Shuigeng Zhou
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- research-article
DP-SSL: towards robust semi-supervised learning with a few labeled samples
Yi Xu
Shanghai Key Lab of Intelligent Information Processing, and School of Computer Science, Fudan University, China
,Jiandong Ding
Alibaba Group
,Lu Zhang
Shanghai Key Lab of Intelligent Information Processing, and School of Computer Science, Fudan University, China
,Shuigeng Zhou
Shanghai Key Lab of Intelligent Information Processing, and School of Computer Science, Fudan University, China
NIPS '21: Proceedings of the 35th International Conference on Neural Information Processing Systems•December 2021, Article No.: 1216, pp 15895-15907The scarcity of labeled data is a critical obstacle to deep learning. Semi-supervised learning (SSL) provides a promising way to leverage unlabeled data by pseudo labels. However, when the size of labeled data is very small (say a few labeled samples per ...
- 0Citation
MetricsTotal Citations0- 1
Supplementary Material3540261.3541477_supp.pdf
- research-articlefree
Published By ACM
Published By ACM
Variate Associated Domain Adaptation for Unsupervised Multivariate Time Series Anomaly Detection
Yifan He
Shanghai Key Lab of Intelligent Information Processing, and School of Computer Science, Fudan University, China
,Yatao Bian
Tencent AI Lab, China
,Xi Ding
Shanghai Key Lab of Intelligent Information Processing, and School of Computer Science, Fudan University, China
,Bingzhe Wu
Tencent AI Lab, China
,Jihong Guan
Department of Computer Science and Technology, Tongji University, China
,Ji Zhang
The University of Southern Queensland, Australia
,Shuigeng Zhou
Shanghai Key Lab of Intelligent Information Processing, and School of Computer Science, Fudan University, China
ACM Transactions on Knowledge Discovery from Data, Volume 0, Issue ja • https://doi.org/10.1145/3663573Multivariate Time Series Anomaly Detection (MTS-AD) is crucial for the effective management and maintenance of devices in complex systems such as server clusters, spacecrafts and financial systems etc. However, upgrade or cross-platform deployment of ...
- 0Citation
- 200
- Downloads
MetricsTotal Citations0Total Downloads200Last 12 Months200Last 6 weeks61
- Article
Identifying Backdoor Attacks in Federated Learning via Anomaly Detection
Yuxi Mi
https://ror.org/013q1eq08Fudan University, 200438, Shanghai, China
,Yiheng Sun
https://ror.org/00hhjss72Tencent, 518000, Shenzhen, China
,Jihong Guan
https://ror.org/03rc6as71Tongji University, 201804, Shanghai, China
,Shuigeng Zhou
https://ror.org/013q1eq08Fudan University, 200438, Shanghai, China
AbstractFederated learning has seen increased adoption in recent years in response to the growing regulatory demand for data privacy. However, the opaque local training process of federated learning also sparks rising concerns about model faithfulness. ...
- 0Citation
MetricsTotal Citations0
- research-article
Towards video text visual question answering: benchmark and baseline
Minyi Zhao
Shanghai Key Lab of Intelligent Information Processing, and School of Computer Science, Fudan University, Shanghai, China
,Bingjia Li
Shanghai Key Lab of Intelligent Information Processing, and School of Computer Science, Fudan University, Shanghai, China
,Jie Wang
ByteDance, China
,Wanqing Li
ByteDance, China
,Wenjing Zhou
ByteDance, China
,Lan Zhang
ByteDance, China
,Shijie Xuyang
Shanghai Key Lab of Intelligent Information Processing, and School of Computer Science, Fudan University, Shanghai, China
,Zhihang Yu
Shanghai Key Lab of Intelligent Information Processing, and School of Computer Science, Fudan University, Shanghai, China
,Xinkun Yu
Shanghai Key Lab of Intelligent Information Processing, and School of Computer Science, Fudan University, Shanghai, China
,Guangze Li
Shanghai Key Lab of Intelligent Information Processing, and School of Computer Science, Fudan University, Shanghai, China
,Aobotao Dai
Shanghai Key Lab of Intelligent Information Processing, and School of Computer Science, Fudan University, Shanghai, China
,Shuigeng Zhou
Shanghai Key Lab of Intelligent Information Processing, and School of Computer Science, Fudan University, Shanghai, China
NIPS '22: Proceedings of the 36th International Conference on Neural Information Processing Systems•November 2022, Article No.: 2576, pp 35549-35562There are already some text-based visual question answering (TextVQA) benchmarks for developing machine's ability to answer questions based on texts in images in recent years. However, models developed on these benchmarks cannot work effectively in many ...
