Jinyang Liu
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- ICSE-SEIP '24: Proceedings of the 46th International Conference on Software Engineering: Software Engineering in Practice (2)
- ASE '19: Proceedings of the 34th IEEE/ACM International Conference on Automated Software Engineering (1)
- ASE '21: Proceedings of the 36th IEEE/ACM International Conference on Automated Software Engineering (1)
- ASE '23: Proceedings of the 38th IEEE/ACM International Conference on Automated Software Engineering (1)
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- CIKM '21: Proceedings of the 30th ACM International Conference on Information & Knowledge Management (1)
- ICSE '22: Proceedings of the 44th International Conference on Software Engineering (1)
- ICSE '23: Proceedings of the 45th International Conference on Software Engineering (1)
- ICSE-SEIP '19: Proceedings of the 41st International Conference on Software Engineering: Software Engineering in Practice (1)
- ISSTA 2024: Proceedings of the 33rd ACM SIGSOFT International Symposium on Software Testing and Analysis (1)
- SIGIR '22: Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (1)
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- research-articlefreePublished By ACMPublished By ACM
Identifying Performance Issues in Cloud Service Systems Based on Relational-Temporal Features
- Wenwei Gu
The Chinese University of Hong Kong, Hong Kong SAR
, - Jinyang Liu
The Chinese University of Hong Kong, Hong Kong SAR
, - Zhuangbin Chen
Sun Yat-sen University, China
, - Jianping Zhang
The Chinese University of Hong Kong, Hong Kong SAR
, - Yuxin Su
Sun Yat-sen University, China
, - Jiazhen Gu
The Chinese University of Hong Kong, Hong Kong SAR
, - Cong Feng
Huawei Cloud Computing Technology Co., Ltd, China
, - Zengyin Yang
Huawei Cloud Computing Technology Co., Ltd, China
, - Yongqiang Yang
Huawei Cloud Computing Technology Co., Ltd, China
, - Michael R. Lyu
The Chinese University of Hong Kong, Hong Kong SAR
ACM Transactions on Software Engineering and Methodology, Volume 0, Issue ja • https://doi.org/10.1145/3702978Cloud systems, typically comprised of various components (e.g., microservices), are susceptible to performance issues, which may cause service-level agreement violations and financial losses. Identifying performance issues is thus of paramount importance ...
- 0Citation
- 307
- Downloads
MetricsTotal Citations0Total Downloads307Last 12 Months307Last 6 weeks159
- Wenwei Gu
- research-article
Prism: Revealing Hidden Functional Clusters from Massive Instances in Cloud Systems
- Jinyang Liu
The Chinese University of Hong Kong, Hong Kong SAR, China
, - Zhihan Jiang
The Chinese University of Hong Kong, Hong Kong SAR, China
, - Jiazhen Gu
The Chinese University of Hong Kong, Hong Kong SAR, China
, - Junjie Huang
The Chinese University of Hong Kong, Hong Kong SAR, China
, - Zhuangbin Chen
School of Software Engineering, Sun Yat-sen University, Zhuhai, China
, - Cong Feng
Computing and Networking Innovation Lab, Huawei Cloud Computing Technology Co., Ltd, China
, - Zengyin Yang
Computing and Networking Innovation Lab, Huawei Cloud Computing Technology Co., Ltd, China
, - Yongqiang Yang
Computing and Networking Innovation Lab, Huawei Cloud Computing Technology Co., Ltd, China
, - Michael R. Lyu
The Chinese University of Hong Kong, Hong Kong SAR, China
ASE '23: Proceedings of the 38th IEEE/ACM International Conference on Automated Software Engineering•November 2023, pp 268-280• https://doi.org/10.1109/ASE56229.2023.00077Ensuring the reliability of cloud systems is critical for both cloud vendors and customers. Cloud systems often rely on virtualization techniques to create instances of hardware resources, such as virtual machines. However, virtualization hinders the ...
