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ORCIDData Mining and Knowledge Discovery, Volume 34
Volume 34, Number 1, January 2020
- Jia Zhu
, Zetao Zheng, Min Yang, Gabriel Pui Cheong Fung, Yong Tang:
A semi-supervised model for knowledge graph embedding. 1-20 - Kai Puolamäki, Emilia Oikarinen, Bo Kang, Jefrey Lijffijt, Tijl De Bie:
Interactive visual data exploration with subjective feedback: an information-theoretic approach. 21-49 - Felipe Azevedo Pinage, Eulanda Miranda dos Santos, João Gama:
A drift detection method based on dynamic classifier selection. 50-74 - Min Shi, Yufei Tang, Xingquan Zhu, Jianxun Liu, Haibo He:
Topical network embedding. 75-100 - Taito Lee, Shin Matsushima, Kenji Yamanishi:
Grafting for combinatorial binary model using frequent itemset mining. 101-123 - Sunil Aryal, Kai Ming Ting, Takashi Washio, Gholamreza Haffari:
A comparative study of data-dependent approaches without learning in measuring similarities of data objects. 124-162 - Meike Zehlike, Philipp Hacker, Emil Wiedemann:
Matching code and law: achieving algorithmic fairness with optimal transport. 163-200 - Mehdi Katranji, Sami Kraiem, Laurent Moalic, Guilhem Sanmarty, Ghazaleh Khodabandelou, Alexandre Caminada, Fouad Hadj-Selem:
Deep multi-task learning for individuals origin-destination matrices estimation from census data. 201-230 - Chang Wei Tan, François Petitjean, Geoffrey I. Webb:
FastEE: Fast Ensembles of Elastic Distances for time series classification. 231-272
Volume 34, Number 2, March 2020
- Diego Olaya, Kristof Coussement, Wouter Verbeke:
A survey and benchmarking study of multitreatment uplift modeling. 273-308 - Sevvandi Kandanaarachchi, Mario A. Muñoz, Rob J. Hyndman, Kate Smith-Miles:
On normalization and algorithm selection for unsupervised outlier detection. 309-354 - Anes Bendimerad, Ahmad Mel, Jefrey Lijffijt, Marc Plantevit, Céline Robardet, Tijl De Bie:
SIAS-miner: mining subjectively interesting attributed subgraphs. 355-393 - Adnene Belfodil, Sylvie Cazalens, Philippe Lamarre, Marc Plantevit:
Identifying exceptional (dis)agreement between groups. 394-442 - Loredana Caruccio, Vincenzo Deufemia, Giuseppe Polese:
Mining relaxed functional dependencies from data. 443-477 - Fedor V. Fomin, Petr A. Golovach, Fahad Panolan:
Parameterized low-rank binary matrix approximation. 478-532 - Catherine Kerr, Terri Hoare, Paula Carroll, Jakub Marecek:
Integer programming ensemble of temporal relations classifiers. 533-562 - Thomas Guyet, René Quiniou:
NegPSpan: efficient extraction of negative sequential patterns with embedding constraints. 563-609
Volume 34, Number 3, May 2020
- Florian Adriaens, Tijl De Bie, Aristides Gionis, Jefrey Lijffijt, Antonis Matakos, Polina Rozenshtein:
Relaxing the strong triadic closure problem for edge strength inference. 611-651 - Carlos Andres Ferrero, Lucas May Petry, Luis Otávio Alvares, Camila Leite da Silva, Willian Zalewski, Vania Bogorny:
MasterMovelets: discovering heterogeneous movelets for multiple aspect trajectory classification. 652-680 - Fatemeh Riahi, Oliver Schulte:
Model-based exception mining for object-relational data. 681-722 - Irene Ortner, Peter Filzmoser, Christophe Croux:
Robust and sparse multigroup classification by the optimal scoring approach. 723-741 - Ahmed Shifaz, Charlotte Pelletier, François Petitjean, Geoffrey I. Webb:
TS-CHIEF: a scalable and accurate forest algorithm for time series classification. 742-775 - Marco Capó, Aritz Pérez, José Antonio Lozano:
An efficient K-means clustering algorithm for tall data. 776-811 - Matthias Schmid, Thomas Welchowski, Marvin N. Wright, Moritz Berger:
Discrete-time survival forests with Hellinger distance decision trees. 812-832 - Zengyou He, Hao Liang, Zheng Chen, Can Zhao, Yan Liu:
Computing exact P-values for community detection. 833-869 - Taha Ceritli, Christopher K. I. Williams, James Geddes:
ptype: probabilistic type inference. 870-904
Volume 34, Number 4, July 2020
- Muhammad Irfan Yousuf, Suhyun Kim:
Guided sampling for large graphs. 905-948 - Yan Zhu, Shaghayegh Gharghabi, Diego Furtado Silva, Hoang Anh Dau, Chin-Chia Michael Yeh, Nader Shakibay Senobari, Abdulaziz Almaslukh, Kaveh Kamgar, Zachary Zimmerman, Gareth J. Funning, Abdullah Mueen, Eamonn J. Keogh:
The Swiss army knife of time series data mining: ten useful things you can do with the matrix profile and ten lines of code. 949-979 - Jinghan Meng, Napath Pitaksirianan, Yi-Cheng Tu:
Counting frequent patterns in large labeled graphs: a hypergraph-based approach. 980-1021 - Michele Linardi, Yan Zhu, Themis Palpanas, Eamonn J. Keogh:
Matrix profile goes MAD: variable-length motif and discord discovery in data series. 1022-1071 - Yulong Pei, Xin Du, Jianpeng Zhang, George Fletcher, Mykola Pechenizkiy:
