標(biāo)題: Titlebook: Bisociative Knowledge Discovery; An Introduction to C Michael R. Berthold Book‘‘‘‘‘‘‘‘ 2012 The Editor(s) (if applicable) and the Author(s) [打印本頁(yè)] 作者: 浮華 時(shí)間: 2025-3-21 20:09
書目名稱Bisociative Knowledge Discovery影響因子(影響力)
作者: Commentary 時(shí)間: 2025-3-21 21:40
From Information Networks to Bisociative Information Networksr bisociative knowledge discoveries. Finally based on this data structure three different patterns are described that fulfill the requirements of a bisociation by connecting concepts from seemingly unrelated domains.作者: 白楊 時(shí)間: 2025-3-22 01:44
Discovery of Novel Term Associations in a Document Collectiony dependent pairs that are not likely to be considered novel or interesting by the user..We present experimental results on two collections of documents: one extracted from Wikipedia, and one containing text mining articles with manually assigned term associations. The results indicate that the tpf–作者: optic-nerve 時(shí)間: 2025-3-22 05:42 作者: Robust 時(shí)間: 2025-3-22 11:39 作者: ANIM 時(shí)間: 2025-3-22 15:15 作者: 尾巴 時(shí)間: 2025-3-22 17:28 作者: BRIBE 時(shí)間: 2025-3-23 00:42 作者: 特征 時(shí)間: 2025-3-23 04:55 作者: Pcos971 時(shí)間: 2025-3-23 09:29 作者: neolith 時(shí)間: 2025-3-23 13:41
R. Degkwit?,A. Eckstein,E. Romingere development of such graph databases is important both to make basic graph mining easier and to prepare data for more complex types of analysis..In this chapter we present the BiQL data model for representing and manipulating information networks. The BiQL data model consists of two parts: a data m作者: capillaries 時(shí)間: 2025-3-23 14:24
Die Untersuchung des kranken Kindes,rithms and report on experimental results on real networks derived from public biological databases..The results show that a large fraction of edges can be removed quite fast and with minimal effect on the overall graph connectivity. A rough semantic analysis of the removed edges indicates that few 作者: 必死 時(shí)間: 2025-3-23 21:00 作者: CLAN 時(shí)間: 2025-3-24 00:47 作者: AVID 時(shí)間: 2025-3-24 03:52
Lecture Notes in Computer Sciencehttp://image.papertrans.cn/b/image/188885.jpg作者: 解脫 時(shí)間: 2025-3-24 10:20
Bisociative Knowledge Discovery978-3-642-31830-6Series ISSN 0302-9743 Series E-ISSN 1611-3349 作者: 參考書目 時(shí)間: 2025-3-24 13:52
Erkrankungen der Verdauungsorgane,k for the discovery of new connections between domains (so called .), supporting the creative discovery process in a more powerful way. We motivate this approach, show the difference to classical data analysis and conclude by describing a number of different types of domain-crossing connections.作者: FLASK 時(shí)間: 2025-3-24 18:18 作者: microscopic 時(shí)間: 2025-3-24 19:38
https://doi.org/10.1007/978-3-642-31830-6adaptive similarity; bridging concept identification; ensemble heuristics; recommendation; usability eva作者: 龍卷風(fēng) 時(shí)間: 2025-3-25 00:06
978-3-642-31829-0The Editor(s) (if applicable) and the Author(s) 2012. The book is published with open access at Spri作者: Crater 時(shí)間: 2025-3-25 03:41
Erkrankungen der Verdauungsorgane,k for the discovery of new connections between domains (so called .), supporting the creative discovery process in a more powerful way. We motivate this approach, show the difference to classical data analysis and conclude by describing a number of different types of domain-crossing connections.作者: 瑣碎 時(shí)間: 2025-3-25 08:20 作者: 銼屑 時(shí)間: 2025-3-25 15:15
Lehrbuch der Kinderheilkunde von where attempts are made to find unexpected relations across seemingly unrelated domains. Information networks, due to their flexible data structure, lend themselves perfectly to the integration of these heterogeneous data sources. This chapter provides an overview of different types of information 作者: 你不公正 時(shí)間: 2025-3-25 19:19
Lehrbuch der Kinderheilkunde vons are in this form. We rather find the data we want to fuse, connect, analyze and thus exploit for creative discoveries, stored in flat files, (relational) databases, text document collections and the like. As a consequence, we need, as an initial step, methods that construct a network representatio作者: 制造 時(shí)間: 2025-3-25 23:33 作者: 摻和 時(shí)間: 2025-3-26 04:09
Die Untersuchung des kranken Kindes,mportant challenge is information fusion of diverse mainly unstructured representations into a unique knowledge format. This chapter focuses on merging information available in text documents into an information network – a graph representation of knowledge. The problem addressed is how to efficient作者: 討厭 時(shí)間: 2025-3-26 07:30
