A NoSQL approach for aspect mining of cultural heritage streaming data

Gerasimos Vonitsanos; Andreas Kanavos; Alaa Mohasseb; Dimitrios Tsolis

doi:10.1109/IISA.2019.8900770

A NoSQL approach for aspect mining of cultural heritage streaming data

Gerasimos Vonitsanos
, Andreas Kanavos
, Alaa Mohasseb
, Dimitrios Tsolis

University of Patras

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

269 Downloads (Pure)

Abstract

Aspect mining constitutes an essential part of delivering concise and, perhaps more importantly, accurately tailored cultural content. With the advent of social media, there is a data abundance so that analytics can be reliably designed for ultimately providing valuable information towards a given product or service. Naturally representing and efficiently processing a large number of opinions can be implemented with the use of streaming technologies. Big data analytics are especially important in the case of cultural content management where reviews and opinions may be analyzed in order to extract meaningful representations. In this paper, a NoSQL database method for aspect mining of a cultural heritage scenario by taking advantage of Apache Spark streaming architecture is presented.

Original language	English
Title of host publication	Proceedings of 2019 10th International Conference on Information, Intelligence, Systems and Applications (IISA)
Publisher	Institute of Electrical and Electronics Engineers Inc.
Number of pages	4
ISBN (Electronic)	978-1-7281-4959-2
ISBN (Print)	978-1-7281-4960-8
DOIs	https://doi.org/10.1109/IISA.2019.8900770
Publication status	Published - 14 Nov 2019
Event	International Conference on Information, Intelligence, Systems and Applications - Patras, Greece Duration: 15 Jul 2019 → 17 Jul 2019 Conference number: 10th https://ieeexplore.ieee.org/xpl/conhome/8893976/proceeding

Conference

Conference	International Conference on Information, Intelligence, Systems and Applications
Abbreviated title	IISA
Country/Territory	Greece
City	Patras
Period	15/07/19 → 17/07/19
Internet address	https://ieeexplore.ieee.org/xpl/conhome/8893976/proceeding

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 11 Sustainable Cities and Communities

Keywords

Apache Cassandra
Apache Spark Streaming
big data analytics
cultural heritage management
knowledge representation
topic modeling tweet
stream analysis

Access to Document

10.1109/IISA.2019.8900770

A NoSQL Approach for Aspect Mining of Cultural Heritage Streaming Data
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Accepted author manuscript (Post-print), 236 KB

Cite this

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title = "A NoSQL approach for aspect mining of cultural heritage streaming data",

abstract = "Aspect mining constitutes an essential part of delivering concise and, perhaps more importantly, accurately tailored cultural content. With the advent of social media, there is a data abundance so that analytics can be reliably designed for ultimately providing valuable information towards a given product or service. Naturally representing and efficiently processing a large number of opinions can be implemented with the use of streaming technologies. Big data analytics are especially important in the case of cultural content management where reviews and opinions may be analyzed in order to extract meaningful representations. In this paper, a NoSQL database method for aspect mining of a cultural heritage scenario by taking advantage of Apache Spark streaming architecture is presented.",

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publisher = "Institute of Electrical and Electronics Engineers Inc.",

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note = "International Conference on Information, Intelligence, Systems and Applications, IISA ; Conference date: 15-07-2019 Through 17-07-2019",

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Vonitsanos, G, Kanavos, A, Mohasseb, A & Tsolis, D 2019, A NoSQL approach for aspect mining of cultural heritage streaming data. in Proceedings of 2019 10th International Conference on Information, Intelligence, Systems and Applications (IISA). Institute of Electrical and Electronics Engineers Inc., International Conference on Information, Intelligence, Systems and Applications, Patras, Greece, 15/07/19. https://doi.org/10.1109/IISA.2019.8900770

A NoSQL approach for aspect mining of cultural heritage streaming data. / Vonitsanos, Gerasimos; Kanavos, Andreas; Mohasseb, Alaa et al.
Proceedings of 2019 10th International Conference on Information, Intelligence, Systems and Applications (IISA). Institute of Electrical and Electronics Engineers Inc., 2019.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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AU - Tsolis, Dimitrios

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N2 - Aspect mining constitutes an essential part of delivering concise and, perhaps more importantly, accurately tailored cultural content. With the advent of social media, there is a data abundance so that analytics can be reliably designed for ultimately providing valuable information towards a given product or service. Naturally representing and efficiently processing a large number of opinions can be implemented with the use of streaming technologies. Big data analytics are especially important in the case of cultural content management where reviews and opinions may be analyzed in order to extract meaningful representations. In this paper, a NoSQL database method for aspect mining of a cultural heritage scenario by taking advantage of Apache Spark streaming architecture is presented.

AB - Aspect mining constitutes an essential part of delivering concise and, perhaps more importantly, accurately tailored cultural content. With the advent of social media, there is a data abundance so that analytics can be reliably designed for ultimately providing valuable information towards a given product or service. Naturally representing and efficiently processing a large number of opinions can be implemented with the use of streaming technologies. Big data analytics are especially important in the case of cultural content management where reviews and opinions may be analyzed in order to extract meaningful representations. In this paper, a NoSQL database method for aspect mining of a cultural heritage scenario by taking advantage of Apache Spark streaming architecture is presented.

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KW - Apache Spark Streaming

KW - big data analytics

KW - cultural heritage management

KW - knowledge representation

KW - topic modeling tweet

KW - stream analysis

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M3 - Conference contribution

SN - 978-1-7281-4960-8

BT - Proceedings of 2019 10th International Conference on Information, Intelligence, Systems and Applications (IISA)

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - International Conference on Information, Intelligence, Systems and Applications

Y2 - 15 July 2019 through 17 July 2019

ER -

A NoSQL approach for aspect mining of cultural heritage streaming data

Abstract

Conference

UN SDGs

Keywords

Access to Document

Fingerprint

Cite this