NLP Project: Machine Comprehension Using Attention-Based LSTM Encoder-Decoder...
Daedalus
1. R. Ortale (2) , E. Ritacco (2) , N. Pelekis (3) R. Trasarti (1), F. Giannotti (1) , C. Renso (1) , G. Costa (2) , G. Manco (2) , Y. Theodoridis (3) (1) ISTI-CNR , Pisa, Italy (2) ICAR-CNR , Rende (CS), Italy (3) Univerity of Pireus , Athens, Greece The DAEDALUS Framework: Progressive Querying and Mining of Movement Data
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5. The Two Worlds framework Filtering operators : manipulate basic objects. Mining operators : extract properties from samples. K:D M Population operators : detect samples exhibiting properties. P:DxM D
6. From Two Worlds to Daedalus Hermes is the repository of both data and models. Hermes has been extended to represent objects in M-World: Model_TAS, (T-Pattern) The mining operator is realized by calling an external algorithm. The populate operator has been defined on Hermes
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9. Model representation For T-Pattern, a Model_Tas is defined in Hermes as: Sequence of <Region, <Minimum travel time, Maximum travel time>> Model_TAS: VARRAY <SDO_Geometry, <TAU_TLL.interval, TAU_TLL.interval>> <A,<10,30>; B<5,60>; C<nd,nd>> A B c 10,30 5,60
10. The Daedalus system DAEDALUS provides a Data Mining Query Language based on SQL, that includes basic mechanisms for interactive queries on D-World and M-World
11. The Daedalus System Architecture HERMES DMQL query Model_TAS Package MOD Mediator Controller Parser Object Translator Mining Engine T-Pattern Algorithm User Interface TAS Translation Library Moving_point Translation Library Object Store
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Editor's Notes
A flurry of research has covered with spatio-temporal data analysis from different perspectives. The definition of new movement patterns. The development of solutions to algorithmic issues, with which to improve existing pattern-mining schemes Little attention has been paid to the definition of a unifying framework, wherein to set the above pattern-mining tools as specific components of the knowledge discovery process. Knowledge discovery is a multi-step process, that involves data preprocessing, different pattern mining stages and pattern postprocessing.
A flurry of research has covered with spatio-temporal data analysis from different perspectives. The definition of new movement patterns. The development of solutions to algorithmic issues, with which to improve existing pattern-mining schemes Little attention has been paid to the definition of a unifying framework, wherein to set the above pattern-mining tools as specific components of the knowledge discovery process. Knowledge discovery is a multi-step process, that involves data preprocessing, different pattern mining stages and pattern postprocessing.
![Motivation ,[object Object],[object Object]](data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7)