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Semantics in the Deep: Semantic Analytics for Big Data

Dimitrios Koutsomitropoulos, Spiridon Likothanassis, Panos Kalnis
2019 Data  
One cannot help but classify the continuous birth and demise of Artificial Intelligence (AI) trends into the everlasting theme of the battle between connectionist and symbolic AI [...]  ...  Conflicts of Interest: The authors declare no conflicts of interest.  ...  This has been exactly the reasoning behind the Semantic Analytics for Big Data (SEDSEAL) international workshop [1].  ... 
doi:10.3390/data4020063 fatcat:ezudf4hfqjguldo3nst5oop5vi

Semantic Data Ingestion for Intelligent, Value-Driven Big Data Analytics

Jeremy Debattista, Judie Attard, Rob Brennan
2018 2018 4th International Conference on Big Data Innovations and Applications (Innovate-Data)  
In this position paper we describe a conceptual model for intelligent Big Data analytics based on both semantic and machine learning AI techniques (called AI ensembles).  ...  These processes are linked to business outcomes by explicitly modelling data value and using semantic technologies as the underlying mode for communication between the diverse processes and organisations  ...  ACKNOWLEDGEMENT We would like to thank Giovanni Schiuma, Markus Helfurt, Pieter De Leenheer, Eamonn Clinton, Diego Calvanese, Christian Dirschl, Ismael Caballero, Hans Viehmann, and Rico Richter for their  ... 
doi:10.1109/innovate-data.2018.00008 dblp:conf/obd/DebattistaAB18 fatcat:3hiyg2rd4fh2hdx37jelozkz5e

Statistical learning for semantic parsing: A survey

Qile Zhu, Xiyao Ma, Xiaolin Li
2019 Big Data Mining and Analytics  
With the rise of deep learning, we will pay more attention on the deep learning based semantic parsing, especially for the application of Knowledge Base Question Answering (KBQA).  ...  In this paper, we review recent algorithms for semantic parsing including both conventional machine learning approaches and deep learning approaches.  ...  R01GM110240), and Industry Members of NSF Center for Big Learning ( php/partners/).  ... 
doi:10.26599/bdma.2019.9020011 dblp:journals/bigdatama/ZhuML19 fatcat:evuhlbbl7jd67ajemd6xolxrje

Towards the 5th Industrial Revolution: A literature review and a framework for Process Optimization Based on Big Data Analytics and Semantics

Dimitris Mourtzis
2021 Journal of Machine Engineering  
Although there are several technologies and techniques under the term Data Analytics for gathering such data, their interpretation to information, and ultimately to knowledge remains in its infancy.  ...  This paper aims to investigate the opportunities and the gaps as well as the challenges arising in the current industrial landscape, towards the efficient utilization of Big Data, for process optimization  ...  SEMANTICS FOR BIG DATA INTEGRATION Fig. 10 . 10 Process for Big Data Analytics [51] Fig. 11 . 11 Semantic Memory for Big Data Analysis Architecture [45] Fig. 12 . 12 Predictive Analytics Workflow  ... 
doi:10.36897/jme/141834 fatcat:tsp4zeziebg5hcxwguwx6dgsgi

Giving meaning to unsupervised EO change detection rasters

Jordane Dorne, Nathalie Aussenac-Gilles, Catherine Comparot, Cassia Trojahn, Romain Hugues
2020 Proceedings of the 9th ACM SIGSPATIAL International Workshop on Analytics for Big Geospatial Data  
This paper presents a semantic-driven data integration approach that supports the generation of a knowledge graph from a raster change file and from various data sources of events that may explain the  ...  We show the added value of the proposed approach for i) explaining change detection and ii) validating the results from unsupervised deep learning algorithms.  ...  This work benefits from two financial supports: an H2020 grant for the CANDELA project under convention number 776193; and the CIFRE PhD. scholar agreement ANRT number 2017/1399 involving Thales Alenia  ... 
doi:10.1145/3423336.3429347 dblp:conf/gis/DorneACTH20 fatcat:fsiagajj3bbmjllkqusitlpidi