- 0Citation
MetricsTotal Citations0- 1
Supplementary Material3600270.3602846_supp.pdf
- research-article
Published By ACM
Published By ACM
Zero-Shot Object Detection by Semantics-Aware DETR with Adaptive Contrastive Loss
Huan Liu
Fudan University, Shanghai, China
,Lu Zhang
Fudan University, Shanghai, China
,Jihong Guan
Tongji University, Shanghai, China
,Shuigeng Zhou
Fudan University, Shanghai, China
MM '23: Proceedings of the 31st ACM International Conference on Multimedia•October 2023, pp 4421-4430• https://doi.org/10.1145/3581783.3612523Zero-shot object detection (ZSD) aims to localize and recognize unseen objects in unconstrained images by leveraging semantic descriptions. Existing ZSD methods typically suffer from two drawbacks: 1) Due to the lack of data on unseen categories during ...
- 1Citation
- 226
- Downloads
MetricsTotal Citations1Total Downloads226Last 12 Months226Last 6 weeks11
- research-article
Published By ACM
Published By ACM
STIRER: A Unified Model for Low-Resolution Scene Text Image Recovery and Recognition
Minyi Zhao
Fudan University, Shanghai, China
,Shijie Xuyang
Fudan University, Shanghai, China
,Jihong Guan
Tongji University, Shanghai, China
,Shuigeng Zhou
Fudan University, Shanghai, China
MM '23: Proceedings of the 31st ACM International Conference on Multimedia•October 2023, pp 7530-7539• https://doi.org/10.1145/3581783.3612488Though scene text recognition (STR) from high-resolution (HR) images has achieved significant success in the past years, text recognition from low-resolution (LR) images is still a challenging task. This inspires the study on scene text image super-...
- 1Citation
- 263
- Downloads
MetricsTotal Citations1Total Downloads263Last 12 Months263Last 6 weeks9- 1
Supplementary MaterialACMMM_2023.mp4
- research-article
Published By ACM
Published By ACM
IDDR-NGP:Incorporating Detectors for Distractors Removal with Instant Neural Radiance Field
Xianliang Huang
Fudan University, Shanghai, China
,Jiajie Gou
Fudan University, Shanghai, China
,Shuhang Chen
Fudan University, Shanghai, China
,Zhizhou Zhong
Fudan University, Shanghai, China
,Jihong Guan
Tongji University, Shanghai, China
,Shuigeng Zhou
Fudan University, Shanghai, China
MM '23: Proceedings of the 31st ACM International Conference on Multimedia•October 2023, pp 1343-1351• https://doi.org/10.1145/3581783.3612045This paper presents the first unified distractor removal method, named IDDR-NGP, which directly operates on Instant-NPG. The method is able to remove a wide range of distractors in 3D scenes, such as snowflakes, confetti, defoliation and petals, whereas ...
- 0Citation
- 156
- Downloads
MetricsTotal Citations0Total Downloads156Last 12 Months156Last 6 weeks9
- research-article
Published By ACM
Published By ACM
Incremental Graph Classification by Class Prototype Construction and Augmentation
Yixin Ren
Fudan University, Shanghai, China
,Li Ke
Alibaba Group, Hangzhou, China
,Dong Li
Alibaba Group, Hangzhou, China
,Hui Xue
Alibaba, Hangzhou, China
,Zhao Li
Hangzhou Yugu Technology, Hangzhou, China
,Shuigeng Zhou
Fudan University, Shanghai, China
CIKM '23: Proceedings of the 32nd ACM International Conference on Information and Knowledge Management•October 2023, pp 2136-2145• https://doi.org/10.1145/3583780.3614932Graph neural networks (GNNs) are prone to catastrophic forgetting of past experience in continuous learning scenarios. In this work, we propose a novel method for class-incremental graph learning (CGL) by class prototype construction and augmentation, ...
