標(biāo)題: Titlebook: Discovery Science; 14th International C Tapio Elomaa,Jaakko Hollmén,Heikki Mannila Conference proceedings 2011 Springer-Verlag GmbH Berlin [打印本頁] 作者: 忠誠 時(shí)間: 2025-3-21 16:16
書目名稱Discovery Science影響因子(影響力)
書目名稱Discovery Science影響因子(影響力)學(xué)科排名
書目名稱Discovery Science網(wǎng)絡(luò)公開度
書目名稱Discovery Science網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Discovery Science被引頻次
書目名稱Discovery Science被引頻次學(xué)科排名
書目名稱Discovery Science年度引用
書目名稱Discovery Science年度引用學(xué)科排名
書目名稱Discovery Science讀者反饋
書目名稱Discovery Science讀者反饋學(xué)科排名
作者: 退出可食用 時(shí)間: 2025-3-21 22:33
https://doi.org/10.1007/978-94-017-3175-1tion. The use of prototype semantic data mining systems SEGS and g-SEGS is demonstrated in a simple semantic data mining scenario and in two real-life functional genomics scenarios of mining biological ontologies with the support of experimental microarray data.作者: sebaceous-gland 時(shí)間: 2025-3-22 00:56 作者: 反復(fù)拉緊 時(shí)間: 2025-3-22 06:25 作者: reperfusion 時(shí)間: 2025-3-22 11:36
Using Ontologies in Semantic Data Mining with SEGS and g-SEGS,tion. The use of prototype semantic data mining systems SEGS and g-SEGS is demonstrated in a simple semantic data mining scenario and in two real-life functional genomics scenarios of mining biological ontologies with the support of experimental microarray data.作者: LATE 時(shí)間: 2025-3-22 14:06 作者: LATE 時(shí)間: 2025-3-22 20:10
Application of Semantic Kernels to Literature-Based Gene Function Annotation, solution to deal with class imbalance. From experiments on the TREC Genomics Track data, our approach achieves better ..-score than two state-of-the-art approaches based on string-matching and cross-species information.作者: Schlemms-Canal 時(shí)間: 2025-3-22 23:03
Multiple Hypothesis Testing in Pattern Discovery,ives (Type I error). Our contribution in this paper is to extend the multiple hypothesis framework to be used in a generic data mining setting. We provide a method that provably controls the family-wise error rate (FWER, the probability of at least one false positive). We show the power of our solution on real data.作者: 使高興 時(shí)間: 2025-3-23 02:18 作者: interlude 時(shí)間: 2025-3-23 06:40 作者: 富足女人 時(shí)間: 2025-3-23 13:22
0302-9743 ubmissions. The papers cover a wide range including the development and analysis of methods for automatic scientific knowledge discovery, machine learning, intelligent data analysis, theory of learning, as well as their application to knowledge discovery.978-3-642-24476-6978-3-642-24477-3Series ISSN 0302-9743 Series E-ISSN 1611-3349 作者: semiskilled 時(shí)間: 2025-3-23 14:04
Income Distribution and Economic Growthsuch as multi-label classification, hierarchical classification or ordinal classification, may be addressed within the framework of learning from label preferences. We also briefly address theoretical questions as well as algorithmic and complexity issues.作者: 流動(dòng)才波動(dòng) 時(shí)間: 2025-3-23 20:20 作者: 逢迎白雪 時(shí)間: 2025-3-24 00:23 作者: 熒光 時(shí)間: 2025-3-24 05:44 作者: 有發(fā)明天才 時(shí)間: 2025-3-24 06:51
Learning from Label Preferences,such as multi-label classification, hierarchical classification or ordinal classification, may be addressed within the framework of learning from label preferences. We also briefly address theoretical questions as well as algorithmic and complexity issues.作者: parallelism 時(shí)間: 2025-3-24 12:21
Information Distance and Its Extensions,ry has found many applications. Recently we have introduced two extensions to this theory concerning multiple objects and irrelevant information. This expository article will focus on explaining the main ideas behind this theory, especially these recent extensions, and their applications. We will also discuss some very preliminary applications.作者: 歡騰 時(shí)間: 2025-3-24 17:04 作者: 暫時(shí)休息 時(shí)間: 2025-3-24 20:38
A Methodology for Mining Document-Enriched Heterogeneous Information Networks,ed. We exploit this feature vector construction process to devise an efficient classification algorithm. We demonstrate the approach by applying it to the task of categorizing video lectures. We show that our approach exhibits low time and space complexity without compromising classification accuracy.作者: 瑣碎 時(shí)間: 2025-3-24 23:59 作者: 持久 時(shí)間: 2025-3-25 05:32
