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Temporal Probabilistic Concepts from Heterogeneous Data Sequences [chapter]

Sally McClean, Bryan Scotney, Fiona Palmer
2002 Lecture Notes in Computer Science  
We consider the problem of characterisation of sequences of heterogeneous symbolic data that arise from a common underlying temporal pattern.  ...  On the basis of these mappings we use maximum likelihood techniques to handle uncertainty in the data and learn local probabilistic concepts represented by individual temporal instances of the sequences  ...  In this paper we are concerned, in particular, with identifying temporal probabilistic concepts from heterogeneous data sequences.  ... 
doi:10.1007/3-540-46019-5_15 fatcat:c3ovf7ul3jaqthittonjwkecy4

Feature-rich networks: going beyond complex network topologies

Roberto Interdonato, Martin Atzmueller, Sabrina Gaito, Rushed Kanawati, Christine Largeron, Alessandra Sala
2019 Applied Network Science  
Attributed Graphs, Heterogeneous Networks, Multilayer Networks, Temporal Networks, Location-aware Networks, Knowledge Networks, Probabilistic Networks, and many other task-driven and data-driven models  ...  The growing availability of multirelational data gives rise to an opportunity for novel characterization of complex real-world relations, supporting the proliferation of diverse network models such as  ...  , e. g. networks modeling uncertain relations, such as sensor networks, or networks inferred from survey data ("Probabilistic networks" section).  ... 
doi:10.1007/s41109-019-0111-x fatcat:obdhovj2kffqbe6drixhw3bp5q

A study on sequential pattern mining on chemical information

S Sathya, N Rajendran
2018 International Journal of Engineering & Technology  
Data mining (DM) is used for extracting the useful and non-trivial information from the large amount of data to collect in many and diverse fields.  ...  However, large-scale sequential data is a fundamental problem like higher classification time and bonding time in data mining with many applications.  ...  The separation of the meaningful and essential temporal structures from largescale sequential data is a key issue in data mining with many applications like mining the customer purchasing sequences, motion  ... 
doi:10.14419/ijet.v7i2.33.14828 fatcat:4xofoypxcnhodolqoywc256mqe

Mining Electronic Medical Records to Explore the Linkage between Healthcare Resource Utilization and Disease Severity in Diabetic Patients

Noah Lee, Andrew F. Laine, Jianying Hu, Fei Wang, Jimeng Sun, Shahram Ebadollahi
2011 2011 IEEE First International Conference on Healthcare Informatics, Imaging and Systems Biology  
We demonstrate our framework on synthetic data and on EHRs together with an extensive validation involving over 70,000 computed latent factor models.  ...  Within this realm we present a novel temporal event matrix representation and learning framework that discovers complex latent event patterns, which are easily interpretable by humans.  ...  of temporal operators and concepts.  ... 
doi:10.1109/hisb.2011.34 dblp:conf/hisb/LeeLHWSE11 fatcat:s5vokrsaxrhubb3lubiogh7lga

Probabilistic change detection and visualization methods for the assessment of temporal stability in biomedical data quality

Carlos Sáez, Pedro Pereira Rodrigues, João Gama, Montserrat Robles, Juan M. García-Gómez
2014 Data mining and knowledge discovery  
This work establishes the temporal stability as a data quality dimension and proposes new methods for its assessment based on a probabilistic framework.  ...  These problems can be seen as a lack of data temporal stability.  ...  Gregor Stiglic, from the Univeristy of Maribor, Slovenia, for his support on the NHDS data.  ... 
doi:10.1007/s10618-014-0378-6 fatcat:bmj7luikffachoj7op7vvwrqyq

Challenges on Probabilistic Modeling for Evolving Networks [article]

Jianguo Ding, Pascal Bouvry
2013 arXiv   pre-print
This paper presents a survey on probabilistic modeling for evolving networks and identifies the new challenges which emerge on the probabilistic models and optimization strategies in the potential application  ...  With the emerging of new networks, such as wireless sensor networks, vehicle networks, P2P networks, cloud computing, mobile Internet, or social networks, the network dynamics and complexity expands from  ...  A probabilistic dynamic model will be considered as a sequence of graphs indexed by the time, representing the temporal evolution of a system.  ... 
arXiv:1304.7820v2 fatcat:qvtskgtvpvh2npqbyjlghyu774

Semantic Event Fusion of Different Visual Modality Concepts for Activity Recognition

Carlos F. Crispim-Junior, Vincent Buso, Konstantinos Avgerinakis, Georgios Meditskos, Alexia Briassouli, Jenny Benois-Pineau, Ioannis Yiannis Kompatsiaris, Francois Bremond
2016 IEEE Transactions on Pattern Analysis and Machine Intelligence  
Combining multimodal concept streams from heterogeneous sensors is a problem superficially explored for activity recognition.  ...  It separates semantic modeling from raw sensor data by using an intermediate semantic representation, namely concepts.  ...  ACKNOWLEDGMENTS The research leading to these results has received funding from the European Research  ... 
doi:10.1109/tpami.2016.2537323 pmid:26955015 fatcat:b3v4qtxjtvg23lljhqy4lma6om

Analyzing Phylogenetic Trees with Timed and Probabilistic Model Checking: The Lactose Persistence Case Study