- 0Citation
- 3
- Downloads
MetricsTotal Citations0Total Downloads3Last 12 Months3Last 6 weeks2
- Jinyang Liu
- research-articleOpen AccessPublished By ACMPublished By ACM
A Large-Scale Evaluation for Log Parsing Techniques: How Far Are We?
- Zhihan Jiang
Chinese University of Hong Kong, Hong Kong, China
, - Jinyang Liu
Chinese University of Hong Kong, Hong Kong, China
, - Junjie Huang
Chinese University of Hong Kong, Hong Kong, China
, - Yichen Li
Chinese University of Hong Kong, Hong Kong, China
, - Yintong Huo
Chinese University of Hong Kong, Hong Kong, China
, - Jiazhen Gu
Chinese University of Hong Kong, Hong Kong, China
, - Zhuangbin Chen
Sun Yat-sen University, Zhuhai, China
, - Jieming Zhu
Huawei Ark Lab, Shenzhen, China
, - Michael R. Lyu
Chinese University of Hong Kong, Hong Kong, China
ISSTA 2024: Proceedings of the 33rd ACM SIGSOFT International Symposium on Software Testing and Analysis•September 2024, pp 223-234• https://doi.org/10.1145/3650212.3652123Log data have facilitated various tasks of software development and maintenance, such as testing, debugging and diagnosing. Due to the unstructured nature of logs, log parsing is typically required to transform log messages into structured data for ...
- 4Citation
- 441
- Downloads
MetricsTotal Citations4Total Downloads441Last 12 Months441Last 6 weeks161
- Zhihan Jiang
- research-articleOpen AccessPublished By ACMPublished By ACM
Go Static: Contextualized Logging Statement Generation
- Yichen Li
Chinese University of Hong Kong, Hong Kong, China
, - Yintong Huo
Chinese University of Hong Kong, Hong Kong, China
, - Renyi Zhong
Chinese University of Hong Kong, Hong Kong, China
, - Zhihan Jiang
Chinese University of Hong Kong, Hong Kong, China
, - Jinyang Liu
Chinese University of Hong Kong, Hong Kong, China
, - Junjie Huang
Chinese University of Hong Kong, Hong Kong, China
, - Jiazhen Gu
Chinese University of Hong Kong, Hong Kong, China
, - Pinjia He
Chinese University of Hong Kong, Shen Zhen, Shenzhen, China
, - Michael R. Lyu
Chinese University of Hong Kong, Hong Kong, China
Proceedings of the ACM on Software Engineering, Volume 1, Issue FSE•July 2024, Article No.: 28, pp 609-630 • https://doi.org/10.1145/3643754Logging practices have been extensively investigated to assist developers in writing appropriate logging statements for documenting software behaviors. Although numerous automatic logging approaches have been proposed, their performance remains ...
- 1Citation
- 312
- Downloads
MetricsTotal Citations1Total Downloads312Last 12 Months312Last 6 weeks67
- Yichen Li
- research-articleOpen AccessPublished By ACMPublished By ACM
LILAC: Log Parsing using LLMs with Adaptive Parsing Cache
- Zhihan Jiang
The Chinese University of Hong Kong, Hong Kong, China
, - Jinyang Liu
The Chinese University of Hong Kong, Hong Kong, China
, - Zhuangbin Chen
Sun Yat-sen University, Zhuhai, China
, - Yichen Li
The Chinese University of Hong Kong, Hong Kong, China
, - Junjie Huang
The Chinese University of Hong Kong, Hong Kong, China
, - Yintong Huo
The Chinese University of Hong Kong, Hong Kong, China
, - Pinjia He
The Chinese University of Hong Kong, Shenzhen, China
, - Jiazhen Gu
The Chinese University of Hong Kong, Hong Kong, China
, - Michael R. Lyu
The Chinese University of Hong Kong, Hong Kong, China
Proceedings of the ACM on Software Engineering, Volume 1, Issue FSE•July 2024, Article No.: 7, pp 137-160 • https://doi.org/10.1145/3643733Log parsing transforms log messages into structured formats, serving as the prerequisite step for various log analysis tasks. Although a variety of log parsing approaches have been proposed, their performance on complicated log data remains compromised ...