Conference proceedings 20115 invited lectures were carefully revised and selected from 56 submissions. The papers cover a wide range including the development and analysis of methods for automatic scientific knowledge discovery, machine learning, intelligent data analysis, theory of learning, as well as their application to knowledge discovery.作者: 抗生素 時(shí)間: 2025-3-25 10:59 作者: HEPA-filter 時(shí)間: 2025-3-25 14:51
Georgia K. Hinkley,Stephen M. Robertsives (Type I error). Our contribution in this paper is to extend the multiple hypothesis framework to be used in a generic data mining setting. We provide a method that provably controls the family-wise error rate (FWER, the probability of at least one false positive). We show the power of our solution on real data.作者: 越自我 時(shí)間: 2025-3-25 18:39
https://doi.org/10.1007/978-94-017-3175-1rect outcome of an entropy function used in measuring the encoding length of clusters and the second one is realized through our new encoding method. Experiments using synthetic and real data sets give promising results.作者: 犬儒主義者 時(shí)間: 2025-3-25 23:16 作者: 植物茂盛 時(shí)間: 2025-3-26 01:17 作者: LIKEN 時(shí)間: 2025-3-26 04:20
0302-9743 national Conference on Discovery Science, DS 2011, held in Espoo, Finland, in October 2011 - co-located with ALT 2011, the 22nd International Conference on Algorithmic Learning Theory. The 24 revised full papers presented together with 5 invited lectures were carefully revised and selected from 56 s作者: 音的強(qiáng)弱 時(shí)間: 2025-3-26 09:24
The Lasting Debate on Human Rightsl successful algorithms have been proposed in recent years. We review some of the theoretical motivations for deep architectures, as well as some of their practical successes, and propose directions of investigations to address some of the remaining challenges.作者: 賞心悅目 時(shí)間: 2025-3-26 14:51 作者: 不如屎殼郎 時(shí)間: 2025-3-26 19:10 作者: MURKY 時(shí)間: 2025-3-26 22:37
Information Distance and Its Extensions,mage, an email, a webpage, a Google query, an answer, a movie, a music score, a Facebook blog, a short message, or even an abstract concept. Over the past 20 years, we have been developing a general theory of information distance in this space and applications of this theory. The theory is object-in作者: BACLE 時(shí)間: 2025-3-27 02:15 作者: 放大 時(shí)間: 2025-3-27 07:53
Monotone Instance Ranking with ,,butes describing it. Consider, for example, the problem of ranking documents with respect to their relevance to a particular query. Typical attributes are counts of query terms in the abstract or title of the document, so it is natural to postulate the existence of an increasing relationship between作者: Expressly 時(shí)間: 2025-3-27 10:06 作者: CLOWN 時(shí)間: 2025-3-27 14:57 作者: prick-test 時(shí)間: 2025-3-27 20:38
,“Tell Me More”: Finding Related Items from User Provided Feedback,lenging problem for a user is to pick out the useful information. In this paper we propose an interactive framework to efficiently explore and (re)rank the objects retrieved by such an engine, according to feedback provided on part of the initially retrieved objects. In particular, given a set of ob作者: 阻擋 時(shí)間: 2025-3-28 01:10 作者: 安心地散步 時(shí)間: 2025-3-28 05:24 作者: 合乎習(xí)俗 時(shí)間: 2025-3-28 09:32
Multiple Hypothesis Testing in Pattern Discovery,is is a very common situation in many data mining applications. For instance, assessing simultaneously the significance of all frequent itemsets of a single dataset entails a host of hypothesis, one for each itemset. A multiple hypothesis testing method is needed to control the number of false posit作者: 大酒杯 時(shí)間: 2025-3-28 12:04
A Parameter-Free Method for Discovering Generalized Clusters in a Network,s a network. We define intuitively that generalized clusters contain at least a cluster in which nodes are connected sparsely and the cluster is connected either densely to another cluster or sparsely to another conventional cluster. The first characteristic of the MDL-based graph clustering is a di作者: ESPY 時(shí)間: 2025-3-28 15:20
Detecting Anti-majority Opinionists Using Value-Weighted Mixture Voter Model,ct that some people have a tendency to disagree with any opinion expressed by the majority. We extend the value-weighted voter model to include this phenomenon with the anti-majoritarian tendency of each node as a new parameter, and learn this parameter as well as the value of each opinion from a se作者: apiary 時(shí)間: 2025-3-28 21:13
