NexTech 2021 Congress
October 03, 2021 to October 07, 2021 - Barcelona, Spain

  • UBICOMM 2021, The Fifteenth International Conference on Mobile Ubiquitous Computing, Systems, Services and Technologies
  • ADVCOMP 2021, The Fifteenth International Conference on Advanced Engineering Computing and Applications in Sciences
  • SEMAPRO 2021, The Fifteenth International Conference on Advances in Semantic Processing
  • AMBIENT 2021, The Eleventh International Conference on Ambient Computing, Applications, Services and Technologies
  • EMERGING 2021, The Thirteenth International Conference on Emerging Networks and Systems Intelligence
  • DATA ANALYTICS 2021, The Tenth International Conference on Data Analytics
  • GLOBAL HEALTH 2021, The Tenth International Conference on Global Health Challenges
  • CYBER 2021, The Sixth International Conference on Cyber-Technologies and Cyber-Systems

SoftNet 2021 Congress
October 03, 2021 to October 07, 2021 - Barcelona, Spain

  • ICSEA 2021, The Sixteenth International Conference on Software Engineering Advances
  • ICSNC 2021, The Sixteenth International Conference on Systems and Networks Communications
  • CENTRIC 2021, The Fourteenth International Conference on Advances in Human-oriented and Personalized Mechanisms, Technologies, and Services
  • VALID 2021, The Thirteenth International Conference on Advances in System Testing and Validation Lifecycle
  • SIMUL 2021, The Thirteenth International Conference on Advances in System Simulation
  • SOTICS 2021, The Eleventh International Conference on Social Media Technologies, Communication, and Informatics
  • INNOV 2021, The Tenth International Conference on Communications, Computation, Networks and Technologies
  • HEALTHINFO 2021, The Sixth International Conference on Informatics and Assistive Technologies for Health-Care, Medical Support and Wellbeing

NetWare 2021 Congress
November 14, 2021 to November 18, 2021 - Athens, Greece

  • SENSORCOMM 2021, The Fifteenth International Conference on Sensor Technologies and Applications
  • SENSORDEVICES 2021, The Twelfth International Conference on Sensor Device Technologies and Applications
  • SECURWARE 2021, The Fifteenth International Conference on Emerging Security Information, Systems and Technologies
  • AFIN 2021, The Thirteenth International Conference on Advances in Future Internet
  • CENICS 2021, The Fourteenth International Conference on Advances in Circuits, Electronics and Micro-electronics
  • ICQNM 2021, The Fifteenth International Conference on Quantum, Nano/Bio, and Micro Technologies
  • FASSI 2021, The Seventh International Conference on Fundamentals and Advances in Software Systems Integration
  • GREEN 2021, The Sixth International Conference on Green Communications, Computing and Technologies

TrendNews 2021 Congress
November 14, 2021 to November 18, 2021 - Athens, Greece

  • CORETA 2021, Advances on Core Technologies and Applications
  • DIGITAL 2021, Advances on Societal Digital Transformation

 


ThinkMind // UBICOMM 2019, The Thirteenth International Conference on Mobile Ubiquitous Computing, Systems, Services and Technologies // View article ubicomm_2019_4_10_18005


Automating the Semantic Labeling of Stream Data

Authors:
Konstantinos Kotis

Keywords: semantic label; ontology; stream data

Abstract:
The collection of a voluminous real-world stream data is achieved today through a large number of distributed and heterogeneous data sources. On the other hand, it is quite rare to discover and collect semantic models associated with this data, in order to be able to represent implicit meaning and specifying related uncovered concepts and relationships between them. Such semantic models, however, are the key to make the data easily available, understandable and interlinkable for its potential users and applications. Manually modeling the semantics of data requires significant effort and expertise. Most of the related work focuses on the semantic labeling/annotation of the data fields (source attributes), given that a semantic model is already provided. Constructing a semantic model that explicitly describes the relationships between the data attributes in addition to their semantic types is critical. Related works support the semantic annotation of data using existing ontologies, but there are only a few that automatically construct the ontology based on the real-world stream data that will eventually annotate (two-step process). More important, existing solutions require a manually-created training data set and its mapping to existing related ontologies/models, in order to assist in the process of learning the mapping function between the actual stream data and the related semantic model (usually via a supervised machine learning approach). This paper a) presents the problem and representative related work, and b) proposes design directions that are aligned to key requirements.

Pages: 55 to 62

Copyright: Copyright (c) IARIA, 2019

Publication date: September 22, 2019

Published in: conference

ISSN: 2308-4278

ISBN: 978-1-61208-736-8

Location: Porto, Portugal

Dates: from September 22, 2019 to September 26, 2019

SERVICES CONTACT
2010 - 2017 © ThinkMind. All rights reserved.
Read Terms of Service and Privacy Policy.