- 0Citation
- 860
- Downloads
MetricsTotal Citations0Total Downloads860Last 12 Months860Last 6 weeks217
- Zhihan Jiang
- research-articleOpen AccessPublished By ACMPublished By ACM
FaultProfIT: Hierarchical Fault Profiling of Incident Tickets in Large-scale Cloud Systems
- Junjie Huang
Department of Computer Science and Engineering, The Chinese University of Hong Kong, Hong Kong, Hong Kong, China
, - Jinyang Liu
Department of Computer Science and Engineering, The Chinese University of Hong Kong, Hong Kong, HongKong, China
, - Zhuangbin Chen
School of Software Engineering, Sun Yat-sen University, Guangzhou, China
, - Zhihan Jiang
Department of Computer Science and Engineering, The Chinese University of Hong Kong, Hong Kong, China
, - Yichen Li
Department of Computer Science and Engineering, The Chinese University of Hong Kong, Hong Kong, China
, - Jiazhen Gu
Department of Computer Science and Engineering, The Chinese University of Hong Kong, Hong Kong, China
, - Cong Feng
Computing and Networking Innovation Lab, Huawei Cloud Computing Technology, Shenzhen, China
, - Zengyin Yang
Computing and Networking Innovation Lab, Huawei Cloud Computing Technology, Shenzhen, China
, - Yongqiang Yang
Computing and Networking Innovation Lab, Huawei Cloud Computing Technology, Shenzhen, China
, - Michael R. Lyu
Department of Computer Science and Engineering, The Chinese University of Hong Kong, Hong Kong, China
ICSE-SEIP '24: Proceedings of the 46th International Conference on Software Engineering: Software Engineering in Practice•April 2024, pp 392-404• https://doi.org/10.1145/3639477.3639754Postmortem analysis is essential in the management of incidents within cloud systems, which provides valuable insights to improve system's reliability and robustness. At CloudA1, fault pattern profiling is performed during the postmortem phase, which ...
- 2Citation
- 311
- Downloads
MetricsTotal Citations2Total Downloads311Last 12 Months311Last 6 weeks63
- Junjie Huang
- research-articleOpen AccessPublished By ACMPublished By ACM
Knowledge-aware Alert Aggregation in Large-scale Cloud Systems: a Hybrid Approach
- Jinxi Kuang
The Chinese University of Hong Kong, Hong Kong, China
, - Jinyang Liu
The Chinese University of Hong Kong, Hong Kong, China
, - Junjie Huang
The Chinese University of Hong Kong, Hong Kong, China
, - Renyi Zhong
The Chinese University of Hong Kong, Hong Kong, China
, - Jiazhen Gu
The Chinese University of Hong Kong, Hong Kong, China
, - Lan Yu
Computing and Networking Innovation Lab, Huawei Cloud Computing Technology Co., Ltd, Shenzhen, China
, - Rui Tan
Computing and Networking Innovation Lab, Huawei Cloud Computing Technology Co., Ltd, Shenzhen, China
, - Zengyin Yang
Computing and Networking Innovation Lab, Huawei Cloud Computing Technology Co., Ltd, Shenzhen, China
, - Michael R. Lyu
The Chinese University of Hong Kong, Hong Kong, China
ICSE-SEIP '24: Proceedings of the 46th International Conference on Software Engineering: Software Engineering in Practice•April 2024, pp 369-380• https://doi.org/10.1145/3639477.3639745Due to the scale and complexity of cloud systems, a system failure would trigger an "alert storm", i.e., massive correlated alerts. Although these alerts can be traced back to a few root causes, the overwhelming number makes it infeasible for manual ...
