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Redescription Mining and Applications in Bioinformatics [chapter]

Naren Ramakrishnan, Mohammed Zaki
2009 Chapman & Hall/CRC Data Mining and Knowledge Discovery Series  
We present algorithms for redescription mining based on formal concept analysis and applications of redescription mining to multiple biological datasets.  ...  A critical need is the development of algorithms that can bridge, relate, and unify diverse categories of data descriptors. Redescription mining is such an approach.  ...  Acknowledgements This work was supported in part by NSF grants CNS-0615181, ITR-0428344, EMT-0829835, and CNS-0103708, and NIH Grant 1R01EB0080161-01A1.  ... 
doi:10.1201/9781420086850.ch22 fatcat:lelc5qyxrzggnkuahgu7ticihe

From Sets of Good Redescriptions to Good Sets of Redescriptions

Janis Kalofolias, Esther Galbrun, Pauli Miettinen
2016 2016 IEEE 16th International Conference on Data Mining (ICDM)  
Redescription mining aims at finding pairs of queries over data variables that describe roughly the same set of observations.  ...  These redescriptions can be used to obtain different views on the same set of entities. So far, redescription mining methods have aimed at listing all redescriptions supported by the data.  ...  Among existing redescription mining algorithms, we selected the ReReMi algorithm (Galbrun and Miettinen, 2012a) .  ... 
doi:10.1109/icdm.2016.0032 dblp:conf/icdm/KalofoliasGM16 fatcat:tbsngvyrgzc4nozeb4pqvqc4am

Interpreter of maladies: redescription mining applied to biomedical data analysis

Peter Waltman, Alex Pearlman, Bud Mishra
2006 Pharmacogenomics (London)  
Ramakrisnan and colleagues also proposed a novel tree-based algorithm (classification and regression trees [CART]wheels) for mining redescriptions, and then applied it to biological problems as a way of  ...  Furthermore, other extensions of redescription mining to handle dynamicdatasets (embodied in the Gene Ontology Algorithmic Logic and Information Extraction [GOALIE] toolkit) also enable the understanding  ... 
doi:10.2217/14622416.7.3.503 pmid:16610960 fatcat:shha2f42nrb3dft3rr3qgivyne

Finding Subgroups having Several Descriptions: Algorithms for Redescription Mining [chapter]

Arianna Gallo, Pauli Miettinen, Heikki Mannila
2008 Proceedings of the 2008 SIAM International Conference on Data Mining  
Given a 0-1 dataset, we consider the redescription mining task introduced by Ramakrishnan, Parida, and Zaki.  ...  Table 12 : Results from the DBLP data with the MID algorithm. Left formulae are over the conferences and right formulae are over the co-authors. 334 Left formula Right formula J  ...  Acknowledgments The authors are grateful to Gemma Garriga, Aristides Gionis, and Evimaria Terzi for their helpful comments.  ... 
doi:10.1137/1.9781611972788.30 dblp:conf/sdm/GalloMM08 fatcat:ipeiihouazhcnkpr7lqdaj7jii

Aligning Discourse and Argumentation Structures using Subtrees and Redescription Mining

Laurine Huber, Yannick Toussaint, Charlotte Roze, Mathilde Dargnat, Chloé Braud
2019 Proceedings of the 6th Workshop on Argument Mining  
Dans cet article, nous étudions la similarité entre structures argumentatives et discursives en alignant des sous-arbres dans un corpus annoté en RST et en structure argumentative.  ...  L'annotation multiple du corpus permet également de proposer un alignement entre les structures.  ...  Les sous-arbres sont extraits avec gSpan (Graph-Based Substructure Pattern Mining) (Yan et Han, 2002) , un algorithme qui, étant donné un ensemble de graphes GS, en extrait les sous-graphes fréquents.  ... 
doi:10.18653/v1/w19-4504 dblp:conf/argmining/HuberTRDB19 fatcat:nm2mckujtrbxnbygd52vih6t2m

A framework for redescription set construction

Matej Mihelčić, Sašo Džeroski, Nada Lavrač, Tomislav Šmuc
2017 Expert systems with applications  
We provide both theoretical and empirical comparison of the novel framework against current state of the art redescription mining algorithms and show that it represents more efficient and versatile approach  ...  Construction of large and heterogeneous redescription set relies on CLUS-RM algorithm and a novel, conjunctive refinement procedure that facilitates generation of larger and more accurate redescription  ...  Science Foundation (Pr. no. 9623: Machine Learning Algorithms for Insightful Analysis of Complex Data Structures).  ... 
doi:10.1016/j.eswa.2016.10.012 fatcat:e276m2xtuvecnjcotclh2wkxpi

Comparing apples and oranges: measuring differences between exploratory data mining results

Nikolaj Tatti, Jilles Vreeken
2012 Data mining and knowledge discovery  
Deciding whether the results of two different mining algorithms provide significantly different information is an important, yet understudied, open problem in exploratory data mining.  ...  We propose to meaningfully convert results into sets of noisy tiles, and compare between these sets by Maximum Entropy modelling and Kullback-Leibler divergence, well-founded notions from Information Theory  ...  Most importantly, we investigate the practical application of our measure for both mining redescriptions of (partial) results, and for application to the end of iterative data mining-giving algorithms  ... 
doi:10.1007/s10618-012-0275-9 fatcat:cdecq3yk2vgbppyr2kp6krub5a

Interactive Data Exploration Using Pattern Mining [chapter]

