Yoav Goldberg
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Proceedings/Book Names
- HLT '11: Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies: short papers - Volume 2 (2)
- NIPS'19: Proceedings of the 33rd International Conference on Neural Information Processing Systems (2)
- SPMRL '10: Proceedings of the NAACL HLT 2010 First Workshop on Statistical Parsing of Morphologically-Rich Languages (2)
- ACL-44: Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics (1)
- Advances in Web and Network Technologies, and Information Management (1)
- CALC '09: Proceedings of the Workshop on Computational Approaches to Linguistic Creativity (1)
- CICLing'08: Proceedings of the 9th international conference on Computational linguistics and intelligent text processing (1)
- CoNLL '10: Proceedings of the Fourteenth Conference on Computational Natural Language Learning (1)
- Cyber Security, Cryptology, and Machine Learning (1)
- EACL '09: Proceedings of the 12th Conference of the European Chapter of the Association for Computational Linguistics (1)
- EMNLP '09: Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 3 - Volume 3 (1)
- FAccT '21: Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency (1)
- FAccT '22: Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (1)
- FAccT '23: Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (1)
- HLT '10: Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics (1)
- HLT-Short '08: Proceedings of the 46th Annual Meeting of the Association for Computational Linguistics on Human Language Technologies: Short Papers (1)
- ISI'06: Proceedings of the 4th IEEE international conference on Intelligence and Security Informatics (1)
- IWPT '09: Proceedings of the 11th International Conference on Parsing Technologies (1)
- Leveraging Applications of Formal Methods, Verification and Validation: Engineering Principles (1)
- RECOMB'11: Proceedings of the 15th Annual international conference on Research in computational molecular biology (1)
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- Association for Computational Linguistics (13)
- Springer-Verlag (6)
- Curran Associates Inc. (5)
- MIT Press (4)
- Association for Computing Machinery (3)
- AI Access Foundation (2)
- Elsevier Science (2)
- Kluwer Academic Publishers (2)
- Elsevier Science Publishers Ltd. (1)
- IBM Corp. (1)
- Morgan & Claypool Publishers (1)
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- Article
Polynomial Adaptation of Large-Scale CNNs for Homomorphic Encryption-Based Secure Inference
- Moran Baruch
https://ror.org/05rw9t746IBM Research, Haifa, Israel
https://ror.org/03kgsv495Bar-Ilan University, Ramat Gan, Israel
, - Nir Drucker
https://ror.org/05rw9t746IBM Research, Haifa, Israel
, - Gilad Ezov
https://ror.org/05rw9t746IBM Research, Haifa, Israel
, - Yoav Goldberg
https://ror.org/03kgsv495Bar-Ilan University, Ramat Gan, Israel
AI2, Tel Aviv-Yafo, Israel
, - Eyal Kushnir
https://ror.org/05rw9t746IBM Research, Haifa, Israel
, - Jenny Lerner
https://ror.org/05rw9t746IBM Research, Haifa, Israel
, - Omri Soceanu
https://ror.org/05rw9t746IBM Research, Haifa, Israel
, - Itamar Zimerman
https://ror.org/05rw9t746IBM Research, Haifa, Israel
Cyber Security, Cryptology, and Machine Learning•December 2024, pp 3-25• https://doi.org/10.1007/978-3-031-76934-4_1AbstractEnabling secure inference of large-scale CNNs using Homomorphic Encryption (HE) requires a preliminary step for adapting unencrypted pre-trained models to only use polynomial operations. Prior art advocates for high-degree polynomials for accurate ...
- 0Citation
MetricsTotal Citations0
- Moran Baruch
- correction
Correction to: Extracting automata from recurrent neural networks using queries and counterexamples (extended version)
- Gail Weiss
https://ror.org/03qryx823Technion, Haifa, Israel
, - Yoav Goldberg
https://ror.org/03kgsv495Bar Ilan University, Ramat Gan, Israel
, - Eran Yahav
https://ror.org/03qryx823Technion, Haifa, Israel
Machine Language, Volume 113, Issue 11•Dec 2024, pp 8769-8769 • https://doi.org/10.1007/s10994-024-06628-6- 0Citation
MetricsTotal Citations0
- Gail Weiss
- articlefree
Diagnosing AI Explanation Methods with Folk Concepts of Behavior
- Alon Jacovi
Bar Ilan University and Google Research
, - Jasmijn Bastings
Google Research
, - Sebastian Gehrmann
Google Research
, - Yoav Goldberg
Bar Ilan University and the Allen Institute for Artificial Intelligence
, - Katja Filippova
Google Research
Journal of Artificial Intelligence Research, Volume 78•Jan 2024 • https://doi.org/10.1613/jair.1.14053We investigate a formalism for the conditions of a successful explanation of AI. We consider “success” to depend not only on what information the explanation contains, but also on what information the human explainee understands from it. Theory of mind ...
