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Guest Editorial: Global modeling using local patterns

Johannes Fürnkranz, Arno Knobbe
2010 Data mining and knowledge discovery  
Open Access This article is distributed under the terms of the Creative Commons Attribution Noncommercial License which permits any noncommercial use, distribution, and reproduction in any medium, provided  ...  comments on the submitted papers contributed to this final selection of papers.  ...  Thus, any data mining operation that works on binary features can be employed in the subsequent phases of Pattern Subset Discovery and Global Modeling.  ... 
doi:10.1007/s10618-010-0169-7 fatcat:sskra5hm7jfnfm4qpzxshf6doa

Feature model extraction from large collections of informal product descriptions

Jean-Marc Davril, Edouard Delfosse, Negar Hariri, Mathieu Acher, Jane Cleland-Huang, Patrick Heymans
2013 Proceedings of the 2013 9th Joint Meeting on Foundations of Software Engineering - ESEC/FSE 2013  
While each individual product description provides only a partial view of features in the domain, a large set of descriptions can provide fairly comprehensive coverage.  ...  Feature Models (FMs) are used extensively in software product line engineering to help generate and validate individual product configurations and to provide support for domain analysis.  ...  (i) Implies constraints are binary implications between two features (A ⇒ B). press that the presence of a feature in a configuration implies the absence of another feature (A ⇒ ¬B).  ... 
doi:10.1145/2491411.2491455 dblp:conf/sigsoft/DavrilDHACH13 fatcat:3ckd3qv3s5amvjjqilihlxg464

Constraint based temporal event sequence mining for Glioblastoma survival prediction

Kunal Malhotra, Shamkant B. Navathe, Duen Horng Chau, Costas Hadjipanayis, Jimeng Sun
2016 Journal of Biomedical Informatics  
We proposed sequential mining algorithms with novel clinical constraints, namely, 'exact-order' and 'temporal overlap' constraints, to extract treatment patterns as features used in predictive modeling  ...  Conclusions: We demonstrated the importance of diverse sources of features in predicting GBM patient survival outcome.  ...  Acknowledgment This work was supported by the National Science Foundation, award IIS-1418511 and CCF-1533768, Children's Healthcare of Atlanta, CDC I-SMILE project, Google Faculty Award, AWS Research Award  ... 
doi:10.1016/j.jbi.2016.03.020 pmid:27064059 fatcat:mcx27o6crra3xhspes5tecztba

A Probabilistic Substructure-Based Approach for Graph Classification

H.D.K. Moonesinghe, Hamed Valiza, Samah Fodeh, Pang-Ning Tan
2007 19th IEEE International Conference on Tools with Artificial Intelligence(ICTAI 2007)  
More specifically, we use a frequent subgraph mining algorithm to construct substructure based descriptors and apply the maximum entropy principle to convert the local patterns into a global classification  ...  model for graph data.  ...  George Karypis for providing the PAFI software containing FSG graph mining algorithm.  ... 
doi:10.1109/ictai.2007.159 dblp:conf/ictai/MoonesingheVFT07 fatcat:zo36nslkczafxn2wfqd5ztktsy

A Survey on Binary Code Vulnerability Mining Technology

Pengzhi Xu, Zetian Mai, Yuhao Lin, Zhen Guo, Victor S. Sheng
2021 Journal of Information Hiding and Privacy Protection  
Therefore, the research on the vulnerability mining technology of binary code has strong practical value.  ...  Finally, based on the existing research work, this article puts forward the prospect of the future research on the technology of binary program vulnerability mining.  ...  Acknowledgement: The authors would like to thank the partners for their hard work, as well as the reviewers for their detailed review and valuable comments.  ... 
doi:10.32604/jihpp.2021.027280 fatcat:3l22xfqflnafdpydya45std7ey

Discrete Multi-modal Hashing with Canonical Views for Robust Mobile Landmark Search [article]

Lei Zhu, Zi Huang, Xiaobai Liu, Xiangnan He, Jingkuan Song, Xiaofang Zhou
2017 arXiv   pre-print
Finally, compact binary codes are learned on intermediate representation within a tailored discrete binary embedding model which preserves visual relations of images measured with canonical views and removes  ...  In this part, we develop a new augmented Lagrangian multiplier (ALM) based optimization method to directly solve the discrete binary codes.  ...  ACKNOWLEDGMENT The authors would like to thank the anonymous reviewers for their constructive and helpful suggestions.  ... 
arXiv:1707.04047v1 fatcat:in4v4b4i2zarblkbuj2ajba254

From Local Patterns to Classification Models [chapter]

Björn Bringmann, Siegfried Nijssen, Albrecht Zimmermann
2010 Inductive Databases and Constraint-Based Data Mining  
The aim of these techniques is to obtain classifiers of better predictive performance as compared to greedily constructed models, as well as to allow the construction of predictive models for data not  ...  algorithms that integrate pattern mining and model construction.  ...  to use patterns in classification models. features, and the construction of a feature table is not a separate phase.  ... 
doi:10.1007/978-1-4419-7738-0_6 fatcat:mbyja6yozzfn3m47c7t65gj5gm

On breaking the curse of dimensionality in reverse engineering feature models

Jean-Marc Davril, Mathieu Acher, Guillaume Bécan, Patrick Heymans
2015 International Configuration Workshop  
In this paper, we discuss motivations for the development of dimensionality reduction techniques for product lines in order to support the extraction of feature models in the case of high-dimensional product  ...  As the manual construction of feature models proves to be a time-consuming and error prone task, researchers have proposed various approaches for automatically deriving feature models from available product  ...  High dimensionality in FM synthesis We now list the variability structures that are commonly mined from configuration matrices by existing FM synthesis approaches. • Binary implications: Binary implications  ... 
dblp:conf/confws/DavrilABH15 fatcat:zkcexgshinbynm34gmdl3jfvv4