Matthijs van Leeuwen
2014 Lecture Notes in Computer Science  
To achieve this, pattern mining algorithms will need to be combined with techniques from both visualisation and human-computer interaction.  ...  The ultimate goal is to make pattern mining practically more useful, by enabling the user to interactively explore the data and identify interesting structure.  ...  Galbrun and Miettinen [26] introduced SIREN, a system for visual and interactive mining of geospatial redescriptions.  ... 
doi:10.1007/978-3-662-43968-5_9 fatcat:v3fifyrph5cercw5wip4wppv6m

Mining Complex Boolean Expressions for Sequential Equivalence Checking

Neha Goel, Michael S. Hsiao, Narendran Ramakrishnan, Mohammed J. Zaki
2010 2010 19th IEEE Asian Test Symposium  
In contrast to traditional learning methods, our mining algorithm can detect inductive invariants as well as illegal state cubes.  ...  We propose a novel technique to mine powerful and generalized boolean relations among flip-flops in a sequential circuit for sequential equivalence checking.  ...  There was none or very few one-to-one mapping among the flip-flops in the gray and one-hot encoded designs and also limited structural similarity internally.  ... 
doi:10.1109/ats.2010.81 dblp:conf/ats/GoelHRZ10 fatcat:nglhwyc4dnerhaf6kyqpbgo6um

Algorithms for storytelling

Deept Kumar, Naren Ramakrishnan, Richard F. Helm, Malcolm Potts
2006 Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining - KDD '06  
Index Terms-Data mining, mining methods and algorithms, retrieval models, graph and tree search strategies.  ...  This approach is practical and effective for mining large data sets and, at the same time, exploits the structure of partitions imposed by the given vocabulary.  ...  Algorithms for Redescription Mining There are many algorithms proposed for mining redescriptions, some based on systematic enumeration and pruning (e.g., CHARM-L [3] ) and some based on heuristic search  ... 
doi:10.1145/1150402.1150475 dblp:conf/kdd/KumarRHP06 fatcat:2mmzmwpyonemlf2h5epgol7zza

Mining Subjectively Interesting Attributed Subgraphs [article]

Anes Bendimerad, Ahmad Mel, Jefrey Lijffijt, Marc Plantevit, Céline Robardet, Tijl De Bie
2019 arXiv   pre-print
Community detection in graphs, data clustering, and local pattern mining are three mature fields of data mining and machine learning.  ...  The proposed pattern language improves upon prior work in being both highly flexible and intuitive. We show how an effective and principled algorithm can enumerate patterns of this language.  ...  We have shown how an effective and principled algorithm can enumerate patterns of this language.  ... 
arXiv:1905.03040v1 fatcat:hlkax52by5bg3a2gbveelewpwu

Intelligent simulation tools for mining large scientific data sets

Feng Zhao, Chris Bailey-Kellogg, Xingang Huang, Iván Ordóñez
1999 New generation computing  
This paper describes problems, challenges, and opportunities for intelligent simulation of physical systems.  ...  We i d e n tify the characteristics of intelligent s i m ulation and describe several concrete application examples.  ...  describes research conducted at Ohio State University a n d Xerox P alo Alto Research Center, supported in part by FZ's ONR YI grant N00014-97-1-0599, NSF NYI grant CCR-9457802, NSF grant CCR-9308639, and  ... 
doi:10.1007/bf03037240 fatcat:cut4xpervbegllpmmndj3ullsy

Physics-based feature mining for large data exploration

D.S. Thompson, R.K. Machiraju, Ming Jiang, J.S. Nair, G. Craclun, S.S.D. Venkata
2002 Computing in science & engineering (Print)  
The two approaches described here locate specific features through algorithms that are geared to those features' underlying physics.  ...  Evita The Evita system consists of three main components: an offline preprocessor, a server, and a client.  ...  Fowler and Bharat Soni of Mississippi State University and Will Schroeder of Rennselaer Polytechnic Institute.  ... 
doi:10.1109/mcise.2002.1014977 fatcat:m635ify4zfgvdostnwdv6brugy

SIAS-miner: mining subjectively interesting attributed subgraphs

Anes Bendimerad, Ahmad Mel, Jefrey Lijffijt, Marc Plantevit, Céline Robardet, Tijl De Bie
2019 Data mining and knowledge discovery  
Data clustering, local pattern mining, and community detection in graphs are three mature areas of data mining and machine learning.  ...  The proposed pattern syntax improves upon prior work in being both highly flexible and intuitive. Plus, we define an effective and principled algorithm to enumerate patterns of this syntax.  ...  SIAS-Miner algorithm SIAS-Miner mines interesting patterns using an enumerate-and-rank approach.  ... 
doi:10.1007/s10618-019-00664-w fatcat:am7miygbmjhaxlmg6buxjmt4eu

Grammatical Evolution to Mine OWL Disjointness Axioms Involving Complex Concept Expressions

Thu Huong Nguyen, Andrea G. B. Tettamanzi
2020 2020 IEEE Congress on Evolutionary Computation (CEC)  
To help overcome the knowledge-acquisition bottleneck, we propose a grammar-based genetic programming method for mining OWL class disjointness axioms from the Web of data.  ...  Discovering disjointness axioms is a very important task in ontology learning and knowledge base enrichment.  ...  Our research motto: AI in bridging social semantics and formal semantics on the Web.  ... 
doi:10.1109/cec48606.2020.9185681 dblp:conf/cec/NguyenT20a fatcat:gq2pcrl4i5grfnm4qxoj52tg3e
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