Real time content-based news recommendation in Turkish with apache spark

Altan Çakır; Mert Candar; Didem Makaroğlu; Koray Kocabaş

doi:10.1007/978-3-030-23756-1_29

Real time content-based news recommendation in Turkish with apache spark

Altan Çakır, Mert Candar, Didem Makaroğlu^*, Koray Kocabaş

^*Corresponding author for this work

Department of Physics Engineering

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

1 Citation (Scopus)

Abstract

The readers’ behavior have partially turned into consuming news online, after news providers are transformed the printed newspapers into digital web sites. Engaging attention of the readers by retaining them on the web site contents as much as possible to consume more articles has become crucial and as a scarce resource, it is also challenging for the providers. While readers click through on the pages, system records each click for classical counting approach, also measure the time spent on pages which is critical for news providers in digital web sites. In this regard, recommendation engines which builds on the natural language processing with machine learning algorithms play important role to gain insights from the vectorized contents and provide similar articles to the readers. We motivate to analyze news content similarities expanding with tags and emotion similarities by comparing various text analytics methods results starting from sports and travel categories. By adding domain knowledge on the findings, our aim is to have a specific category based approach which could be applied on different news providers contents in Turkey.

Original language	English
Title of host publication	Intelligent and Fuzzy Techniques in Big Data Analytics and Decision Making - Proceedings of the INFUS 2019 Conference
Editors	Cengiz Kahraman, Sezi Cevik Onar, Basar Oztaysi, Irem Ucal Sari, Selcuk Cebi, A.Cagri Tolga
Publisher	Springer Verlag
Pages	229-237
Number of pages	9
ISBN (Print)	9783030237554
DOIs	https://doi.org/10.1007/978-3-030-23756-1_29
Publication status	Published - 2020
Event	International Conference on Intelligent and Fuzzy Systems, INFUS 2019 - Istanbul, Turkey Duration: 23 Jul 2019 → 25 Jul 2019

Publication series

Name	Advances in Intelligent Systems and Computing
Volume	1029
ISSN (Print)	2194-5357
ISSN (Electronic)	2194-5365

Conference

Conference	International Conference on Intelligent and Fuzzy Systems, INFUS 2019
Country/Territory	Turkey
City	Istanbul
Period	23/07/19 → 25/07/19

Bibliographical note

Publisher Copyright:
© 2020, Springer Nature Switzerland AG.

Keywords

Doc2Vec
LDA
Machine learning
News events

UN SDGs

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

Access to Document

10.1007/978-3-030-23756-1_29

Cite this

Çakır, A., Candar, M., Makaroğlu, D., & Kocabaş, K. (2020). Real time content-based news recommendation in Turkish with apache spark. In C. Kahraman, S. Cevik Onar, B. Oztaysi, I. U. Sari, S. Cebi, & A. C. Tolga (Eds.), Intelligent and Fuzzy Techniques in Big Data Analytics and Decision Making - Proceedings of the INFUS 2019 Conference (pp. 229-237). (Advances in Intelligent Systems and Computing; Vol. 1029). Springer Verlag. https://doi.org/10.1007/978-3-030-23756-1_29

Çakır, Altan ; Candar, Mert ; Makaroğlu, Didem et al. / Real time content-based news recommendation in Turkish with apache spark. Intelligent and Fuzzy Techniques in Big Data Analytics and Decision Making - Proceedings of the INFUS 2019 Conference. editor / Cengiz Kahraman ; Sezi Cevik Onar ; Basar Oztaysi ; Irem Ucal Sari ; Selcuk Cebi ; A.Cagri Tolga. Springer Verlag, 2020. pp. 229-237 (Advances in Intelligent Systems and Computing).

@inproceedings{fdbc2ff9b54c4c779d6a7b2486f476b7,

title = "Real time content-based news recommendation in Turkish with apache spark",

abstract = "The readers{\textquoteright} behavior have partially turned into consuming news online, after news providers are transformed the printed newspapers into digital web sites. Engaging attention of the readers by retaining them on the web site contents as much as possible to consume more articles has become crucial and as a scarce resource, it is also challenging for the providers. While readers click through on the pages, system records each click for classical counting approach, also measure the time spent on pages which is critical for news providers in digital web sites. In this regard, recommendation engines which builds on the natural language processing with machine learning algorithms play important role to gain insights from the vectorized contents and provide similar articles to the readers. We motivate to analyze news content similarities expanding with tags and emotion similarities by comparing various text analytics methods results starting from sports and travel categories. By adding domain knowledge on the findings, our aim is to have a specific category based approach which could be applied on different news providers contents in Turkey.",

keywords = "Doc2Vec, LDA, Machine learning, News events",

author = "Altan {\c C}akır and Mert Candar and Didem Makaroğlu and Koray Kocaba{\c s}",

note = "Publisher Copyright: {\textcopyright} 2020, Springer Nature Switzerland AG.; International Conference on Intelligent and Fuzzy Systems, INFUS 2019 ; Conference date: 23-07-2019 Through 25-07-2019",

year = "2020",

doi = "10.1007/978-3-030-23756-1_29",

language = "English",

isbn = "9783030237554",

series = "Advances in Intelligent Systems and Computing",

publisher = "Springer Verlag",

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editor = "Cengiz Kahraman and {Cevik Onar}, Sezi and Basar Oztaysi and Sari, {Irem Ucal} and Selcuk Cebi and A.Cagri Tolga",

