--- title: "Information Systems — papers" description: "Information Systems: 402 papers of the Elamur Research library · page 1 of 5 · 1–25, the most cited first — our summary of each, its ideas, references…" canonical: "https://research.elamur.ai/free/en/shelves/computer-science/information-systems/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/shelves/computer-science/information-systems/) [home](https://md.research.elamur.ai/free/en/) / [shelves](https://md.research.elamur.ai/free/en/shelves/) / [Computer Science](https://md.research.elamur.ai/free/en/shelves/computer-science/) / Information Systems # 🗄️ Information Systems 402 papers · page 1 of 5 · 1–25 · the most cited first · [all shelves](https://md.research.elamur.ai/free/en/shelves/) Information Systems is a subfield of Computer Science in the OpenAlex classification of science. The topics most of its papers here are on: «Information Retrieval and Search Behavior», «Software Engineering Research», «Recommender Systems and Techniques». ## Papers **1** [2](https://md.research.elamur.ai/free/en/shelves/computer-science/information-systems/page/2/) … [5](https://md.research.elamur.ai/free/en/shelves/computer-science/information-systems/page/5/) [next →](https://md.research.elamur.ai/free/en/shelves/computer-science/information-systems/page/2/) 1. [**C4.5: Programs for Machine Learning**J. Ross Quinlan*1993 · 23,781 citations*](https://md.research.elamur.ai/free/en/papers/quinlan-1993-c45-programs-machine-learning/) 2. [**The Anatomy of a Large-Scale Hypertextual Web Search Engine**Sergey Brin, Lawrence Page*1998 · 16,227 citations*](https://md.research.elamur.ai/free/en/papers/brin-1998-anatomy-large-scale-hypertextual-web/) 3. [**The PageRank Citation Ranking: Bringing Order to the Web**Lawrence Page, Sergey Brin, Rajeev Motwani, et al.*1999 · 12,691 citations*](https://md.research.elamur.ai/free/en/papers/page-1999-pagerank-citation-ranking-bringing/) 4. [**A Comprehensive Survey on Graph Neural Networks**Zonghan Wu, Shirui Pan, Fengwen Chen, et al.*2019 · 10,295 citations*](https://md.research.elamur.ai/free/en/papers/wu-2019-comprehensive-survey-graph-neural-networks/) 5. [**SQuAD: 100,000+ Questions for Machine Comprehension of Text**Pranav Rajpurkar, Jian Zhang, Konstantin Lopyrev, et al.*2016 · 9,488 citations*](https://md.research.elamur.ai/free/en/papers/rajpurkar-2016-squad-100-000-questions-machine/) 6. [**TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems**Martín Abadi, Ashish Agarwal, Paul Barham, et al.*2016 · 9,453 citations*](https://md.research.elamur.ai/free/en/papers/abadi-2016-tensorflow-large-scale-machine-learning/) 7. [**Authoritative Sources in a Hyperlinked Environment**Jon M. Kleinberg*1999 · 9,089 citations*](https://md.research.elamur.ai/free/en/papers/kleinberg-1999-authoritative-sources-hyperlinked-environment/) 8. [**ChatGPT for Good? On Opportunities and Challenges of Large Language Models for Education**Enkelejda Kasneci, Kathrin Seßler, Stefan Küchemann, et al.*2023 · 7,429 citations*](https://md.research.elamur.ai/free/en/papers/kasneci-2023-chatgpt-good-opportunities-challenges-large/) 9. [**Dense Passage Retrieval for Open-Domain Question Answering**Vladimir Karpukhin, Barlas Oguz, Sewon Min, et al.*2020 · 5,370 citations*](https://md.research.elamur.ai/free/en/papers/karpukhin-2020-dense-passage-retrieval-open-domain/) 10. [**Instance-Based Learning Algorithms**David W. Aha, Dennis Kibler, Marc K. Albert*1991 · 5,248 citations*](https://md.research.elamur.ai/free/en/papers/aha-1991-instance-based-learning-algorithms/) 11. [**Inductive Representation Learning on Large Graphs**William L. Hamilton, Rex Ying, Jure Leskovec*2017 · 4,687 citations*](https://md.research.elamur.ai/free/en/papers/hamilton-2017-inductive-representation-learning-large-graphs/) 12. [**Performance of ChatGPT on USMLE: Potential for AI-assisted medical education using large language models**Tiffany H. Kung, Morgan Cheatham, Arielle Medenilla, et al.