- 2Citation
- 353
- Downloads
MetricsTotal Citations2Total Downloads353Last 12 Months353Last 6 weeks71
- Jinxi Kuang
- research-article
Incident-Aware Duplicate Ticket Aggregation for Cloud Systems
- Jinyang Liu
The Chinese University of Hong Kong, Hong Kong SAR, China
, - Shilin He
Microsoft Research, Beijing, China
, - Zhuangbin Chen
The Chinese University of Hong Kong, Hong Kong SAR, China
, - Liqun Li
Microsoft Research, Beijing, China
, - Yu Kang
Microsoft Research, Beijing, China
, - Xu Zhang
Microsoft Research, Beijing, China
, - Pinjia He
The Chinese University of Hong Kong, Shenzhen, China
, - Hongyu Zhang
Chongqing University, Chongqing, China
, - Qingwei Lin
Microsoft Research, Beijing, China
, - Zhangwei Xu
Microsoft Azure, Redmond, USA
, - Saravan Rajmohan
Microsoft 365, Redmond, USA
, - Dongmei Zhang
Microsoft Research, Beijing, China
, - Michael R. Lyu
The Chinese University of Hong Kong, Hong Kong SAR, China
ICSE '23: Proceedings of the 45th International Conference on Software Engineering•May 2023, pp 2299-2311• https://doi.org/10.1109/ICSE48619.2023.00193In cloud systems, incidents are potential threats to customer satisfaction and business revenue. When customers are affected by incidents, they often request customer support service (CSS) from the cloud provider by submitting a support ticket. Many ...
- 0Citation
- 49
- Downloads
MetricsTotal Citations0Total Downloads49Last 12 Months27Last 6 weeks2
- Jinyang Liu
- research-articlePublished By ACMPublished By ACM
BARS: Towards Open Benchmarking for Recommender Systems
- Jieming Zhu
Huawei Noah's Ark Lab, Shenzhen, China
, - Quanyu Dai
Huawei Noah's Ark Lab, Shenzhen, China
, - Liangcai Su
Tsinghua University, Shenzhen, China
, - Rong Ma
Tsinghua University, Beijing, China
, - Jinyang Liu
The Chinese University of Hong Kong, Hong Kong, China
, - Guohao Cai
Huawei Noah's Ark Lab, Shenzhen, China
, - Xi Xiao
Tsinghua University, Shenzhen, China
, - Rui Zhang
ruizhang.info, Shenzhen, China
SIGIR '22: Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval•July 2022, pp 2912-2923• https://doi.org/10.1145/3477495.3531723The past two decades have witnessed the rapid development of personalized recommendation techniques. Despite the significant progress made in both research and practice of recommender systems, to date, there is a lack of a widely-recognized benchmarking ...
- 48Citation
- 549
- Downloads
MetricsTotal Citations48Total Downloads549Last 12 Months164Last 6 weeks18- 1
Supplementary Material3531723-vor.pdf
- Jieming Zhu
- research-articlePublished By ACMPublished By ACM
Adaptive performance anomaly detection for online service systems via pattern sketching
- Zhuangbin Chen
The Chinese University of Hong Kong, Hong Kong, China
, - Jinyang Liu
The Chinese University of Hong Kong, Hong Kong, China
, - Yuxin Su
Sun Yat-sen University, Zhuhai, China
, - Hongyu Zhang
The University of Newcastle, NSW, Australia
, - Xiao Ling
Huawei Cloud BU, Beijing, China
, - Yongqiang Yang
Huawei Cloud BU, Beijing, China
, - Michael R. Lyu
The Chinese University of Hong Kong, Hong Kong, China
ICSE '22: Proceedings of the 44th International Conference on Software Engineering•May 2022, pp 61-72• https://doi.org/10.1145/3510003.3510085To ensure the performance of online service systems, their status is closely monitored with various software and system metrics. Performance anomalies represent the performance degradation issues (e.g., slow response) of the service systems. When ...
