Tunga Güngör

1.9k total citations
75 papers, 839 citations indexed

About

Tunga Güngör is a scholar working on Artificial Intelligence, Information Systems and Computer Vision and Pattern Recognition. According to data from OpenAlex, Tunga Güngör has authored 75 papers receiving a total of 839 indexed citations (citations by other indexed papers that have themselves been cited), including 68 papers in Artificial Intelligence, 14 papers in Information Systems and 11 papers in Computer Vision and Pattern Recognition. Recurrent topics in Tunga Güngör's work include Natural Language Processing Techniques (48 papers), Topic Modeling (45 papers) and Text and Document Classification Technologies (15 papers). Tunga Güngör is often cited by papers focused on Natural Language Processing Techniques (48 papers), Topic Modeling (45 papers) and Text and Document Classification Technologies (15 papers). Tunga Güngör collaborates with scholars based in Türkiye, United States and Canada. Tunga Güngör's co-authors include Haşim Sak, Murat Saraçlar, Şerafettin Taşcı, A. Sumru Özsoy, Bülent Sankur, Hidayet Takçı, Fikret Gürgen, Suzan Üsküdarlı, Can Alkan and Arzucan Özgür and has published in prestigious journals such as Bioinformatics, PLoS ONE and Expert Systems with Applications.

In The Last Decade

Tunga Güngör

67 papers receiving 744 citations

Peers

Tunga Güngör
Tunga Güngör
Citations per year, relative to Tunga Güngör Tunga Güngör (= 1×) peers Rodrigo Nogueira

Countries citing papers authored by Tunga Güngör

Since Specialization
Citations

This map shows the geographic impact of Tunga Güngör'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 Tunga Güngör with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tunga Güngör more than expected).

Fields of papers citing papers by Tunga Güngör

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Tunga Güngör. 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 Tunga Güngör. The network helps show where Tunga Güngör may publish in the future.

Co-authorship network of co-authors of Tunga Güngör

This figure shows the co-authorship network connecting the top 25 collaborators of Tunga Güngör. A scholar is included among the top collaborators of Tunga Güngör 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 Tunga Güngör. Tunga Güngör is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Khattab, Omar, et al.. (2024). Building efficient and effective OpenQA systems for low-resource languages. Knowledge-Based Systems. 302. 112243–112243. 3 indexed citations
2.
Güngör, Tunga, et al.. (2024). A comprehensive analysis of static word embeddings for Turkish. Expert Systems with Applications. 252. 124123–124123. 2 indexed citations
3.
Güngör, Tunga, et al.. (2024). Sentiment analysis using averaged weighted word vector features. PLoS ONE. 19(4). e0299264–e0299264. 3 indexed citations
4.
Güngör, Tunga, et al.. (2024). Çeviribilim Çalışmalarında Çevirmenin Üslubu ve Makinenin Üslubu. DergiPark (Istanbul University). 100–124. 2 indexed citations
5.
6.
Üsküdarlı, Suzan, et al.. (2023). TULAP - An Accessible and Sustainable Platform for Turkish Natural Language Processing Resources. 219–227. 1 indexed citations
7.
Güngör, Tunga, et al.. (2023). Analysis of Deep Learning Model Combinations and Tokenization Approaches in Sentiment Classification. IEEE Access. 11. 134951–134968. 4 indexed citations
8.
Güngör, Tunga, et al.. (2022). Turkish abstractive text summarization using pretrained sequence-to-sequence models. Natural Language Engineering. 29(5). 1275–1304. 11 indexed citations
10.
Güngör, Tunga, et al.. (2020). EXSEQREG: Explaining sequence-based NLP tasks with regions with a case study using morphological features for named entity recognition. PLoS ONE. 15(12). e0244179–e0244179. 4 indexed citations
11.
Güngör, Tunga, et al.. (2020). Intrinsic and Extrinsic Evaluation of Word Embedding Models. 1–6. 3 indexed citations
12.
Güngör, Tunga, et al.. (2018). Deep-BGT at PARSEME Shared Task 2018: Bidirectional LSTM-CRF Model for Verbal Multiword Expression Identification. International Conference on Computational Linguistics. 248–253. 5 indexed citations
13.
Güngör, Tunga, et al.. (2018). USING GENETIC ALGORITHMS WITH LEXICAL CHAINS FOR AUTOMATIC TEXT SUMMARIZATION. 595–600.
15.
Yüksel, Bayram, Tunga Güngör, Faraz Hach, et al.. (2015). Robustness of Massively Parallel Sequencing Platforms. PLoS ONE. 10(9). e0138259–e0138259. 2 indexed citations
16.
Gencer, Adem Efe, et al.. (2012). Input-evaluation: A new mechanism for collecting data using games with a purpose. 3. 239–244. 1 indexed citations
17.
Sak, Haşim, Murat Saraçlar, & Tunga Güngör. (2011). Discriminative reranking of ASR hypotheses with morpholexical and N-best-list features. 2. 202–207. 14 indexed citations
18.
Sak, Haşim, et al.. (2006). A Corpus-Based Concatenative Speech Synthesis System for Turkish. DergiPark (Istanbul University). 22 indexed citations
19.
Güngör, Tunga, et al.. (2006). A Composite Approach for Part of Speech Tagging in Turkish. 1 indexed citations
20.
Yolum, Pınar, Tunga Güngör, Fikret Gürgen, & Can Özturan. (2005). Computer and Information Sciences - ISCIS 2005: 20th International Symposium, Istanbul, Turkey, October 26 -- 28, 2005, Proceedings (Lecture Notes in Computer Science). Springer eBooks. 1 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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