*2023 · 4,154 citations*](https://md.research.elamur.ai/free/en/papers/kung-2023-performance-chatgpt-usmle-potential-ai/) 13. [**Natural Questions: A Benchmark for Question Answering Research**Tom Kwiatkowski, Jennimaria Palomaki, Olivia Redfield, et al.*2019 · 4,031 citations*](https://md.research.elamur.ai/free/en/papers/kwiatkowski-2019-natural-questions-benchmark-question-answering/) 14. [**Teaching Machines to Read and Comprehend**Karl Moritz Hermann, Tomáš Kočiský, Edward Grefenstette, et al.*2015 · 3,806 citations*](https://md.research.elamur.ai/free/en/papers/hermann-2015-teaching-machines-read-comprehend/) 15. [**A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions**Lei Huang, Weijiang Yu, Weitao Ma, et al.*2023 · 3,221 citations*](https://md.research.elamur.ai/free/en/papers/huang-2023-survey-hallucination-large-language-models/) 16. [**TriviaQA: A Large Scale Distantly Supervised Challenge Dataset for Reading Comprehension**Mandar Joshi, Eunsol Choi, Daniel Weld, et al.*2017 · 3,204 citations*](https://md.research.elamur.ai/free/en/papers/joshi-2017-triviaqa-large-scale-distantly-supervised/) 17. [**CodeBERT: A Pre-Trained Model for Programming and Natural Languages**Zhangyin Feng, Daya Guo, Duyu Tang, et al.*2020 · 2,954 citations*](https://md.research.elamur.ai/free/en/papers/feng-2020-codebert-pre-trained-model-programming/) 18. [**Learning to Rank using Gradient Descent**Chris Burges, Tal Shaked, Erin Renshaw, et al.*2005 · 2,896 citations*](https://md.research.elamur.ai/free/en/papers/burges-2005-learning-rank-using-gradient/) 19. [**Reading Wikipedia to Answer Open-Domain Questions**Danqi Chen, Adam Fisch, Jason Weston, et al.*2017 · 2,250 citations*](https://md.research.elamur.ai/free/en/papers/chen-2017-reading-wikipedia-answer-open-domain/) 20. [**Knowledge Graph Embedding via Dynamic Mapping Matrix**Guoliang Ji, Shizhu He, Liheng Xu, et al.*2015 · 1,936 citations*](https://md.research.elamur.ai/free/en/papers/ji-2015-knowledge-graph-embedding-dynamic-mapping/) 21. [**A Language Modeling Approach to Information Retrieval**Jay M. Ponte, W. Bruce Croft*1998 · 1,867 citations*](https://md.research.elamur.ai/free/en/papers/ponte-1998-language-modeling-approach-information/) 22. [**“Liar, Liar Pants on Fire”: A New Benchmark Dataset for Fake News Detection**William Yang Wang*2017 · 1,801 citations*](https://md.research.elamur.ai/free/en/papers/wang-2017-liar-liar-pants-fire-new/) 23. [**ColBERT: Efficient and Effective Passage Search via Contextualized Late Interaction over BERT**Omar Khattab, Matei Zaharia*2020 · 1,776 citations*](https://md.research.elamur.ai/free/en/papers/khattab-2020-colbert-efficient-effective-passage/) 24. [**Leveraging Passage Retrieval with Generative Models for Open Domain Question Answering**Gautier Izacard, Edouard Grave*2021 · 1,674 citations*](https://md.research.elamur.ai/free/en/papers/izacard-2021-leveraging-passage-retrieval-generative-models/) 25. [**Retrieval-Augmented Generation for Large Language Models: A Survey**Yunfan Gao, Yun Xiong, Xinyu Gao, et al.*2023 · 1,647 citations*](https://md.research.elamur.ai/free/en/papers/gao-2023-retrieval-augmented-generation-large-language/) **1** [2](https://md.research.elamur.ai/free/en/shelves/computer-science/information-systems/page/2/) … [5](https://md.research.elamur.ai/free/en/shelves/computer-science/information-systems/page/5/) [next →](https://md.research.elamur.ai/free/en/shelves/computer-science/information-systems/page/2/) Updated 23 October 2026 - [← previous subfield Human-Computer Interaction](https://md.research.elamur.ai/free/en/shelves/computer-science/human-computer-interaction/) - [next subfield → Signal Processing](https://md.research.elamur.ai/free/en/shelves/computer-science/signal-processing/) - [↑ back to Computer Science](https://md.research.elamur.ai/free/en/shelves/computer-science/)