Filters








69,050 Hits in 3.7 sec

Mining Multi-Relational Gradual Patterns [chapter]

NhatHai Phan, Dino Ienco, Donato Malerba, Pascal Poncelet, Maguelonne Teisseire
2015 Proceedings of the 2015 SIAM International Conference on Data Mining  
The interestingness measure for this class of "relational gradual patterns" is defined on the basis of both Kendall's τ and gradual supports.  ...  The efficiency of the algorithms is empirically validated, and the usefulness of relational gradual patterns is proved on some real-world databases.  ...  To discover this kind of patterns, we first introduce the concept of multi-relational gradual pattern (multi-rgp), and its associated support measures based on Kendall's τ [3] and gradual support [5  ... 
doi:10.1137/1.9781611974010.95 dblp:conf/sdm/PhanIMPT15 fatcat:lz7s6ezba5aqlgbj5hm4eihdk4

Mining Multi-Relational Gradual Patterns Mining Multi-Relational Gradual Patterns

Nhathai Phan, Dino Ienco, Donato Malerba, Pascal Poncelet, Nhathai Phan, Dino Ienco, Donato Malerba, Pascal Poncelet, Maguelonne Mining, Nhathai Phan, Dino Ienco, Donato Malerba (+1 others)
2015 Relational Gradual Patterns. International Conference on Data Mining   unpublished
The interestingness measure for this class of "relational gradual patterns" is defined on the basis of both Kendall's τ and gradual supports.  ...  The efficiency of the algorithms is empirically validated, and the usefulness of relational gradual patterns is proved on some real-world databases.  ...  To discover this kind of patterns, we first introduce the concept of multi-relational gradual pattern (multi-rgp), and its associated support measures based on Kendall's τ [3] and gradual support [5  ... 
fatcat:iqafapaf4jbbzhp5mh3fdntrg4

Multi-Core Parallel Gradual Pattern Mining Based on Multi-Precision Fuzzy Orderings

Nicolas Sicard, Yogi Aryadinata, Federico Del Razo Lopez, Anne Laurent, Perfecto Flores
2013 Algorithms  
In recent years, such patterns have been studied more and more from the data mining point of view.  ...  Gradual patterns aim at describing co-variations of data such as the higher the size, the higher the weight.  ...  Parallel Fuzzy Gradual Pattern Mining Based on Multi-Precision Fuzzy Orderings In this section, we detail our approach.  ... 
doi:10.3390/a6040747 fatcat:dfjacfumtbdxjk7hpo7dximz24

Scalability and Fuzzy Systems: What Parallelization Can Do [chapter]

Malaquias Q. Flores, Federico Del Razo, Anne Laurent, Nicolas Sicard
2013 Studies in Computational Intelligence  
gradual dependencies, and fuzzy tree  ...  More precisely, we present the parallelization of fuzzy database mining algorithms on multi-core architectures of four knowledge discovery paradigms, namely fuzzy association rules, fuzzy clustering, fuzzy  ...  In this framework, a gradual pattern is defined as a relation of simultaneous variation between values of the attributes of two or more gradual items.  ... 
doi:10.1007/978-3-319-00954-4_13 fatcat:okkfilr5njdmrbijkdeyryuqca

Efficient Parallel Mining of Gradual Patterns on Multicore Processors [chapter]

Anne Laurent, Benjamin Négrevergne, Nicolas Sicard, Alexandre Termier
2012 Studies in Computational Intelligence  
Gradual patterns highlight complex order correlations of the form "The more/less X, the more/less Y". Only recently algorithms have appeared to mine efficiently gradual rules.  ...  Mining gradual patterns plays a crucial role in many real world applications where huge volumes of complex numerical data must be handled, e.g., biological databases, survey databases, data streams or  ...  Table 1 3 Related Work In this section, we discuss the related works on mining gradual patterns as well as on parallel frequent pattern mining.  ... 
doi:10.1007/978-3-642-25838-1_8 fatcat:ezet7xkfgrgyrld4zrujqzt3qq

PGP-mc: Towards a Multicore Parallel Approach for Mining Gradual Patterns [chapter]

Anne Laurent, Benjamin Negrevergne, Nicolas Sicard, Alexandre Termier
2010 Lecture Notes in Computer Science  
Gradual patterns highlight complex order correlations of the form "The more/less X, the more/less Y". Only recently algorithms have appeared to mine efficiently gradual rules.  ...  However, due to the complexity of mining gradual rules, these algorithms cannot yet scale on huge real world datasets.  ...  The outline of this paper is as follows: In Section 2, we explain the notion of gradual itemsets. In Section 3, we present the related works on gradual patterns and parallel pattern mining.  ... 
doi:10.1007/978-3-642-12026-8_8 fatcat:wek6ft3oaffu3dxcbl2cnjmqfy

Multi-Level Sequential Pattern Mining Based on Prime Encoding

Sun Lianglei, Li Yun, Yin Jiang
2012 Physics Procedia  
multi-level sequential pattern and cross-level sequential pattern respectively.  ...  Experimental results show that the algorithm can effectively extract multi-level and cross-level sequential pattern from the sequence database.  ...  for mining multi-level sequential pattern and cross-level sequential pattern respectively.  ... 
doi:10.1016/j.phpro.2012.02.258 fatcat:cp4wzsh6v5b6hogj4tdp45vd5q