- 18Citation
- 463
- Downloads
MetricsTotal Citations18Total Downloads463Last 12 Months134Last 6 weeks13
- Zhuangbin Chen
- research-article
Graph-based incident aggregation for large-scale online service systems
- Zhuangbin Chen
The Chinese University of Hong Kong, Hong Kong, China
, - Jinyang Liu
The Chinese University of Hong Kong, Hong Kong, China
, - Yuxin Su
The Chinese University of Hong Kong, Hong Kong, China
, - Hongyu Zhang
The University of Newcastle, NSW, Australia
, - Xuemin Wen
Huawei, China
, - Xiao Ling
Huawei, China
, - Yongqiang Yang
Huawei, China
, - Michael R. Lyu
The Chinese University of Hong Kong, Hong Kong, China
ASE '21: Proceedings of the 36th IEEE/ACM International Conference on Automated Software Engineering•November 2021, pp 430-442• https://doi.org/10.1109/ASE51524.2021.9678746As online service systems continue to grow in terms of complexity and volume, how service incidents are managed will significantly impact company revenue and user trust. Due to the cascading effect, cloud failures often come with an overwhelming number ...
- 6Citation
- 69
- Downloads
MetricsTotal Citations6Total Downloads69Last 12 Months20Last 6 weeks4
- Zhuangbin Chen
- articlePublished By ACMPublished By ACM
An Intelligent Framework for Timely, Accurate, and Comprehensive Cloud Incident Detection
- Yichen Li
The Chinese University of Hong Kong, Hong Kong, China
, - Xu Zhang
Microsoft Research, Beijing 100080, China
, - Shilin He
Microsoft Research, Beijing 100080, China
, - Zhuangbin Chen
The Chinese University of Hong Kong, Hong Kong, China
, - Yu Kang
Microsoft Research, Beijing 100080, China
, - Jinyang Liu
The Chinese University of Hong Kong, Hong Kong, China
, - Liqun Li
Microsoft Research, Beijing 100080, China
, - Yingnong Dang
Microsoft Azure, Redmond, WA 98052, USA
, - Feng Gao
Microsoft Azure, Redmond, WA 98052, USA
, - Zhangwei Xu
Microsoft Azure, Redmond, WA 98052, USA
, - Saravan Rajmohan
Microsoft 365, Redmond, WA 98052, USA
, - Qingwei Lin
Microsoft Research, Beijing 100080, China
, - Dongmei Zhang
Microsoft Research, Beijing 100080, China
, - Michael R. Lyu
The Chinese University of Hong Kong, Hong Kong, China
ACM SIGOPS Operating Systems Review, Volume 56, Issue 1•June 2022, pp 1-7 • https://doi.org/10.1145/3544497.3544499Cloud incidents (service interruptions or performance degradation) dramatically degrade the reliability of large-scale cloud systems, causing customer dissatisfaction and revenue loss. With years of efforts, cloud providers are able to solve most ...
- 9Citation
- 438
- Downloads
MetricsTotal Citations9Total Downloads438Last 12 Months77Last 6 weeks9
- Yichen Li
- research-articlePublished By ACMPublished By ACM
Open Benchmarking for Click-Through Rate Prediction
- Jieming Zhu
Huawei Noah's Ark Lab, Shenzhen, China
, - Jinyang Liu
The Chinese University of Hong Kong, Hong Kong, China
, - Shuai Yang
Peking University, Beijing, China
, - Qi Zhang
Huawei Noah's Ark Lab, Beijing, China
, - Xiuqiang He
Huawei Noah's Ark Lab, Shenzhen, China
CIKM '21: Proceedings of the 30th ACM International Conference on Information & Knowledge Management•October 2021, pp 2759-2769• https://doi.org/10.1145/3459637.3482486Click-through rate (CTR) prediction is a critical task for many applications, as its accuracy has a direct impact on user experience and platform revenue. In recent years, CTR prediction has been widely studied in both academia and industry, resulting ...