- 0Citation
- 205
- Downloads
MetricsTotal Citations0Total Downloads205Last 12 Months205Last 6 weeks10
- research-article
Incremental Maximal Clique Enumeration for Hybrid Edge Changes in Large Dynamic Graphs
Ting Yu
Zhejiang Lab, Hangzhou, Zhejiang, China
,Ting Jiang
Zhejiang Lab, Hangzhou, Zhejiang, China
,Mohamed Jaward Bah
Zhejiang Lab, Hangzhou, Zhejiang, China
,Chen Zhao
School of Computer Science, Wuhan University, Wuhan, Hubei, China
,Hao Huang
School of Computer Science, Wuhan University, Wuhan, Hubei, China
,Mengchi Liu
School of Computer Science, South China Normal University, Guangzhou, Guangzhou, China
,Shuigeng Zhou
School of Computer Science, Shanghai Key Lab of Intelligent Information Processing, Fudan University, Shanghai, China
,Zhao Li
Hangzhou Yugu Technology Co., Ltd., Hangzhou, Zhejiang, China
,Ji Zhang
University of Southern Queensland, Toowoomba, QLD, Australia
IEEE Transactions on Knowledge and Data Engineering, Volume 36, Issue 4•April 2024, pp 1650-1666 • https://doi.org/10.1109/TKDE.2023.3311398Incremental maximal clique enumeration (IMCE), which maintains maximal cliques in dynamic graphs, is a fundamental problem in graph analysis. A maximal clique has a solid descriptive power of dense structures in graphs. Real-world graph data is often ...
- 0Citation
MetricsTotal Citations0
- research-article
Published By ACM
Published By ACM
HiGRN: A Hierarchical Graph Recurrent Network for Global Sea Surface Temperature Prediction
Hanchen Yang
Tongji University, China
,Wengen Li
Tongji University, China
,Siyun Hou
Tongji University, China
,Jihong Guan
Tongji University, China
,Shuigeng Zhou
Fudan University, China
ACM Transactions on Intelligent Systems and Technology, Volume 14, Issue 4•August 2023, Article No.: 73, pp 1-19 • https://doi.org/10.1145/3597937Sea surface temperature (SST) is one critical parameter of global climate change, and accurate SST prediction is important to various applications, e.g., weather forecasting, fishing directions, and disaster warnings. The global ocean system is unified ...
- 4Citation
- 425
- Downloads
MetricsTotal Citations4Total Downloads425Last 12 Months357Last 6 weeks28
- research-article
Published By ACM
Published By ACM
Keyword-Based Diverse Image Retrieval by Semantics-aware Contrastive Learning and Transformer
Minyi Zhao
Fudan University, Shanghai, China
,Jinpeng Wang
Tsinghua University, Shenzhen, China
,Dongliang Liao
Tencent Inc., Guangzhou, China
,Yiru Wang
Tencent Inc., Beijing, China
,Huanzhong Duan
Tencent Inc., Beijing, China
,Shuigeng Zhou
Fudan University, Shanghai, China
SIGIR '23: Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval•July 2023, pp 1262-1272• https://doi.org/10.1145/3539618.3591705In addition to relevance, diversity is an important yet less studied performance metric of cross-modal image retrieval systems, which is critical to user experience. Existing solutions for diversity-aware image retrieval either explicitly post-process ...
- 1Citation
- 127
- Downloads
MetricsTotal Citations1Total Downloads127Last 12 Months127Last 6 weeks8- 1
Supplementary MaterialSIGIR.mp4
- research-article
Published By ACM
Published By ACM
Conditional Independence Test Based on Residual Similarity
Hao Zhang
School of Computer Science, Fudan University, China
,Yewei Xia
School of Computer Science, Fudan University, China
,Kun Zhang
Department of Philosophy, Carnegie Mellon University, USA
,Shuigeng Zhou
Shanghai Key Lab of Intelligent Information Processing, and School of Computer Science, Fudan University, China
,Jihong Guan
Department of Computer Science and Technology, Tongji University, China
ACM Transactions on Knowledge Discovery from Data, Volume 17, Issue 8•September 2023, Article No.: 117, pp 1-18 • https://doi.org/10.1145/3593810Recently, many regression-based conditional independence (CI) test methods have been proposed to solve the problem of causal discovery. These methods provide alternatives to test CI of x,y given Z by first removing the information of the controlling set Z ...