Learners Demographics Classification on MOOCs During the COVID-19: Author Profiling via Deep Learning Based on Semantic and Syntactic Representations

Tahani Aljohani, Alexandra I. Cristea
2021 Frontiers in Research Metrics and Analytics  
We have focused on examining models which show promise elsewhere, but were never examined in the LP area (deep learning models) based on effective textual representations.  ...  In this paper, we seek to improve Learner Profiling (LP), i.e. estimating the demographic characteristics of learners in MOOC platforms.  ...  ACKNOWLEDGMENTS We thank the journal reviewers for their valuable comments. We also gratefully acknowledge funding support from the Ministry of Education of Saudi Arabia.  ... 
doi:10.3389/frma.2021.673928 fatcat:dnjlr7yo5jaklcouhcvcl7mwpm

Cultural Heritage Storytelling, Engagement and Management in the Era of Big Data and the Semantic Web

Charalampos A. Dimoulas
2022 Sustainability  
that have been preserved throughout the years of humankind [...]  ...  Cultural heritage (CH) refers to a highly multidisciplinary research and application field, intending to collect, archive, and disseminate the traditions, monuments/artworks, and overall civilization legacies  ...  Storytelling, Engagement and Management in the Era of Big Data and the Semantic Web.  ... 
doi:10.3390/su14020812 fatcat:piqqze5pf5hszgym3gfa5y47ae

IMIA LaMB WG publications: 'Biomedical Semantics in the Big Data Era' - conference paper introducing the related workshop, MEDINFO, 2015

Ronald Cornet, Laszlo Balkanyi, Olivier Bodenreider
2019 Zenodo  
So the question is neither "What can semantics do for Big Data?", nor "What can Big Data do for semantics?". It is "How can Big Data and biomedical semantics best benefit from each other?".  ...  This workshop, organized by the IMIA WG LaMB (Language and Meaning in Biomedicine) sees in the advance of Big Data technologies a chance for leveraging large amounts of unstructured domain content to build  ...  interplay between (big) data, semantic resources and natural language processing  ... 
doi:10.5281/zenodo.3399568 fatcat:bgkapibaabejlosypvtzcg4jqq

Using Semantic Modelling to Improve the Processing Efficiency of Big Data in the Internet of Things Domain

A. Gladun, Y. Rogushina, A. Andrushevich
2019 Kibernetika i vyčislitelʹnaâ tehnika  
In this article we look at the features of Big Data generated by the Internet of Things (IoT) technology, and also present the methodology for processing this Big Data with use of semantic modeling (ontologies  ...  The conceptual architecture of the Big Data processing system for IoT and describe it on on the example of the NoSQL database for Smart Home were given.  ...  Therefore, we plan to use not only Big Data analytics, but also modem ML approaches, such as deep learning.  ... 
doi:10.15407/kvt196.02.027 fatcat:b3yzwnp2prbjlnqm4ll33kuxxq

Deep Learning meets Semantic Web: A feasibility study with the Cardiovascular Disease Ontology and PubMed citations

Mercedes Argüello Casteleiro, George Demetriou, Warren J. Read, Maria Jesus Fernandez Prieto, Diego Maseda-Fernandez, Goran Nenadic, Julie Klein, John A. Keane, Robert Stevens
2016 Workshop on Ontologies and Data in Life Sciences  
As of today, this is a challenging task related to information retrieval, and in the realm of Big Data Analytics.  ...  Overall, our study explores the feasibility of obtaining methods that scale when dealing with big data, and which enable automation of deep semantic analysis and markup of textual information from unannotated  ...  ACKNOWLEDGEMENTS To Prof Iain Buchan and Stephen Walker for useful discussions; and to Timothy Furmston for helping with the software and einfrastructure.  ... 
dblp:conf/odls/CasteleiroDRPMN16 fatcat:gxdpzlhwfjeu7kwzkk5y6v3bve