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address = "Germany",

}

Çakır, A, Candar, M, Makaroğlu, D & Kocabaş, K 2020, Real time content-based news recommendation in Turkish with apache spark. in C Kahraman, S Cevik Onar, B Oztaysi, IU Sari, S Cebi & AC Tolga (eds), Intelligent and Fuzzy Techniques in Big Data Analytics and Decision Making - Proceedings of the INFUS 2019 Conference. Advances in Intelligent Systems and Computing, vol. 1029, Springer Verlag, pp. 229-237, International Conference on Intelligent and Fuzzy Systems, INFUS 2019, Istanbul, Turkey, 23/07/19. https://doi.org/10.1007/978-3-030-23756-1_29

Real time content-based news recommendation in Turkish with apache spark. / Çakır, Altan; Candar, Mert; Makaroğlu, Didem et al.
Intelligent and Fuzzy Techniques in Big Data Analytics and Decision Making - Proceedings of the INFUS 2019 Conference. ed. / Cengiz Kahraman; Sezi Cevik Onar; Basar Oztaysi; Irem Ucal Sari; Selcuk Cebi; A.Cagri Tolga. Springer Verlag, 2020. p. 229-237 (Advances in Intelligent Systems and Computing; Vol. 1029).

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

TY - GEN

T1 - Real time content-based news recommendation in Turkish with apache spark

AU - Çakır, Altan

AU - Candar, Mert

AU - Makaroğlu, Didem

AU - Kocabaş, Koray

PY - 2020

Y1 - 2020

N2 - The readers’ behavior have partially turned into consuming news online, after news providers are transformed the printed newspapers into digital web sites. Engaging attention of the readers by retaining them on the web site contents as much as possible to consume more articles has become crucial and as a scarce resource, it is also challenging for the providers. While readers click through on the pages, system records each click for classical counting approach, also measure the time spent on pages which is critical for news providers in digital web sites. In this regard, recommendation engines which builds on the natural language processing with machine learning algorithms play important role to gain insights from the vectorized contents and provide similar articles to the readers. We motivate to analyze news content similarities expanding with tags and emotion similarities by comparing various text analytics methods results starting from sports and travel categories. By adding domain knowledge on the findings, our aim is to have a specific category based approach which could be applied on different news providers contents in Turkey.

AB - The readers’ behavior have partially turned into consuming news online, after news providers are transformed the printed newspapers into digital web sites. Engaging attention of the readers by retaining them on the web site contents as much as possible to consume more articles has become crucial and as a scarce resource, it is also challenging for the providers. While readers click through on the pages, system records each click for classical counting approach, also measure the time spent on pages which is critical for news providers in digital web sites. In this regard, recommendation engines which builds on the natural language processing with machine learning algorithms play important role to gain insights from the vectorized contents and provide similar articles to the readers. We motivate to analyze news content similarities expanding with tags and emotion similarities by comparing various text analytics methods results starting from sports and travel categories. By adding domain knowledge on the findings, our aim is to have a specific category based approach which could be applied on different news providers contents in Turkey.

KW - Doc2Vec

KW - LDA

KW - Machine learning

KW - News events

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U2 - 10.1007/978-3-030-23756-1_29

DO - 10.1007/978-3-030-23756-1_29

M3 - Conference contribution

AN - SCOPUS:85069496370

SN - 9783030237554

T3 - Advances in Intelligent Systems and Computing

SP - 229

EP - 237

BT - Intelligent and Fuzzy Techniques in Big Data Analytics and Decision Making - Proceedings of the INFUS 2019 Conference

A2 - Kahraman, Cengiz

A2 - Cevik Onar, Sezi

A2 - Oztaysi, Basar

A2 - Sari, Irem Ucal

A2 - Cebi, Selcuk

A2 - Tolga, A.Cagri

PB - Springer Verlag

T2 - International Conference on Intelligent and Fuzzy Systems, INFUS 2019

Y2 - 23 July 2019 through 25 July 2019

ER -

Çakır A, Candar M, Makaroğlu D, Kocabaş K. Real time content-based news recommendation in Turkish with apache spark. In Kahraman C, Cevik Onar S, Oztaysi B, Sari IU, Cebi S, Tolga AC, editors, Intelligent and Fuzzy Techniques in Big Data Analytics and Decision Making - Proceedings of the INFUS 2019 Conference. Springer Verlag. 2020. p. 229-237. (Advances in Intelligent Systems and Computing). doi: 10.1007/978-3-030-23756-1_29

Real time content-based news recommendation in Turkish with apache spark

Abstract

Publication series

Conference

Bibliographical note

Keywords

UN SDGs

Access to Document

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