- 3Citation
- 430
- Downloads
MetricsTotal Citations3Total Downloads430Last 12 Months262Last 6 weeks33
- survey
Published By ACM
Published By ACM
Recent Few-shot Object Detection Algorithms: A Survey with Performance Comparison
Tianying Liu
Tongji University, China
,Lu Zhang
Fudan University, China
,Yang Wang
Tongji University, China
,Jihong Guan
Tongji University, China
,Yanwei Fu
Fudan University, China
,Jiajia Zhao
Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory, China
,Shuigeng Zhou
Fudan University, China
ACM Transactions on Intelligent Systems and Technology, Volume 14, Issue 4•August 2023, Article No.: 66, pp 1-36 • https://doi.org/10.1145/3593588The generic object detection (GOD) task has been successfully tackled by recent deep neural networks, trained by an avalanche of annotated training samples from some common classes. However, it is still non-trivial to generalize these object detectors to ...
- 13Citation
- 855
- Downloads
MetricsTotal Citations13Total Downloads855Last 12 Months699Last 6 weeks46
- research-article
Towards Cross-Lingual Multi-Modal Misinformation Detection for E-Commerce Management
Yifan He
Shanghai Key Laboratory of Intelligent Information Processing and the School of Computer Science, Fudan University, Shanghai, China
,Zhao Li
Alibaba-ZJU Joint Research Institute of Frontier Technologies, Zhejiang University, Hangzhou, China
,Zhenpeng Li
Taobao Search Business Department, Alibaba Group, Hangzhou, China
,Shuigeng Zhou
Shanghai Key Laboratory of Intelligent Information Processing and the School of Computer Science, Fudan University, Shanghai, China
,Ting Yu
Big Data Intelligence Research Center, Zhejiang Lab, Hangzhou, China
,Ji Zhang
University of Southern Queensland, Toowoomba, QLD, Australia
IEEE Transactions on Network and Service Management, Volume 20, Issue 2•June 2023, pp 1040-1050 • https://doi.org/10.1109/TNSM.2023.3234114The misinformation detection systems are increasingly important in E-commerce management, which detect misinformation on the commodity display page. Misinformation in E-commerce is usually presented as a mismatch between multi-modal information, the ...
- 0Citation
MetricsTotal Citations0
- research-article
Generalized multidimensional association rules
Aoying Zhou
Department of Computer Science, Fudan University, 200433, Shanghai, P.R. China
,Shuigeng Zhou
Department of Computer Science, Fudan University, 200433, Shanghai, P.R. China
,Wen Jin
Department of Computer Science, Fudan University, 200433, Shanghai, P.R. China
,Zengping Tian
Department of Computer Science, Fudan University, 200433, Shanghai, P.R. China
Journal of Computer Science and Technology, Volume 15, Issue 4•Jul 2000, pp 388-392 • https://doi.org/10.1007/BF02948876AbstractThe problem of association rule mining has gained considerable prominence in the data mining community for its use as an important tool of knowledge discovery from large-scale databases. And there has been a spurt of research activities around ...
- 0Citation
MetricsTotal Citations0
- research-article
Incremental mining of the schema of semistructured data
Aoying Zhou
Department of Computer Science, Fudan University, 200433, Shanghai, P.R. China
,Wen Jin
Department of Computer Science, Fudan University, 200433, Shanghai, P.R. China
,Shuigeng Zhou
Department of Computer Science, Fudan University, 200433, Shanghai, P.R. China
,Weining Qian
Department of Computer Science, Fudan University, 200433, Shanghai, P.R. China
,Zenping Tian
Department of Computer Science, Fudan University, 200433, Shanghai, P.R. China
Journal of Computer Science and Technology, Volume 15, Issue 3•May 2000, pp 241-248 • https://doi.org/10.1007/BF02948811AbstractSemistructured data are specified in lack of any fixed and rigid schema, even though typically some implicit structure appears in the data. The huge amounts of on-line applications make it important and imperative to mine the schema of ...