struc2gauss: Structural role preserving network embedding via Gaussian embedding. 1072-1103 - Shaghayegh Gharghabi, Shima Imani, Anthony J. Bagnall, Amirali Darvishzadeh, Eamonn J. Keogh:
An ultra-fast time series distance measure to allow data mining in more complex real-world deployments. 1104-1135 - Saeid Hosseini, Saeed Najafi Pour, Ngai-Man Cheung, Hongzhi Yin, Mohammad Reza Kangavari, Xiaofang Zhou:
TEAGS: time-aware text embedding approach to generate subgraphs. 1136-1174 - Steven Elsworth, Stefan Güttel:
ABBA: adaptive Brownian bridge-based symbolic aggregation of time series. 1175-1200 - Leonardo Pellegrina, Fabio Vandin:
Efficient mining of the most significant patterns with permutation testing. 1201-1234
Volume 34, Number 5, September 2020
- Ira Assent, Carlotta Domeniconi, Aristides Gionis, Eyke Hüllermeier:
Introduction to the special issue of the ECML PKDD 2020 journal track. 1235-1236 - Maciej Grzenda, Heitor Murilo Gomes, Albert Bifet:
Delayed labelling evaluation for data streams. 1237-1266 - Xin Du, Yulong Pei, Wouter Duivesteijn, Mykola Pechenizkiy:
Exceptional spatio-temporal behavior mining through Bayesian non-parametric modeling. 1267-1290 - David García-Soriano, Francesco Bonchi:
Fair-by-design matching. 1291-1335 - Patrick Schäfer, Ulf Leser:
TEASER: early and accurate time series classification. 1336-1362 - Jihong Wang, Minnan Luo, Fnu Suya, Jundong Li, Zijiang Yang, Qinghua Zheng:
Scalable attack on graph data by injecting vicious nodes. 1363-1389 - Stefano Calzavara, Claudio Lucchese, Gabriele Tolomei, Seyum Assefa Abebe, Salvatore Orlando:
Treant: training evasion-aware decision trees. 1390-1420 - Peter Bloem, Steven de Rooij:
Large-scale network motif analysis using compression. 1421-1453 - Angus Dempster, François Petitjean, Geoffrey I. Webb:
ROCKET: exceptionally fast and accurate time series classification using random convolutional kernels. 1454-1495 - Felipe Kenji Nakano, Ricardo Cerri, Celine Vens:
Active learning for hierarchical multi-label classification. 1496-1530 - Guiliang Liu, Yudong Luo, Oliver Schulte, Tarak Kharrat:
Deep soccer analytics: learning an action-value function for evaluating soccer players. 1531-1559 - Shameem Ahamed Puthiya Parambath, Sanjay Chawla:
Simple and effective neural-free soft-cluster embeddings for item cold-start recommendations. 1560-1588 - Bay-Yuan Hsu, Chia-Lin Tu, Ming-Yi Chang, Chih-Ya Shen:
CrawlSN: community-aware data acquisition with maximum willingness in online social networks. 1589-1620
Volume 34, Number 6, November 2020
- Zhuo Wang, Runlong Hu, Qian Chen, Pei Gao, Xiaowei Xu:
ColluEagle: collusive review spammer detection using Markov random fields. 1621-1641 - Hannah Rae Kerner, Kiri L. Wagstaff, Brian D. Bue, Danika F. Wellington, Samantha Jacob, Paul Horton, James F. Bell, Chiman Kwan, Heni Ben Amor:
Comparison of novelty detection methods for multispectral images in rover-based planetary exploration missions. 1642-1675 - Ofir Lindenbaum, Moshe Salhov, Arie Yeredor, Amir Averbuch:
Gaussian bandwidth selection for manifold learning and classification. 1676-1712 - Shima Imani, Frank Madrid, Wei Ding, Scott E. Crouter, Eamonn J. Keogh:
Introducing time series snippets: a new primitive for summarizing long time series. 1713-1743 - Chenxu Wang, Yang Wang, Zhiyuan Zhao, Dong Qin, Xiapu Luo, Tao Qin:
Credible seed identification for large-scale structural network alignment. 1744-1776 - Jake H. Lee, Kiri L. Wagstaff:
Visualizing image content to explain novel image discovery. 1777-1804 - Vinícius M. A. de Souza, Denis Moreira dos Reis, André Gustavo Maletzke, Gustavo E. A. P. A. Batista:
Challenges in benchmarking stream learning algorithms with real-world data. 1805-1858 - Qian Ma, Wang-Chien Lee, Tao-Yang Fu, Yu Gu, Ge Yu:
MIDIA: exploring denoising autoencoders for missing data imputation. 1859-1897 - Alberto Lumbreras, Louis Filstroff, Cédric Févotte:
Bayesian mean-parameterized nonnegative binary matrix factorization. 1898-1935 - Hassan Ismail Fawaz, Benjamin Lucas, Germain Forestier, Charlotte Pelletier, Daniel F. Schmidt, Jonathan Weber, Geoffrey I. Webb, Lhassane Idoumghar, Pierre-Alain Muller, François Petitjean:
InceptionTime: Finding AlexNet for time series classification. 1936-1962 - Maryam Habibi, Johannes Starlinger, Ulf Leser:
DeepTable: a permutation invariant neural network for table orientation classification. 1963-1983 - Jadson Castro Gertrudes, Arthur Zimek, Jörg Sander, Ricardo J. G. B. Campello:
Correction to: A unified view of density-based methods for semi-supervised clustering and classification. 1984-1985
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