Dalveren, Gonca Gökçe Menekşe

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Profile URL
https://hdl.handle.net/20.500.14411/7994
Name Variants
Gonca Gökçe Menekşe, Dalveren
Dalveren, Gonca Gokce Menekse
G., Dalveren
G.,Dalveren
D.,Gonca Gökçe Menekşe
Gonca Gokce Menekse, Dalveren
Dalveren, Gonca Gökçe Menekşe
G.G.M.Dalveren
D.,Gonca Gokce Menekse
D., Gonca Gokce Menekse
Dalveren,G.G.M.
Job Title
Doktor Öğretim Üyesi
Email Address
gonca.menekse@atilim.edu.tr
Main Affiliation
Information Systems Engineering
Status
Former Staff
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This researcher does not have a Scopus ID.
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Scholarly Output

28

Articles

18

Views / Downloads

127/918

Supervised MSc Theses

3

Supervised PhD Theses

1

WoS Citation Count

196

Scopus Citation Count

273

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9

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10

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WoS Citations per Publication

7.00

Scopus Citations per Publication

9.75

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14

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4

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IEEE Access5
Sustainability2
2018 International Symposium on Networks, Computers and Communications, ISNCC 2018 -- 2018 International Symposium on Networks, Computers and Communications, ISNCC 2018 -- 19 June 2018 through 21 June 2018 -- Rome -- 1424272
Journal of Eye Movement Research2
Avrupa Bilim ve Teknoloji Dergisi1
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Author: Ayaz, AhmetSubject: topic modeling

Scholarly Output Search Results

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    Article
    Citation - WoS: 9
    Citation - Scopus: 20
    Business Intelligence Strategies, Best Practices, and Latest Trends: Analysis of Scientometric Data From 2003 To 2023 Using Machine Learning
    (Mdpi, 2023) Gurcan, Fatih; Ayaz, Ahmet; Dalveren, Gonca Gokce Menekse; Derawi, Mohammad
    The widespread use of business intelligence products, services, and applications piques the interest of researchers in this field. The interest of researchers in business intelligence increases the number of studies significantly. Identifying domain-specific research patterns and trends is thus a significant research problem. This study employs a topic modeling approach to analyze domain-specific articles in order to identify research patterns and trends in the business intelligence field over the last 20 years. As a result, 36 topics were discovered that reflect the field's research landscape and trends. Topics such as "Organizational Capability", "AI Applications", "Data Mining", "Big Data Analytics", and "Visualization" have recently gained popularity. A systematic taxonomic map was also created, revealing the research background and BI perspectives based on the topics. This study may be useful to researchers and practitioners interested in learning about the most recent developments in the field. Topics generated by topic modeling can also be used to identify gaps in current research or potential future research directions.