- 0Citation
MetricsTotal Citations0
- Article
Two-Stage Multimodality Fusion for High-Performance Text-Based Visual Question Answering
Bingjia Li
Shanghai Key Lab of Intelligent Information Processing, and School of Computer Science, Fudan University, 200438, Shanghai, China
,Jie Wang
ByteDance, Shanghai, China
,Minyi Zhao
Shanghai Key Lab of Intelligent Information Processing, and School of Computer Science, Fudan University, 200438, Shanghai, China
,Shuigeng Zhou
Shanghai Key Lab of Intelligent Information Processing, and School of Computer Science, Fudan University, 200438, Shanghai, China
AbstractText-based visual question answering (TextVQA) is to answer a text-related question by reading texts in a given image, which needs to jointly reason over three modalities—question, visual objects and scene texts in images. Most existing works ...
- 0Citation
MetricsTotal Citations0
- research-article
Multi-level wavelet mapping correlation for statistical dependence measurement: methodology and performance
Yixin Ren
Shanghai Key Lab of Intelligent Information Processing, and School of Computer Science, Fudan University, China
,Hao Zhang
Shanghai Key Lab of Intelligent Information Processing, and School of Computer Science, Fudan University, China
,Yewei Xia
Shanghai Key Lab of Intelligent Information Processing, and School of Computer Science, Fudan University, China
,Jihong Guan
Department of Computer Science & Technology, Tongji University, China
,Shuigeng Zhou
Shanghai Key Lab of Intelligent Information Processing, and School of Computer Science, Fudan University, China
AAAI'23/IAAI'23/EAAI'23: Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence and Thirty-Fifth Conference on Innovative Applications of Artificial Intelligence and Thirteenth Symposium on Educational Advances in Artificial Intelligence•February 2023, Article No.: 730, pp 6499-6506• https://doi.org/10.1609/aaai.v37i5.25799We propose a new criterion for measuring dependence between two real variables, namely, Multi-level Wavelet Mapping Correlation (MWMC). MWMC can capture the nonlinear dependencies between variables by measuring their correlation under different levels of ...
- 0Citation
MetricsTotal Citations0
- research-article
Differentially private nonlinear causal discovery from numerical data
Hao Zhang
Shanghai Key Lab of Intelligent Information Processing, and School of Computer Science, Fudan University, China
,Yewei Xia
Shanghai Key Lab of Intelligent Information Processing, and School of Computer Science, Fudan University, China
,Yixin Ren
Shanghai Key Lab of Intelligent Information Processing, and School of Computer Science, Fudan University, China
,Jihong Guan
Department of Computer Science & Technology, Tongji University, China
,Shuigeng Zhou
Shanghai Key Lab of Intelligent Information Processing, and School of Computer Science, Fudan University, China
AAAI'23/IAAI'23/EAAI'23: Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence and Thirty-Fifth Conference on Innovative Applications of Artificial Intelligence and Thirteenth Symposium on Educational Advances in Artificial Intelligence•February 2023, Article No.: 1383, pp 12321-12328• https://doi.org/10.1609/aaai.v37i10.26452Recently, several methods such as private ANM, EM-PC and Priv-PC have been proposed to perform differentially private causal discovery in various scenarios including bivariate, multivariate Gaussian and categorical cases. However, there is little effort ...
- 0Citation
MetricsTotal Citations0
- short-paper
Published By ACM
Published By ACM
Fusing Geometric and Scene Information for Cross-View Geo-Localization
Siyuan Guo
Tongji University, Shanghai, China
,Tianying Liu
Tongji University, Shanghai, China
,Wengen Li
Tongji University, Shanghai, China
,Jihong Guan
Tongji University, Shanghai, China
,Shuigeng Zhou
Fudan University, Shanghai, China
CIKM '22: Proceedings of the 31st ACM International Conference on Information & Knowledge Management•October 2022, pp 3978-3982• https://doi.org/10.1145/3511808.3557633Cross-view geo-localization is to match scene images (e.g. ground-view images) with geo-tagged aerial images, which is crucial to a wide range of applications such as autonomous driving and street view navigation. Existing methods can neither address ...