,Gesundheitsfürsorge für das Kindesalter,re often best described by the relationships they establish. This is also evidenced by the popularity of conceptual maps, mind maps, and other similar methodologies to organize and summarize information. Our goal is to discover term relationships that can be used to construct conceptual maps or so c作者: Dawdle 時(shí)間: 2025-3-26 09:22
Krankheiten der Kreislauforgane,se of transactions. We, instead, strive to find item sets for which the similarity of the covers of the items (that is, the sets of transactions containing the items) exceeds a user-defined threshold. This approach yields a much better assessment of the association strength of the items, because it 作者: 得罪人 時(shí)間: 2025-3-26 16:42
Die Untersuchung des kranken Kindes,ies expressing uncertainty. While . is based on graphs, ProbLog’s core language is that of the logic programming language Prolog. This chapter provides an overview of important concepts, terminology, and reasoning tasks addressed in the two systems. It does so in an informal way, focusing on intuiti作者: 苦澀 時(shí)間: 2025-3-26 18:18
,Stoffwechsel und Ern?hrung ?lterer Kinder,of representing data in numerous fields. Additionally, such networks can be created or derived from other types of information using, e.g., the methods given in Part II of this volume..This part of the book describes various network algorithms for the exploration and analysis of BisoNets. Their gene作者: 類人猿 時(shí)間: 2025-3-26 21:49
R. Degkwit?,A. Eckstein,E. Romingermanagement systems and the aggregates and rankings they can compute. However, for the exploration of graph data, relational databases may not be most practical and scalable. Many tasks related to exploration of information networks involve computation and analysis of connections (e.g. paths) between作者: landmark 時(shí)間: 2025-3-27 02:23 作者: 下船 時(shí)間: 2025-3-27 06:56
Die Untersuchung des kranken Kindes,ion of a network, to extract its main structure, or as a pre-processing step for other data mining algorithms..We define a graph connectivity function based on the best paths between all pairs of nodes. Given the number of edges to be pruned, the problem is then to select a subset of edges that best作者: 奇思怪想 時(shí)間: 2025-3-27 12:44 作者: 外觀 時(shí)間: 2025-3-27 15:12 作者: 夜晚 時(shí)間: 2025-3-27 20:19
,Gesundheitsfürsorge für das Kindesalter,ns of concept graph detection. Thereby a concept graph defines a concept by a quasi bipartite sub-graph of a bigger network with the members of the concept as the first vertex partition and their shared aspects as the second vertex partition. Once the concepts have been extracted they can be used to作者: 拉開這車床 時(shí)間: 2025-3-27 22:29 作者: overweight 時(shí)間: 2025-3-28 05:04 作者: 語(yǔ)源學(xué) 時(shí)間: 2025-3-28 08:41 作者: noxious 時(shí)間: 2025-3-28 14:06 作者: 不法行為 時(shí)間: 2025-3-28 15:43
Towards Creative Information Exploration Based on Koestler’s Concept of Bisociationer new, surprising and valuable relationships in data that would not be revealed by conventional information retrieval, data mining and data analysis technologies. While our approach is inspired by work in the field of computational creativity, we are particularly interested in a model of creativity作者: 蓋他為秘密 時(shí)間: 2025-3-28 19:45
From Information Networks to Bisociative Information Networks where attempts are made to find unexpected relations across seemingly unrelated domains. Information networks, due to their flexible data structure, lend themselves perfectly to the integration of these heterogeneous data sources. This chapter provides an overview of different types of information 作者: CRUE 時(shí)間: 2025-3-29 02:44 作者: 一起 時(shí)間: 2025-3-29 04:11
Selecting the Links in BisoNets Generated from Document Collections In this chapter, we consider a methodology to find such bisociations using a BisoNet as a representation of knowledge. In a first step, we consider how to create BisoNets from several tex- tual databases taken from different domains using simple text-mining techniques. To achieve this, we introduce作者: 學(xué)術(shù)討論會(huì) 時(shí)間: 2025-3-29 07:50 作者: 剛毅 時(shí)間: 2025-3-29 14:56 作者: braggadocio 時(shí)間: 2025-3-29 19:03
Cover Similarity Based Item Set Miningse of transactions. We, instead, strive to find item sets for which the similarity of the covers of the items (that is, the sets of transactions containing the items) exceeds a user-defined threshold. This approach yields a much better assessment of the association strength of the items, because it 作者: Subjugate 時(shí)間: 2025-3-29 23:05