Deep Learning Security Systems

2019 International Journal of Engineering and Advanced Technology  
There is a hypothesis in this regard, the more data, the more abstract knowledge. So a handy survey of Big Data, Deep Learning and its application in Big Data is necessary.  ...  One technique that can be used for data analysis so that able to help us find abstract patterns in Big Data is Deep Learning.  ...  Semantic Indexing: Information retrieval is a key task that is associated with Big Data Analytics.  ... 
doi:10.35940/ijeat.f1347.0986s319 fatcat:65xw3xt6gvbllm5b56nxirqgzy

Competence in lexical semantics

Andras Kornai, Judit Àcs, Márton Makrai, Dávid Márk Nemeskey, Katalin Pajkossy, Gábor Recski
2015 Proceedings of the Fourth Joint Conference on Lexical and Computational Semantics  
We investigate from the competence standpoint two recent models of lexical semantics, algebraic conceptual representations and continuous vector models.  ...  Acs wrote the first version of the feedback vertex set finder which was adapted to our data bý Acs and Pajkossy, who also took part in the computational experiments, including preprocessing the data, adapting  ...  The system has been used as an experimental platform for a variety of purposes, including quantitative analysis of deep cases by Makrai, who developed the current version of the deep case system with Nemeskey  ... 
doi:10.18653/v1/s15-1019 dblp:conf/starsem/KornaiAMNPR15 fatcat:3resmgdzvfdztpmjw42su46x7q

Deep learning applications and challenges in big data analytics

Maryam M Najafabadi, Flavio Villanustre, Taghi M Khoshgoftaar, Naeem Seliya, Randall Wald, Edin Muharemagic
2015 Journal of Big Data  
In the present study, we explore how Deep Learning can be utilized for addressing some important problems in Big Data Analytics, including extracting complex patterns from massive volumes of data, semantic  ...  Big Data Analytics and Deep Learning are two high-focus of data science.  ...  Deep learning challenges in big data analytics The prior section focused on emphasizing the applicability and benefits of Deep Learning algorithms for Big Data Analytics.  ... 
doi:10.1186/s40537-014-0007-7 fatcat:65mi6dnv5rg6poesotupqbsm7y

The Maturing Semantic Web: Lessons in Web-Scale Knowledge Representation [chapter]

Mark Greaves
2009 Lecture Notes in Computer Science  
-Semantic web meetup groups in Silicon Valley, Boston, Seattle... Emphasis is mostly Semantic dimension of Semantic Web-That was where the money was -RDBMS scale and orientation, powerful analytics for  ...  with more than 10M inhabitants"  The real money in semantics will be made in apps/tools that exploit web-scale data -The cost of semantic data creation is going to zero -The size of semantic data is  ... 
doi:10.1007/978-3-642-03079-6_1 fatcat:bgkvdqaj3ndrtmz56qwqi4mbse

IMIA WG LaMB event: 'Biomedical Semantics in the Big Data Era', Workshop at MEDINFO 2015 – São Paulo,Brazil

Roland Cornet, Stephane Meystre, Stefan Schulz, Patrick Ruch, Tomasz Adamusiak, Laszlo Balkanyi, Jianying Hu
2019 Zenodo  
The workshop of IMIA WG 'Language and Meaning in Biomedicine' was held at MEDINFO 2015 – São Paulo,Brazil.  ...  information, by Stefan Schulz - Deep question-answering for biomedical decision support, by Patrick Ruch - Feature extraction for predictive modeling, by Jianying Hu - Connecting structured and unstructured  ...  Phenotyping Using the Unified Medical Language System • Quality assurance in LOINC using description logic • Question answering for biology and medicine • Subword-based semantic retrieval of clinical  ... 
doi:10.5281/zenodo.3381015 fatcat:lkccddww7raefbwppmtfzedcgq
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