Using Ontologies in Semantic Data Mining with SEGS and g-SEGS,to the data, the amount of semantic data is rapidly growing. The data mining community is faced with a paradigm shift: instead of mining the abundance of empirical data supported by the background knowledge, the new challenge is to mine the abundance of knowledge encoded in domain ontologies, constr作者: 白楊 時(shí)間: 2025-3-29 01:20 作者: Adulterate 時(shí)間: 2025-3-29 04:49 作者: 尋找 時(shí)間: 2025-3-29 07:31
Network Effects on Tweeting,nformation exchange than Twitter.com. In this paper, we study large-scale graph properties and lesser-studied local graph structures of the explicit social network and the implicit retweet network in order to better understand the relationship between socialization and tweeting behaviors. In particu作者: 證實(shí) 時(shí)間: 2025-3-29 14:15 作者: 挑剔為人 時(shí)間: 2025-3-29 18:04
Frontiers in African Business Researchpt to remove unwanted rank equalities. Through experiments we show that . produces ranking functions having predictive performance comparable to that of a state-of-the-art instance ranking algorithm. This makes . a valuable alternative when monotonicity is desired or mandatory.作者: 分期付款 時(shí)間: 2025-3-29 23:09
C. Santano,M. Pérez de Lara,J. Pintormber of communities and topics automatically, Hierarchical/Dirichlet Process Mixture model (H/DPM) is employed. Gibbs sampling based approach is adopted to learn the model parameters. Experiments are conducted on the co-author network extracted from DBLP where each author is associated with his/her 作者: Androgen 時(shí)間: 2025-3-30 02:38 作者: Affectation 時(shí)間: 2025-3-30 06:19
Die Siebenbürger Sachsen und ?sterreiche this problem we incorporate external contextual information (e.g. time of the day) into route recognition from trajectory. We develop a technique to determine from the historical data how the probability of a route depends on contextual features and adjust (post-correct) the route recognition outp作者: athlete’s-foot 時(shí)間: 2025-3-30 10:03 作者: anarchist 時(shí)間: 2025-3-30 14:33
MEI: Mutual Enhanced Infinite Generative Model for Simultaneous Community and Topic Detection,mber of communities and topics automatically, Hierarchical/Dirichlet Process Mixture model (H/DPM) is employed. Gibbs sampling based approach is adopted to learn the model parameters. Experiments are conducted on the co-author network extracted from DBLP where each author is associated with his/her 作者: Offstage 時(shí)間: 2025-3-30 17:50
Detecting Anti-majority Opinionists Using Value-Weighted Mixture Voter Model, the highest value prevails and wins when the opinion values are non-uniform, whereas the opinion share prediction problem becomes ill-defined and any opinion can win when the opinion values are uniform. The simulation results support that this holds for typical real world social networks.作者: 沒有希望 時(shí)間: 2025-3-31 00:30
Context-Aware Personal Route Recognition,e this problem we incorporate external contextual information (e.g. time of the day) into route recognition from trajectory. We develop a technique to determine from the historical data how the probability of a route depends on contextual features and adjust (post-correct) the route recognition outp作者: 圖表證明 時(shí)間: 2025-3-31 01:07 作者: 主動(dòng)脈 時(shí)間: 2025-3-31 06:24 作者: Cholesterol 時(shí)間: 2025-3-31 10:58
https://doi.org/10.1007/978-3-642-24477-3autonomous exploration; data mining; kernel methods; social network analysis; user interface; algorithm a作者: 鄙視 時(shí)間: 2025-3-31 15:38
978-3-642-24476-6Springer-Verlag GmbH Berlin Heidelberg 2011作者: Incorporate 時(shí)間: 2025-3-31 19:46 作者: 有惡意 時(shí)間: 2025-3-31 22:55 作者: GLIB 時(shí)間: 2025-4-1 05:42 作者: 幼兒 時(shí)間: 2025-4-1 06:15
Lecture Notes in Computer Sciencehttp://image.papertrans.cn/e/image/281063.jpg作者: 獨(dú)行者 時(shí)間: 2025-4-1 13:30
The Lasting Debate on Human Rightsing their parameters so as to approximately optimize some training objective. Whereas it was thought too difficult to train deep architectures, several successful algorithms have been proposed in recent years. We review some of the theoretical motivations for deep architectures, as well as some of t作者: 萬靈丹 時(shí)間: 2025-4-1 14:38
Income Distribution and Economic Growtho the learning setting, we particularly focus on our own work, which addresses this problem via the learning by pairwise comparison paradigm. From a machine learning point of view, learning by pairwise comparison is especially appealing as it decomposes a possibly complex prediction problem into a c