- 2Citation
- 134
- Downloads
MetricsTotal Citations2Total Downloads134Last 12 Months39Last 6 weeks1
Author Profile Pages
- Description: The Author Profile Page initially collects all the professional information known about authors from the publications record as known by the ACM bibliographic database, the Guide. Coverage of ACM publications is comprehensive from the 1950's. Coverage of other publishers generally starts in the mid 1980's. The Author Profile Page supplies a quick snapshot of an author's contribution to the field and some rudimentary measures of influence upon it. Over time, the contents of the Author Profile page may expand at the direction of the community.
Please see the following 2007 Turing Award winners' profiles as examples: - History: Disambiguation of author names is of course required for precise identification of all the works, and only those works, by a unique individual. Of equal importance to ACM, author name normalization is also one critical prerequisite to building accurate citation and download statistics. For the past several years, ACM has worked to normalize author names, expand reference capture, and gather detailed usage statistics, all intended to provide the community with a robust set of publication metrics. The Author Profile Pages reveal the first result of these efforts.
- Normalization: ACM uses normalization algorithms to weigh several types of evidence for merging and splitting names.
These include:- co-authors: if we have two names and cannot disambiguate them based on name alone, then we see if they have a co-author in common. If so, this weighs towards the two names being the same person.
- affiliations: names in common with same affiliation weighs toward the two names being the same person.
- publication title: names in common whose works are published in same journal weighs toward the two names being the same person.
- keywords: names in common whose works address the same subject matter as determined from title and keywords, weigh toward being the same person.
The more conservative the merging algorithms, the more bits of evidence are required before a merge is made, resulting in greater precision but lower recall of works for a given Author Profile. Many bibliographic records have only author initials. Many names lack affiliations. With very common family names, typical in Asia, more liberal algorithms result in mistaken merges.
Automatic normalization of author names is not exact. Hence it is clear that manual intervention based on human knowledge is required to perfect algorithmic results. ACM is meeting this challenge, continuing to work to improve the automated merges by tweaking the weighting of the evidence in light of experience.
- Bibliometrics: In 1926, Alfred Lotka formulated his power law (known as Lotka's Law) describing the frequency of publication by authors in a given field. According to this bibliometric law of scientific productivity, only a very small percentage (~6%) of authors in a field will produce more than 10 articles while the majority (perhaps 60%) will have but a single article published. With ACM's first cut at author name normalization in place, the distribution of our authors with 1, 2, 3..n publications does not match Lotka's Law precisely, but neither is the distribution curve far off. For a definition of ACM's first set of publication statistics, see Bibliometrics
- Future Direction:
The initial release of the Author Edit Screen is open to anyone in the community with an ACM account, but it is limited to personal information. An author's photograph, a Home Page URL, and an email may be added, deleted or edited. Changes are reviewed before they are made available on the live site.
ACM will expand this edit facility to accommodate more types of data and facilitate ease of community participation with appropriate safeguards. In particular, authors or members of the community will be able to indicate works in their profile that do not belong there and merge others that do belong but are currently missing.
A direct search interface for Author Profiles will be built.
An institutional view of works emerging from their faculty and researchers will be provided along with a relevant set of metrics.
It is possible, too, that the Author Profile page may evolve to allow interested authors to upload unpublished professional materials to an area available for search and free educational use, but distinct from the ACM Digital Library proper. It is hard to predict what shape such an area for user-generated content may take, but it carries interesting potential for input from the community.
Bibliometrics
The ACM DL is a comprehensive repository of publications from the entire field of computing.
It is ACM's intention to make the derivation of any publication statistics it generates clear to the user.
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- Publication Count = all works of any genre within the universe of ACM's bibliographic database of computing literature of which this person was an author. Works where the person has role as editor, advisor, chair, etc. are listed on the page but are not part of the Publication Count.
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- Available for download = the total number of works by this author whose full texts may be downloaded from an ACM full-text article server. Downloads from external full-text sources linked to from within the ACM bibliographic space are not counted as 'available for download'.
