2025-3-29 16:14 作者: 新陳代謝 時間: 2025-3-29 22:36
Advanced CBR Elementstarts by discussing the advanced aspect of the relationships between containers. The new concepts presented here are however of heterogeneous character in order to cover some aspects not yet presented. We also present a deeper discussion of contexts; CBR systems, their properties, their conditions, 作者: 紀(jì)念 時間: 2025-3-30 00:55 作者: 斷言 時間: 2025-3-30 04:05
Advanced Retrieval First, we consider two advanced retrieval methods: Case Retrieval Nets and Fish and Shrink. Both require a special case representation form. In the case of retrieval nets, the queries and the cases are incrementally completed. Fish and Shrink deals with very complex situations that have different a作者: MILL 時間: 2025-3-30 09:25
Uncertaintyly in applications. Of special interest is the relation to similarity. The rough set concept provides a method of describing uncertain results in a user-controlled way. Fuzzy sets and their logical descriptions are introduced. Examples show the relations between fuzzy sets and CBR. In addition, poss作者: conference 時間: 2025-3-30 12:58
Probabilitiesenomena. Some basic knowledge about probabilities is required. We discuss that the connections between similarities and probabilities are manifold. There are two directions: Probabilities give rise to adequate similarity measures. First we introduced covariance and correlation measures and the Kullb作者: 博愛家 時間: 2025-3-30 18:59
https://doi.org/10.1007/978-3-642-40167-1Artificial intelligence; Case-based reasoning (CBR); Complex knowledge; Information retrieval; Knowledge作者: NEX 時間: 2025-3-30 23:27 作者: abstemious 時間: 2025-3-31 04:32
Michael M. Richter,Rosina O. WeberFirst English-language textbook on the topic.Coauthor among the pioneers of the subject.Content thoroughly class-tested, book features chapter summaries, background notes, and exercises throughout.Inc作者: Armada 時間: 2025-3-31 07:27
http://image.papertrans.cn/c/image/222317.jpg作者: 費解 時間: 2025-3-31 09:59
Advances in Information Technologies,ly an interest in learning about it. It e positions case-based reasoning (CBR) in its scientific, educational, and applied contexts; it is therefore crucial for anyone interested in learning or teaching CBR. It provides a very intuitive notion of the CBR reasoning paradigm that can be understood by 作者: deceive 時間: 2025-3-31 14:23