- 60Citation
- 754
- Downloads
MetricsTotal Citations60Total Downloads754Last 12 Months190Last 6 weeks23- 1
Supplementary MaterialFuxiCTR-video.mp4
- Jieming Zhu
- research-articlePublished By ACMPublished By ACM
Ensembled CTR Prediction via Knowledge Distillation
- Jieming Zhu
Huawei Noah's Ark Lab, Shenzhen, China
, - Jinyang Liu
Sun Yat-Sen University, Guangzhou, China
, - Weiqi Li
Sun Yat-Sen University, Guangzhou, China
, - Jincai Lai
Huawei Noah's Ark Lab, Shenzhen, China
, - Xiuqiang He
Huawei Noah's Ark Lab, Shenzhen, China
, - Liang Chen
Sun Yat-Sen University, Guangzhou, China
, - Zibin Zheng
Sun Yat-sen University, Guangzhou, China
CIKM '20: Proceedings of the 29th ACM International Conference on Information & Knowledge Management•October 2020, pp 2941-2958• https://doi.org/10.1145/3340531.3412704Recently, deep learning-based models have been widely studied for click-through rate (CTR) prediction and lead to improved prediction accuracy in many industrial applications. However, current research focuses primarily on building complex network ...
- 35Citation
- 898
- Downloads
MetricsTotal Citations35Total Downloads898Last 12 Months83Last 6 weeks6- 1
Supplementary Material3340531.3412704.mp4
- Jieming Zhu
- research-article
Logzip: extracting hidden structures via iterative clustering for log compression
- Jinyang Liu
Sun Yat-Sen University, Guangzhou, China and The Chinese University of Hong Kong, Hong Kong, China
, - Jieming Zhu
Huawei Noah's Ark Lab, Shenzhen, China
, - Shilin He
The Chinese University of Hong Kong, Hong Kong, China
, - Pinjia He
ETH Zurich, Switzerland
, - Zibin Zheng
Sun Yat-Sen University, Guangzhou, China
, - Michael R. Lyu
The Chinese University of Hong Kong, Hong Kong, China
ASE '19: Proceedings of the 34th IEEE/ACM International Conference on Automated Software Engineering•November 2019, pp 863-873• https://doi.org/10.1109/ASE.2019.00085System logs record detailed runtime information of software systems and are used as the main data source for many tasks around software engineering. As modern software systems are evolving into large scale and complex structures, logs have become one ...
- 22Citation
- 136
- Downloads
MetricsTotal Citations22Total Downloads136Last 12 Months25
- Jinyang Liu
- research-article
Tools and benchmarks for automated log parsing
- Jieming Zhu
Huawei Noah's Ark Lab, Shenzhen, China
, - Shilin He
The Chinese University of Hong Kong, Hong Kong
, - Jinyang Liu
Sun Yat-Sen University, Guangzhou, China
, - Pinjia He
ETH Zurich, Switzerland
, - Qi Xie
Southwest Minzu University, Chengdu, China
, - Zibin Zheng
Sun Yat-Sen University, Guangzhou, China
, - Michael R. Lyu
The Chinese University of Hong Kong, Hong Kong
ICSE-SEIP '19: Proceedings of the 41st International Conference on Software Engineering: Software Engineering in Practice•May 2019, pp 121-130• https://doi.org/10.1109/ICSE-SEIP.2019.00021Logs are imperative in the development and maintenance process of many software systems. They record detailed runtime information that allows developers and support engineers to monitor their systems and dissect anomalous behaviors and errors. The ...
- 71Citation
- 464
- Downloads
MetricsTotal Citations71Total Downloads464Last 12 Months37Last 6 weeks4
- Jieming Zhu
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.
- Average citations per article = The total Citation Count divided by the total Publication Count.
- Citation Count = cumulative total number of times all authored works by this author were cited by other works within ACM's bibliographic database. Almost all reference lists in articles published by ACM have been captured. References lists from other publishers are less well-represented in the database. Unresolved references are not included in the Citation Count. The Citation Count is citations TO any type of work, but the references counted are only FROM journal and proceedings articles. Reference lists from books, dissertations, and technical reports have not generally been captured in the database. (Citation Counts for individual works are displayed with the individual record listed on the Author Page.)
- 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.
- Publication Years = the span from the earliest year of publication on a work by this author to the most recent year of publication of a work by this author captured within the ACM bibliographic database of computing literature (The ACM Guide to Computing Literature, also known as "the Guide".
- 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