- Average downloads per article = The total number of cumulative downloads divided by the number of articles (including multimedia objects) available for download from ACM's servers.
- Downloads (cumulative) = The cumulative number of times all works by this author have been downloaded from an ACM full-text article server since the downloads were first counted in May 2003. The counts displayed are updated monthly and are therefore 0-31 days behind the current date. Robotic activity is scrubbed from the download statistics.
- Downloads (12 months) = The cumulative number of times all works by this author have been downloaded from an ACM full-text article server over the last 12-month period for which statistics are available. The counts displayed are usually 1-2 weeks behind the current date. (12-month download counts for individual works are displayed with the individual record.)
- Downloads (6 weeks) = The cumulative number of times all works by this author have been downloaded from an ACM full-text article server over the last 6-week period for which statistics are available. The counts displayed are usually 1-2 weeks behind the current date. (6-week download counts for individual works are displayed with the individual record.)
ACM Author-Izer Service
Summary Description
ACM Author-Izer is a unique service that enables ACM authors to generate and post links on both their homepage and institutional repository for visitors to download the definitive version of their articles from the ACM Digital Library at no charge.
Downloads from these sites are captured in official ACM statistics, improving the accuracy of usage and impact measurements. Consistently linking to definitive version of ACM articles should reduce user confusion over article versioning.
ACM Author-Izer also extends ACM’s reputation as an innovative “Green Path” publisher, making ACM one of the first publishers of scholarly works to offer this model to its authors.
To access ACM Author-Izer, authors need to establish a free ACM web account. Should authors change institutions or sites, they can utilize the new ACM service to disable old links and re-authorize new links for free downloads from a different site.
How ACM Author-Izer Works
Authors may post ACM Author-Izer links in their own bibliographies maintained on their website and their own institution’s repository. The links take visitors to your page directly to the definitive version of individual articles inside the ACM Digital Library to download these articles for free.
The Service can be applied to all the articles you have ever published with ACM.
Depending on your previous activities within the ACM DL, you may need to take up to three steps to use ACM Author-Izer.
For authors who do not have a free ACM Web Account:
- Go to the ACM DL http://dl.acm.org/ and click SIGN UP. Once your account is established, proceed to next step.
For authors who have an ACM web account, but have not edited their ACM Author Profile page:
- Sign in to your ACM web account and go to your Author Profile page. Click "Add personal information" and add photograph, homepage address, etc. Click ADD AUTHOR INFORMATION to submit change. Once you receive email notification that your changes were accepted, you may utilize ACM Author-izer.
For authors who have an account and have already edited their Profile Page:
- Sign in to your ACM web account, go to your Author Profile page in the Digital Library, look for the ACM Author-izer link below each ACM published article, and begin the authorization process. If you have published many ACM articles, you may find a batch Authorization process useful. It is labeled: "Export as: ACM Author-Izer Service"
ACM Author-Izer also provides code snippets for authors to display download and citation statistics for each “authorized” article on their personal pages. Downloads from these pages are captured in official ACM statistics, improving the accuracy of usage and impact measurements. Consistently linking to the definitive version of ACM articles should reduce user confusion over article versioning.
Note: You still retain the right to post your author-prepared preprint versions on your home pages and in your institutional repositories with DOI pointers to the definitive version permanently maintained in the ACM Digital Library. But any download of your preprint versions will not be counted in ACM usage statistics. If you use these AUTHOR-IZER links instead, usage by visitors to your page will be recorded in the ACM Digital Library and displayed on your page.
FAQ
- Q. What is ACM Author-Izer?
A. ACM Author-Izer is a unique, link-based, self-archiving service that enables ACM authors to generate and post links on either their home page or institutional repository for visitors to download the definitive version of their articles for free.
- Q. What articles are eligible for ACM Author-Izer?
- A. ACM Author-Izer can be applied to all the articles authors have ever published with ACM. It is also available to authors who will have articles published in ACM publications in the future.
- Q. Are there any restrictions on authors to use this service?
- A. No. An author does not need to subscribe to the ACM Digital Library nor even be a member of ACM.
- Q. What are the requirements to use this service?
