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Large scale fingerprint mining
Proceedings of the Tenth International Workshop on Multimedia Data Mining, 2010Support Vector Machines (SVM) project feature vectors into a linear or non-linear state space using kernel function(s) and attempts to maximize the margin between classes. The projection of feature vectors into a high dimensional hyperspace structure helps to provide sparse separable clusters of data.
Aaron K. Baughman +2 more
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Large-scale mine visualization using VRML
IEEE Computer Graphics and Applications, 1999Traditionally, mine plans and sections in 2D stored 3D information. We show that using VRML to model this information leads to new, interactive methods of data visualization. With the demise of the last working tin mine in Cornwall (South Crofty), perhaps the end has arrived for a way of life that saw the rise of Cornish miners and the engineering know-
Keith Russ, Andrew Wetherelt
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Large-scale multimodal mining for healthcare with mapreduce
Proceedings of the 1st ACM International Health Informatics Symposium, 2010Recent advances in healthcare and bioscience technologies and proliferation of portable medical devices have produce massive amount of multimodal data, the need for parallel processing is apparent for mining these data sets, which can range anywhere from tens of gigabytes, to terabytes or even petabytes.
Fei Wang 0002 +6 more
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Large-scale frequent subgraph mining in MapReduce
2014 IEEE 30th International Conference on Data Engineering, 2014Mining frequent subgraphs from a large collection of graph objects is an important problem in several application domains such as bio-informatics, social networks, computer vision, etc. The main challenge in subgraph mining is efficiency, as (i) testing for graph isomorphisms is computationally intensive, and (ii) the cardinality of the graph ...
Wenqing Lin +2 more
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Large Scale Graph Mining with G-Miner
Proceedings of the 2019 International Conference on Management of Data, 2019This Demo presents G-Miner, a distributed system for graph mining. The take-aways for Demo attendees are: (1) a good understanding of the challenges of various graph mining workloads; (2) useful insights on how to design a good system for graph mining by comparing G-Miner with existing systems on performance, expressiveness and user-friendliness; and ...
Hongzhi Chen +6 more
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Some Experiences on Large Scale Web Mining
2002Web mining is now a popular term of techniques to analize the data from World Wide Web(WWW). Here we will report some of our experiences in large scale web mining. The first is the development of user query recommendation system based on web usage mining of a commercial web directory service, and the second one is cyber community mining from Japan ...
Masaru Kitsuregawa +3 more
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Entity Relation Mining in Large-Scale Data
2015Currently, the web-based Named-Entity relationship extraction has been a new research field with a tremendous potential. The goal of web-based entity relationship extraction is to explore the relationship between a set of realistic entities. It’s a challenging research field and has a widely application value in the related fields of text mining.
Jingnan Li +5 more
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A Method of Large - Scale Log Pattern Mining
2018With the development of the telecommunication network, more and more devices are used in the network, which has been a burden for the network operation and maintenance. At the same time, network devices generate large amounts of log data every day, recording the activities of each device in detail.
Lu Li, Yi Man, Mo Chen
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Mining significant associations in large scale text corpora
2002 IEEE International Conference on Data Mining, 2002. Proceedings., 2003Mining large-scale text corpora is an essential step in extracting the key themes in a corpus. We motivate a quantitative measure for significant associations through the distributions of pairs and triplets of co-occurring words. We consider the algorithmic problem of efficiently enumerating such significant associations and present pruning algorithms ...
Prabhakar Raghavan, Panayiotis Tsaparas
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Distributed Large Scale Privacy-Preserving Deep Mining
2018 IEEE Third International Conference on Data Science in Cyberspace (DSC), 2018With the increasing of the data quantity and the continuous development in data mining applications, the introduction of deep learning is imminent. However, the combination of data mining and deep learning still faces many challenges in distributed large-scale environment, and one of the most immediate issues is to ensure the privacy of data when ...
Hao Xue +6 more
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