José Ignacio Requeno, José Manuel Colom
2014 Journal of Integrative Bioinformatics  
Phylogenetic trees are considered as transition systems over which we interrogate phylogenetic questions written as formulas of temporal logic.  ...  Introduction A phylogenetic tree is a description of the evolution process which is discovered via molecular sequencing data and morphological data matrices [1] .  ...  Later, Section 5 shows the experimentation with a temporal and probabilistic model checking tool.  ... 
doi:10.1515/jib-2014-248 fatcat:c5byw44cvzbqpdbd2krpkv7yua

Analyzing phylogenetic trees with timed and probabilistic model checking: the lactose persistence case study

José Ignacio Requeno, José Manuel Colom
2014 Journal of Integrative Bioinformatics  
Phylogenetic trees are considered as transition systems over which we interrogate phylogenetic questions written as formulas of temporal logic.  ...  Introduction A phylogenetic tree is a description of the evolution process which is discovered via molecular sequencing data and morphological data matrices [1] .  ...  Later, Section 5 shows the experimentation with a temporal and probabilistic model checking tool.  ... 
doi:10.2390/biecoll-jib-2014-248 pmid:25339082 fatcat:m76d54tlsnhhfk7t7b6gwvtu5e

Design of a probabilistic ontology-based clinical decision support system for classifying temporal patterns in the ICU: A sepsis case study

Femke Ongenae, Tom Dhaene, Filip De Turck, Dominique Benoit, Johan Decruyenaere
2010 2010 IEEE 23rd International Symposium on Computer-Based Medical Systems (CBMS)  
First, the time-dependent data is gathered from heterogeneous sources and the semantics are made explicit by using an ontology.  ...  Second, Machine Learning techniques detect trends in the semantic time series data that indicate that a patient has a particular pathology.  ...  This ontology is used to annotate data with their meaning and express the relationships with other data. Moreover, it allows the integration of data coming from heterogeneous sources.  ... 
doi:10.1109/cbms.2010.6042676 dblp:conf/cbms/OngenaeDTBD10 fatcat:cvoopcruqff57oxghxqk7q5rpa

An assessment of computational methods for estimating purity and clonality using genomic data derived from heterogeneous tumor tissue samples

V. K. Yadav, S. De
2014 Briefings in Bioinformatics  
Deconvolution of genomic data from heterogeneous samples provides a powerful tool to address this limitation.  ...  We discuss several computational tools, which enable deconvolution of genomic and transcriptomic data from heterogeneous samples. We also performed a systematic comparative assessment of these tools.  ...  The comparative analysis results published here are in part based upon data generated by The Cancer Genome Atlas pilot project [56] established by the NCI and NHGRI (dbGAP accession ID: phs000178.v8.  ... 
doi:10.1093/bib/bbu002 pmid:24562872 pmcid:PMC4794615 fatcat:mcg7fqdg65gbhnc7okknmpz774

The ERC webdam on foundations of web data management

Serge Abiteboul, Pierre Senellart, Victor Vianu
2012 Proceedings of the 21st international conference companion on World Wide Web - WWW '12 Companion  
Although the proposal addresses fundamental issues, its goal is to serve as the basis for future software development for Web data management.  ...  The goal is to develop a formal model for Web data management that would open new horizons for the development of the Web in a well-principled way, enhancing its functionality, performance, and reliability  ...  It uses an application taken from the movie industry, that specifies task sequencing when managing actors applications for roles in films.  ... 
doi:10.1145/2187980.2188011 dblp:conf/www/AbiteboulSV12 fatcat:hfjnacjft5e2jiyjfb5gyviimy

Analyzing multimodal time series as dynamical systems

Shohei Hidaka, Chen Yu
2010 International Conference on Multimodal Interfaces and the Workshop on Machine Learning for Multimodal Interaction on - ICMI-MLMI '10  
To do so, we develop a Bayesian framework for probabilistic symbolization and demonstrate that the approach can be successfully applied to both simulated data and empirical data from multimodal agent-agent  ...  We propose a novel approach to discovering latent structures from multimodal time series. We view a time series as observed data from an underlying dynamical system.  ...  ACKNOWLEDGEMENTS We would like to thank Amanda Favata, Char Wozniak and Andrew Filipowicz for data collection. Thomas Smith is a great help in data pre-processing.  ... 
doi:10.1145/1891903.1891968 dblp:conf/icmi/HidakaY10 fatcat:5df37633f5h6zgzn527jezbhjm

Capsule Reviews

2005 Computer journal  
from data.  ...  Since temporal functional dependencies are an important data dependency in temporal relational databases, and since temporal data dependencies can be obtained directly from real world semantics instead  ... 
doi:10.1093/comjnl/bxh069 fatcat:7mgwvsfdbnc3tjhkyvjhr3w7by

Guest Editors' Introduction to the Special Issue on Multimodal Human Pose Recovery and Behavior Analysis

Sergio Escalera, Jordi Gonzalez, Xavier Baro, Jamie Shotton
2016 IEEE Transactions on Pattern Analysis and Machine Intelligence  
coming from different sensors, data fusion, and temporal series analysis.  ...  single images and image sequences.  ...  Li proposes a spatio-temporal feature extracted from RGB-D data, namely Mixed Features around Sparse Keypoints (MFSK).  ... 
doi:10.1109/tpami.2016.2557878 fatcat:ee3j7nre4fgdtjrozavgexvhi4
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