Unsupervised Visual Representation Learning by Graph-Based Consistent Constraints [chapter]

Dong Li, Wei-Chih Hung, Jia-Bin Huang, Shengjin Wang, Narendra Ahuja, Ming-Hsuan Yang
2016 Lecture Notes in Computer Science  
We demonstrate the effectiveness of the proposed unsupervised constraint mining method in two settings: (1) unsupervised feature learning and (2) semi-supervised learning.  ...  In this paper, we address the problem of unsupervised visual representation learning from a large, unlabeled collection of images.  ...  Fig. 2 shows the overview of the two settings. Unsupervised Constraint Mining In this section, we introduce the unsupervised constraint mining algorithm.  ... 
doi:10.1007/978-3-319-46493-0_41 fatcat:g5pat4ss45a5liln65msaejcti

Fair Decision Rules for Binary Classification [article]

Connor Lawless, Oktay Gunluk
2021 arXiv   pre-print
In this paper we consider the problem of building Boolean rule sets in disjunctive normal form (DNF), an interpretable model for binary classification, subject to fairness constraints.  ...  The socially sensitive nature of some of these applications together with increasing regulatory constraints has necessitated the need for algorithms that are both fair and interpretable.  ...  Note that when the input data is binary-valued, a DNF-rule set simply corresponds to checking whether a subset of features satisfies a specific combination of 0s and 1s. 0-1 loss When constructing a  ... 
arXiv:2107.01325v1 fatcat:rgx6gfusrneqhesmzyyjnragrq

APPLICATION OF OPERATIONS RESEARCH IN OPEN PIT MINE PLANNING AND A CASE STUDY IN SINQUYEN COPPER DEPOSIT, VIETNAM

N. L. Mai, E. Topal, O. Erten
2016 Mining science and technology  
In this paper, we review the history and methodology of applying operations research in long-term production scheduling and a case study in Sin Quyen copper deposit, Vietnam.  ...  APPLICATION OF OPERATIONS RESEARCH IN OPEN PIT MINE PLANNING AND A CASE STUDY IN SINQUYEN COPPER DEPOSIT, VIETNAM Operations research has been applied to open pit mine planning since 1960s.  ...  Therefore, if an IP model is constructed to optimise this hypothetical mine planning problem, its task is to return output of binary variables correctly, i.e. those of blocks 1, 2, 3, and 5 are 1, meanwhile  ... 
doi:10.17073/2500-0632-2016-3-22-27 fatcat:vkav5hzluzbwxjzlqgwqpzvyle

An Image Processing based Algorithm for Discovering Co-Location Patterns

Shahbaz Ahmad, Muhammad Asif
2016 International Journal of Computer Applications  
It converts the image into binary image and then uses the concept of neighbourhood relationship (materialized using distance threshold) and confidence measure to mine the patterns.  ...  Spatial co-location patterns represents the subset of Boolean spatial features (e.g. Frontage roads, freeways) whose instances are often located in close geographic proximity.  ...  ≤ are named as spatial binary constraint  ... 
doi:10.5120/ijca2016912338 fatcat:i37fysswtffbzmifuf6q4zv3ny

Behavioral Constraint Template-Based Sequence Classification [chapter]

Johannes De Smedt, Galina Deeva, Jochen De Weerdt
2017 Lecture Notes in Computer Science  
In this paper we present the interesting Behavioral Constraint Miner (iBCM), a new approach towards classifying sequences.  ...  These patterns have a broad range of characteristics and go beyond the typical sequence mining representation, allowing for a more precise and concise way of capturing sequential information in a database  ...  All techniques were first employed to generate interesting sequences, and next to build a predictive model by using the presence of the sequences as a binary feature.  ... 
doi:10.1007/978-3-319-71246-8_2 fatcat:ge6uq4spurbe5a5vid3h3fivqm

Performance Optimization Method of Community Sports Facilities Configuration Based on Linear Planning Model

Xuefeng Tan, Chenggen Guo, Pu Sun, Shaojie Zhang, Harish Garg
2022 Complexity  
model in order to reduce the performance capital investment.  ...  Establish a community sports facility configuration performance optimization model, delineate the boundaries of the optimal solution by bifurcation, and set the feasible domain of the performance optimization  ...  Acknowledgments is research was funded by 2020 Beijing Social Science Fund Planning Project: Research on the Content Construction of Beijing Community Residents' Fitness Service System from the perspective  ... 
doi:10.1155/2022/4489802 fatcat:x4dlrrqu55gjvjczwpiqhc5jde

cLP: Linear programming with biological constraints and its application in classification problems

Manli Zhou, Youxi Luo, Guoqin Mai, Fengfeng Zhou
2014 2014 8th International Conference on Systems Biology (ISB)  
Abstract-Feature selection represents a major challenge in the biomedical data mining problem, and numerous algorithms have been proposed to select an optimal subset of features with the best classification  ...  The proposed algorithm incorporates the biomedical knowledge as constraints in the linear programming based optimization model.  ...  CONCLUSIONS This study explores the possibility of combining the merits of both biomedical knowledge and data mining algorithms, by adding constraints for the linear programming model.  ... 
doi:10.1109/isb.2014.6990747 fatcat:mvutjccsrvdada7p6r4nxj642q
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