Research on Intrusion Event Sequence Correlation Method for Privacy Protection

Duan Xueying
2014 International Journal of Security and Its Applications  
On the basis of analyzing the characteristics of multi-step attack, proposed the use of sequential pattern mining techniques associated with rapid multi-step attack methods QSPM.  ...  And compared with typical sequential pattern mining algorithm. Results show the new methods have a positive accuracy and efficiency.  ...  They are engaged in mining cycle mode and event sequential pattern mining, and other related research work in the field of data mining and gradually formed a 354 Copyright ⓒ 2014 SERSC new research direction-sequential  ... 
doi:10.14257/ijsia.2014.8.6.30 fatcat:4meaaex4tbfcvglqgfxykntwvy

Machine Learning Paradigms for Modeling Spatial and Temporal Information in Multimedia Data Mining

Djamel Bouchaffra, Abbes Amira, Ce Zhu, Chu-Song Chen
2010 Advances in Artificial Intelligence  
Advances in multimedia understanding are related directly to advances in signal processing, computer vision, machine learning, pattern recognition, multimedia databases, and smart sensors.  ...  algorithms and advanced related topics.  ...  Advances in multimedia understanding are related directly to advances in signal processing, computer vision, machine learning, pattern recognition, multimedia databases, and smart sensors.  ... 
doi:10.1155/2010/312350 fatcat:ahrarqlanjehnnviojdzfjlsve

DDDM 2008 Message and Committee

2008 2008 IEEE International Conference on Data Mining Workshops  
Thonnard and Dacier proposed a multi-dimensional knowledge discovery and data mining methodology to discover actionable knowledge related to Internet threats, taking into account domain expert guidance  ...  D3M aims to construct next-generation methodologies, techniques and tools for a paradigm shift from data-centered hidden pattern mining to domain-driven actionable knowledge delivery.  ... 
doi:10.1109/icdmw.2008.7 fatcat:fzp73mltjbbw3fs6tmrhsg7w4y

Discovering Frequent Gradual Itemsets with Imprecise Data [article]

Michaël Chirmeni Boujike, Jerry Lonlac, Norbert Tsopze, Engelbert Mephu Nguifo
2020 arXiv   pre-print
Recently, these types of patterns have caught the attention of the data mining community, where several methods have been defined to automatically extract and manage these patterns from different data  ...  However, these methods are often faced the problem of managing the quantity of mined patterns, and in many practical applications, the calculation of all these patterns can prove to be intractable for  ...  [26] proposes the relational gradual pattern concept, which enables to examine the correlations between attributes from a graduality point of view in multi-relational data.  ... 
arXiv:2005.11045v1 fatcat:3bocy7mm3vaobmpdopjz7frsrq

Impacts of Large-Scale Open-Pit Coal Base on the Landscape Ecological Health of Semi-Arid Grasslands

Zhenhua Wu, Shaogang Lei, Qingqing Lu, Zhengfu Bian
2019 Remote Sensing  
Result indicated that coal mining causes gradual increase of landscape patches, landscape fragmentation, gradual decline of landscape connectivity, complexity and irregularity of landscape shape, enhancement  ...  of landscape heterogeneity and complexity, gradual decline of landscape stability, gradual decrease of grassland landscape and annual increase of unhealthy grassland landscape.  ...  Landscapes related to mining, towns, industrial storage, and road networks expand every year by occupying a large number of grasslands, which results in a gradual decrease of overall grassland areas, as  ... 
doi:10.3390/rs11151820 fatcat:yq5e7ymctbcd3jfoabrwhwiroa

Research of Data Mining of Association Pattern Pairs in Multidimensional Structured Database

Zhang Jing, Huang Xiantong, Yang Xinfeng
2011 Energy Procedia  
Secondly, we propose a new data mining problem, the structure of the database to find frequent patterns associated pair.  ...  The new algorithm is also discussed in the one-dimensional and multi-dimensional structure of the database found on the applicability of the model and to assess the efficiency of the new algorithm.  ...  Multidimensional database as a dig at one of the problems in [9] [10] proposed a multi-dimensional sequential pattern mining.  ... 
doi:10.1016/j.egypro.2011.10.347 fatcat:vxchwunkgjfgxpgeqcbforvrm4

Image Retrieval and Re-Ranking Techniques - A Survey

Mayuri D. Joshi, Revati M. Deshmukh, Kalashree N.Hemke, Ashwini Bhake, Rakhi Wajgi
2014 Signal & Image Processing An International Journal  
The pattern is simple the strong performing modality advances from weaker modalities and vice versa.  ...  RELATED WORKS We briefly divide the related works for visual search re-ranking into two groups: recurrent pattern mining and multimodality fusion.  ...  Two general approaches are categorised visual pattern mining [6] and multi modality fusion [1], [2] .The former approach mines the recurrent patterns, disregarding the degree of complexity, i.e. either  ... 
doi:10.5121/sipij.2014.5201 fatcat:gusz6wizpbgsfgjt6asf7s44fi

Comparsion analysis of data mining models applied to clinical research in Traditional Chinese Medicine

Yufeng Zhao, Qi Xie, Liyun He, Baoyan Liu, Kun Li, Xiang Zhang, Wenjing Bai, Lin Luo, Xianghong Jing, Ruili Huo
2014 Journal of Traditional Chinese Medicine  
METHODS: Clinical issues based on data mining models were comprehensively summarized from four significant elements of the clinical studies: symptoms, symptom patterns, herbs, and efficacy.  ...  CONCLUSION: By aiming at the special features of different data mining models, the clinical doctors could select the suitable data mining models to resolve the TCM problem.  ...  However, the pattern classification and core structure of herbs do not appropriately transform into multi-class or multi-type classifications.  ... 
doi:10.1016/s0254-6272(15)30074-1 fatcat:jav4vhd4f5apvhmnxc72zv24aa
« Previous Showing results 1 — 15 out of 69,050 results