Pınar Tüfekçi

582 total citations
12 papers, 366 citations indexed

About

Pınar Tüfekçi is a scholar working on Artificial Intelligence, Information Systems and Computer Networks and Communications. According to data from OpenAlex, Pınar Tüfekçi has authored 12 papers receiving a total of 366 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Artificial Intelligence, 4 papers in Information Systems and 1 paper in Computer Networks and Communications. Recurrent topics in Pınar Tüfekçi's work include Text and Document Classification Technologies (4 papers), Authorship Attribution and Profiling (3 papers) and Topic Modeling (3 papers). Pınar Tüfekçi is often cited by papers focused on Text and Document Classification Technologies (4 papers), Authorship Attribution and Profiling (3 papers) and Topic Modeling (3 papers). Pınar Tüfekçi collaborates with scholars based in Türkiye. Pınar Tüfekçi's co-authors include Heysem Kaya, Erdem Uçar, Yılmaz Kılıçaslan, Ahmet Cihan and Kamil Kahveci and has published in prestigious journals such as SHILAP Revista de lepidopterología, International Journal of Electrical Power & Energy Systems and Multimedia Tools and Applications.

In The Last Decade

Pınar Tüfekçi

10 papers receiving 360 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Pınar Tüfekçi Türkiye	6	185	82	70	43	40	12	366
Chiara Masiero Italy	12	144 0.8×	52 0.6×	88 1.3×	10 0.2×	50 1.3×	23	383
Seok-Beom Roh South Korea	14	256 1.4×	47 0.6×	64 0.9×	38 0.9×	77 1.9×	44	534
Runmei Li China	10	103 0.6×	38 0.5×	132 1.9×	27 0.6×	39 1.0×	38	373
Fucai Qian China	11	139 0.8×	54 0.7×	270 3.9×	16 0.4×	28 0.7×	90	483
Biao Xu China	10	181 1.0×	127 1.5×	86 1.2×	10 0.2×	18 0.5×	33	468
Bruno Almeida Pimentel Brazil	10	281 1.5×	18 0.2×	47 0.7×	19 0.4×	97 2.4×	28	475
Huaguang Zhang China	4	75 0.4×	122 1.5×	83 1.2×	9 0.2×	28 0.7×	6	382
Tuve Löfström Sweden	12	284 1.5×	20 0.2×	49 0.7×	42 1.0×	48 1.2×	56	467
Muhammad Ahmad Pakistan	9	97 0.5×	37 0.5×	27 0.4×	16 0.4×	12 0.3×	26	350
J.J. Choi United States	10	254 1.4×	51 0.6×	95 1.4×	9 0.2×	39 1.0×	21	434

Countries citing papers authored by Pınar Tüfekçi

Since Specialization

Citations

This map shows the geographic impact of Pınar Tüfekçi's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Pınar Tüfekçi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pınar Tüfekçi more than expected).

Fields of papers citing papers by Pınar Tüfekçi

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Pınar Tüfekçi. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Pınar Tüfekçi. The network helps show where Pınar Tüfekçi may publish in the future.

Co-authorship network of co-authors of Pınar Tüfekçi

This figure shows the co-authorship network connecting the top 25 collaborators of Pınar Tüfekçi. A scholar is included among the top collaborators of Pınar Tüfekçi based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Pınar Tüfekçi. Pınar Tüfekçi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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12 of 12 papers shown

Tüfekçi, Pınar, et al.. (2024). Kötü Amaçlı Yazılım Tespiti için Makine Öğrenmesi Algoritmalarının Kullanımı. SHILAP Revista de lepidopterología. 12(1). 307–319.

Tüfekçi, Pınar, et al.. (2023). Biological gender identification in Turkish news text using deep learning models. Multimedia Tools and Applications. 83(17). 50669–50689. 1 indexed citations

Tüfekçi, Pınar, et al.. (2023). Derin Öğrenme ile Göğüs Röntgeni Görüntülerinden COVID-19 ve Viral Pnömoni Tespiti. Afyon Kocatepe University Journal of Sciences and Engineering. 23(1). 89–100.

Tüfekçi, Pınar, et al.. (2022). Author and genre identification of Turkish news texts using deep learning algorithms. Sadhana. 47(4). 4 indexed citations

Kaya, Heysem, et al.. (2019). Predicting CO and NOxemissions from gas turbines: novel data and abenchmark PEMS. TURKISH JOURNAL OF ELECTRICAL ENGINEERING & COMPUTER SCIENCES. 27(6). 4783–4796. 60 indexed citations

Tüfekçi, Pınar. (2016). Classification-based prediction models for stock price index movement. Intelligent Data Analysis. 20(2). 357–376. 3 indexed citations

Uçar, Erdem, et al.. (2016). A novel algorithm for extracting the user reviews from web pages. Journal of Information Science. 43(5). 696–712. 7 indexed citations

Tüfekçi, Pınar, et al.. (2014). A model for predicting drying time period of wool yarn bobbins using computational intelligence techniques. Textile Research Journal. 85(13). 1367–1380. 5 indexed citations

Tüfekçi, Pınar. (2014). Prediction of full load electrical power output of a base load operated combined cycle power plant using machine learning methods. International Journal of Electrical Power & Energy Systems. 60. 126–140. 270 indexed citations

10.

Tüfekçi, Pınar, et al.. (2013). Author detection by using different term weighting schemes. 2. 1–4. 5 indexed citations

11.

Tüfekçi, Pınar, et al.. (2012). Text classification of web based news articles by using Turkish grammatical features. 1–4. 8 indexed citations

12.

Tüfekçi, Pınar & Yılmaz Kılıçaslan. (2007). A Computational Model For Resolving Pronominal Anaphora In Turkish Using Hobbs- Naïve Algorithm. Zenodo (CERN European Organization for Nuclear Research). 13–17. 3 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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