Write in a clean editor, then format for Proceedings of the ACM on Management of Data in one click — DocuGuru applies the official ACM template with numbered references and exports a submission-ready PDF plus the editable LaTeX source. Free to start.
Proceedings of the ACM on Management of Data is a peer-reviewed journal published by ACM, covering Advanced Database Systems and Queries, Data Management and Algorithms, Graph Theory and Algorithms. Over its lifetime it has published 1,160 papers, which have received 6,405 citations.
| Publisher | ACM |
|---|---|
| Reference style | Numbered (ACM) Numbered — [1], [2] in the text [1] Ada Smith, Ben Jones, and Cara Lee. 2023. A representative article title. Proceedings of the ACM on Management of Data 12, 3, Article 45 (2023).
Formats any DOI in Proceedings of the ACM on Management of Data style. No sign-up. |
| Publishes research in | Advanced Database Systems and Queries Data Management and Algorithms Graph Theory and Algorithms Data Quality and Management Advanced Graph Neural Networks |
| ISSN | 2836-6573 |
| Citation impact (2-yr) | 2.89 |
| h-index | 32 |
| i10-index | 214 |
| Top institutions publishing here | Tsinghua University |
| You get | A submission-ready PDF and the editable LaTeX source — ready to submit. |
Citations each year’s papers have accumulated so far — the most recent years are still building up.
Language models have shown promising performance on the task of translating natural language questions into SQL queries (Text-to-SQL). However, most of the state-of-the-art (SOTA) approaches rely on powerful yet closed-source large language models (LLMs), such as ChatGPT and GPT-4, which may have the limitations of unclear model architectures, data privacy risks, and expensive inference overheads.…
Due to the sweeping digitalization of processes, increasingly vast amounts of time series data are being produced. Accurate classification of such time series facilitates decision making in multiple domains. State-of-the-art classification accuracy is often achieved by ensemble learning where results are synthesized from multiple base models. This characteristic implies that ensemble learning needs substantial computing…
Property graphs have reached a high level of maturity, witnessed by multiple robust graph database systems as well as the ongoing ISO standardization effort aiming at creating a new standard Graph Query Language (GQL). Yet, despite documented demand, schema support is limited both in existing systems and in the first version of the GQL Standard.…
Approximate nearest neighbor (ANN) search is a fundamental search in multi-dimensional databases, which has numerous real-world applications, such as image retrieval, recommendation, entity resolution, and sequence matching. Proximity graph (PG) has been the state-of-the-art index for ANN search. However, the search on existing PGs either suffers from a high time complexity or has no performance…
Searching for approximate nearest neighbors (ANN) in the high-dimensional Euclidean space is a pivotal problem. Recently, with the help of fast SIMD-based implementations, Product Quantization (PQ) and its variants can often efficiently and accurately estimate the distances between the vectors and have achieved great success in the in-memory ANN search. Despite their empirical success, we…
ACM Transactions on Storage
Digital Threats: Research and Practice
Journal of Data and Information Quality
Proceedings of the ACM on Human-Computer Interaction
Proceedings of the ACM on Programming Languages
ACM Conference Proceedings
IEEE Transactions on Computational Social Systems
IEEE Transactions on Computers
