计算机科学 ›› 2014, Vol. 41 ›› Issue (11): 260-264.doi: 10.11896/j.issn.1002-137X.2014.11.050
李远航,刘波,唐侨
LI Yuan-hang,LIU Bo and TANG Qiao
摘要： 主动学习已经广泛应用于图数据的研究,但应用于多标签图数据的分类较为少见。结合基于误差界最小化的主动学习,给出了一种多标签图数据的分类方法,即通过多标签分类与局部和全局的一致性学习(LLGC)得到一系列目标方程,并将其用于最小化直推式的拉德马赫复杂度,得到最小泛化误差上界,从而在图上获取少量的但蕴含巨大信息量的节点。实验证明,应用该方法的多标签分类器的输出有很高的精确度。
| [1] Prati L,Villa A,Lupini A R,et al.Gold on carbon:one billion catalysts under a single label[J].Physical Chemistry Chemical Physics,2012,14(9):2969-2978 [2] Zhao G,Xuan K,Taniar D.Path KNN query processing in mobile systems[J].Browse Journals and Magazines,2013,60(3):1099-1107 [3] Chou K-C.Some remarks on predicting multi-label attributes in molecular biosystems[J].Molecular BioSystems,2013,9(6):1092-1100 [4] Markatopoulou F,Mezaris V,Kompatsiaris I.A comparativestudy on the use of multi-label classification techniques for concept-based video indexing and annotation[J].MultiMedia Mo-deling,2014,8325:1-12 [5] Rubin T N,Chambers A,Smyth P,et al.Statistical topic models for multi-label document classification[J].Machine Learning,2012,88(1/2):157-208 [6] Kazawa H,Lzumitani T,Taira H,et al.Maximal marging labe-ling for multi-topic text categorization[J].Neural Information Processing Systems,2005,17:649-656 [7] Boutell M R,Luo J,Shen X,et al.Learning multi-label scene classification[J].Pattern Recognition,2004,37(9):1757-1771 [8] Zhang M L,Zhou Z H.Multilabel neural networks with applications to functional genomics and text categorization[J].Know-ledge and Data Engineering,2006,18(10):1338-1351 [9] Chen B,Ding Y,Wild D.Assessing drug target association using semantic linked data[J].PLoSComput Biology,2012,8(7):1-10 [10] Zhou D,Bousquet O,Lal T N,et al.Learning with local andglobal consistency[J].Advances in neural information processng systems,2004,6(16):321-328 [11] El-Yaniv R,Pechyony D.Transductiverademacher complexityand its applications[J].Learning Theory,2007,4539:157-171 [12] Gu Q,Han J.Towards active learning on graphs:An errorbound minimization approach[C]∥ICDM.2012:882-887 [13] Gao S,Wu W,Lee C-H,et al.A MFoM learning approach to robust multiclass multi-label text categorization[C]∥ICML.2004:42 [14] Crammer K,Singer Y.A new family of online algorithms forcategory ranking[C]∥SIGIR.2002:151-158 [15] Ghamrawi N,McCallum A.Collective Multi-Label Classification[C]∥CIKM.2005:195-200 [16] Boutell M R,Luo J,Shen X,et al.Learning muti-label scene classification[J].Pattern Recognition,2004,37(9):1757-1771 [17] Zhang M L,Zhou Z H.ML-KNN:A lazy learning approach to multi-label learning[J].Pattern Recognition,2007,40(7):2038-2048 [18] Yan X,Han J.gSpan:Graph-based substructure pattern mining[C]∥ICDM.2002:721-724 [19] Inokuchi A,Washio T,Motoda H.An apriori-based algorithm for mining frequent substructures form graph data[C]∥PKDD.2000:13-23 [20] Kuramochi M,Karypis G.Frequent subgraphdiscovery[C]∥ICDM.2001:313-320 [21] Borgelt C,Berthold M.Mining molecular fragments:Finding relevant substructures of molecules[C]∥ICDM.2002:211-128 [22] Nijssen S,Kok J.A quickstart in frequent structure mining can make a difference[C]∥KDD.2004:647-562 [23] Guillory A,Bilmes J.Active semi-supervised learning using submodularfunctions[C]∥UAI.2011:274-282 [24] Guillory A,Bilmes J A.Label selection on graphs[C]∥NIPS.2009:669-691 [25] Ji M,Han J.A variance minimization criterion to active learning on graphs[C]∥AISTATS.2012:556-564 [26] Ngomo A-C N,Lyko K.EAGLE:Efficient active learning of link specifications using genetic programming[J].The Semantic Web:Research and Applications,2012,7295:149-163 [27] Cesa-Bianchi N,Gentile C,Vitale F,et al.Active learning on trees and graphs[C]∥COLT.2010:320-332 [28] Helma C,King R,Kramer S,et al.The predictive toxicologychallenge 2000-2001[J].Bioinformatics,2001,17(1):107-108 |
| No related articles found! |
|
||
首页