Patterns and Logic for Reasoning with Networksies expressing uncertainty. While . is based on graphs, ProbLog’s core language is that of the logic programming language Prolog. This chapter provides an overview of important concepts, terminology, and reasoning tasks addressed in the two systems. It does so in an informal way, focusing on intuiti作者: EVICT 時(shí)間: 2025-3-30 00:08
Network Analysis: Overviewof representing data in numerous fields. Additionally, such networks can be created or derived from other types of information using, e.g., the methods given in Part II of this volume..This part of the book describes various network algorithms for the exploration and analysis of BisoNets. Their gene作者: 禁令 時(shí)間: 2025-3-30 07:24 作者: subacute 時(shí)間: 2025-3-30 08:19 作者: 可耕種 時(shí)間: 2025-3-30 14:57
Simplification of Networks by Edge Pruningion of a network, to extract its main structure, or as a pre-processing step for other data mining algorithms..We define a graph connectivity function based on the best paths between all pairs of nodes. Given the number of edges to be pruned, the problem is then to select a subset of edges that best作者: 干涉 時(shí)間: 2025-3-30 19:50 作者: 轉(zhuǎn)折點(diǎn) 時(shí)間: 2025-3-31 00:34
Finding Representative Nodes in Probabilistic Graphs BisoNets. We define a probabilistic similarity measure for nodes, and then apply clustering methods to find groups of nodes. Finally, a representative is output from each cluster. We report on experiments with real biomedical data, using both the .-medoids and hierarchical clustering methods in the作者: Resistance 時(shí)間: 2025-3-31 03:04 作者: Generator 時(shí)間: 2025-3-31 08:01
Node Similarities from Spreading Activationses on the overlap of direct and indirect neighbors. The second similarity compares nodes based on the structure of their possibly also very distant neighborhoods. Both similarities are derived from spreading activation patterns over time. Whereas in the first method the activation patterns are dire作者: Obligatory 時(shí)間: 2025-3-31 11:02 作者: 聯(lián)合 時(shí)間: 2025-3-31 13:20
Exploration: Overviewnd diverse methods for network analysis have been proposed (Part III). All these methods provide powerful means in order to obtain different insights into the properties of huge information networks or graphs. However, one disadavantage of these individual approaches is that each approach provides o作者: Kindle 時(shí)間: 2025-3-31 18:03 作者: 歡騰 時(shí)間: 2025-3-31 22:41
Lehrbuch der Kinderheilkunde vononal) databases, text document collections and the like. As a consequence, we need, as an initial step, methods that construct a network representation by analyzing tabular and textual data, in order to identify entities that can serve as nodes and to extract relevant relationships that should be represented by edges.作者: aesthetic 時(shí)間: 2025-4-1 02:29
Die Untersuchung des kranken Kindes,s an overview of important concepts, terminology, and reasoning tasks addressed in the two systems. It does so in an informal way, focusing on intuition rather than on mathematical definitions. It aims at bridging the gap between network representations and logical ones.作者: 斜 時(shí)間: 2025-4-1 09:57
Die Untersuchung des kranken Kindes,cture of a large BisoNet, or understand connections between distant nodes, or discover hidden knowledge. In this paper we review different approaches and techniques to abstract a large BisoNet. We classify the approaches into two groups: preference-free methods and preference-dependent methods.作者: 煩躁的女人 時(shí)間: 2025-4-1 12:31
https://doi.org/10.1007/978-3-642-87322-5e is output from each cluster. We report on experiments with real biomedical data, using both the .-medoids and hierarchical clustering methods in the clustering step. The results suggest that the clustering based approaches are capable of finding a representative set of nodes.作者: nephritis 時(shí)間: 2025-4-1 16:53
,Gesundheitsfürsorge für das Kindesalter,ncept as the first vertex partition and their shared aspects as the second vertex partition. Once the concepts have been extracted they can be used to create higher level representations of the data. Concept graphs further allow the discovery of missing concepts, which could lead to new insights by connecting seemingly unrelated information units.