- A. To access ACM Author-Izer, authors need to have a free ACM web account, must have an ACM Author Profile page in the Digital Library, and must take ownership of their Author Profile page.
- Q. What is an ACM Author Profile Page?
- A. The Author Profile Page initially collects all the professional information known about authors from the publications record as known by the ACM Digital Library. The Author Profile Page supplies a quick snapshot of an author's contribution to the field and some rudimentary measures of influence upon it. Over time, the contents of the Author Profile page may expand at the direction of the community. Please visit the ACM Author Profile documentation page for more background information on these pages.
- Q. How do I find my Author Profile page and take ownership?
- A. You will need to take the following steps:
- Create a free ACM Web Account
- Sign-In to the ACM Digital Library
- Find your Author Profile Page by searching the ACM Digital Library for your name
- Find the result you authored (where your author name is a clickable link)
- Click on your name to go to the Author Profile Page
- Click the "Add Personal Information" link on the Author Profile Page
- Wait for ACM review and approval; generally less than 24 hours
- Q. Why does my photo not appear?
- A. Make sure that the image you submit is in .jpg or .gif format and that the file name does not contain special characters
- Q. What if I cannot find the Add Personal Information function on my author page?
- A. The ACM account linked to your profile page is different than the one you are logged into. Please logout and login to the account associated with your Author Profile Page.
- Q. What happens if an author changes the location of his bibliography or moves to a new institution?
- A. Should authors change institutions or sites, they can utilize ACM Author-Izer to disable old links and re-authorize new links for free downloads from a new location.
- Q. What happens if an author provides a URL that redirects to the author’s personal bibliography page?
- A. The service will not provide a free download from the ACM Digital Library. Instead the person who uses that link will simply go to the Citation Page for that article in the ACM Digital Library where the article may be accessed under the usual subscription rules.
However, if the author provides the target page URL, any link that redirects to that target page will enable a free download from the Service.
- Q. What happens if the author’s bibliography lives on a page with several aliases?
- A. Only one alias will work, whichever one is registered as the page containing the author’s bibliography. ACM has no technical solution to this problem at this time.
- Q. Why should authors use ACM Author-Izer?
- A. ACM Author-Izer lets visitors to authors’ personal home pages download articles for no charge from the ACM Digital Library. It allows authors to dynamically display real-time download and citation statistics for each “authorized” article on their personal site.
- Q. Does ACM Author-Izer provide benefits for authors?
- A. Downloads of definitive articles via Author-Izer links on the authors’ personal web page are captured in official ACM statistics to more accurately reflect usage and impact measurements.
Authors who do not use ACM Author-Izer links will not have downloads from their local, personal bibliographies counted. They do, however, retain the existing right to post author-prepared preprint versions on their home pages or institutional repositories with DOI pointers to the definitive version permanently maintained in the ACM Digital Library.
- Q. How does ACM Author-Izer benefit the computing community?
- A. ACM Author-Izer expands the visibility and dissemination of the definitive version of ACM articles. It is based on ACM’s strong belief that the computing community should have the widest possible access to the definitive versions of scholarly literature. By linking authors’ personal bibliography with the ACM Digital Library, user confusion over article versioning should be reduced over time.
In making ACM Author-Izer a free service to both authors and visitors to their websites, ACM is emphasizing its continuing commitment to the interests of its authors and to the computing community in ways that are consistent with its existing subscription-based access model.
- Q. Why can’t I find my most recent publication in my ACM Author Profile Page?
- A. There is a time delay between publication and the process which associates that publication with an Author Profile Page. Right now, that process usually takes 4-8 weeks.
- Q. How does ACM Author-Izer expand ACM’s “Green Path” Access Policies?
- A. ACM Author-Izer extends the rights and permissions that authors retain even after copyright transfer to ACM, which has been among the “greenest” publishers. ACM enables its author community to retain a wide range of rights related to copyright and reuse of materials. They include:
- Posting rights that ensure free access to their work outside the ACM Digital Library and print publications
- Rights to reuse any portion of their work in new works that they may create
- Copyright to artistic images in ACM’s graphics-oriented publications that authors may want to exploit in commercial contexts
- All patent rights, which remain with the original owner