- 0Citation
- 198
- Downloads
MetricsTotal Citations0Total Downloads198Last 12 Months124Last 6 weeks20
- Alon Jacovi
- research-article
Linguistic binding in diffusion models: enhancing attribute correspondence through attention map alignment
- Royi Rassin
Bar-Ilan University, Israel
, - Eran Hirsch
Bar-Ilan University, Israel
, - Daniel Glickman
Bar-Ilan University, Israel
, - Shauli Ravfogel
Bar-Ilan University, Israel and Allen Institute for AI, Israel
, - Yoav Goldberg
Bar-Ilan University, Israel and Allen Institute for AI, Israel
, - Gal Chechik
Bar-Ilan University, Israel and NVIDIA, Israel
NIPS '23: Proceedings of the 37th International Conference on Neural Information Processing Systems•December 2023, Article No.: 157, pp 3536-3559Text-conditioned image generation models often generate incorrect associations between entities and their visual attributes. This reflects an impaired mapping between linguistic binding of entities and modifiers in the prompt and visual binding of the ...
- 0Citation
MetricsTotal Citations0
- Royi Rassin
- research-article
Extending the boundaries of cancer therapeutic complexity with literature text mining
- Danna Niezni
Faculty of Biomedical Engineering, Technion – Israel Institute of Technology, Haifa, Israel
, - Hillel Taub-Tabib
Allen Institute for AI, Tel Aviv, Israel
, - Yuval Harris
Faculty of Biomedical Engineering, Technion – Israel Institute of Technology, Haifa, Israel
, - Hagit Sason
Faculty of Biomedical Engineering, Technion – Israel Institute of Technology, Haifa, Israel
, - Yakir Amrusi
Faculty of Biomedical Engineering, Technion – Israel Institute of Technology, Haifa, Israel
, - Dana Meron-Azagury
Faculty of Biomedical Engineering, Technion – Israel Institute of Technology, Haifa, Israel
, - Maytal Avrashami
Faculty of Biomedical Engineering, Technion – Israel Institute of Technology, Haifa, Israel
, - Shaked Launer-Wachs
Faculty of Biomedical Engineering, Technion – Israel Institute of Technology, Haifa, Israel
, - Jon Borchardt
Allen Institute for AI, Seattle, USA
, - M. Kusold
Allen Institute for AI, Seattle, USA
, - Aryeh Tiktinsky
Allen Institute for AI, Tel Aviv, Israel
, - Tom Hope
Allen Institute for AI, Tel Aviv, Israel
The Hebrew University, Jerusalem, Israel
, - Yoav Goldberg
Allen Institute for AI, Tel Aviv, Israel
Bar-Ilan University, Ramat-Gan, Israel
, - Yosi Shamay
Faculty of Biomedical Engineering, Technion – Israel Institute of Technology, Haifa, Israel
Artificial Intelligence in Medicine, Volume 145, Issue C•Nov 2023 • https://doi.org/10.1016/j.artmed.2023.102681AbstractDrug combination therapy is a main pillar of cancer therapy. As the number of possible drug candidates for combinations grows, the development of optimal high complexity combination therapies (involving 4 or more drugs per treatment) such as ...
Graphical abstractDisplay Omitted
Highlights- In cancer therapy complex drug combination is crucial and might be the only option.
- Current complexity space was studied, the current clinical limit is six drugs.
- A novel text data mining-tool was developed to generate of complex ...
- 0Citation
MetricsTotal Citations0
- Danna Niezni
- abstractOpen AccessPublished By ACMPublished By ACM
Diagnosing AI Explanation Methods with Folk Concepts of Behavior
- Alon Jacovi
Bar-Ilan University, Israel
, - Jasmijn Bastings
Google, Netherlands
, - Sebastian Gehrmann
Google, USA
, - Yoav Goldberg
Bar Ilan University, Israel
, - Katja Filippova
Google, Germany
FAccT '23: Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency•June 2023, pp 247-247• https://doi.org/10.1145/3593013.3593993We investigate a formalism for the conditions of a successful explanation of AI. We consider “success” to depend not only on what information the explanation contains, but also on what information the human explainee understands from it. Theory of mind ...
- 0Citation
- 502
- Downloads
MetricsTotal Citations0Total Downloads502Last 12 Months204Last 6 weeks26
- Alon Jacovi
- research-article
From centralized to ad-hoc knowledge base construction for hypotheses generation
- Shaked Launer-Wachs
Faculty of Biomedical Engineering, Technion – Israel Institute of Technology, Haifa, Israel
, - Hillel Taub-Tabib
Allen Institute for AI, Tel Aviv, Israel
, - Jennie Tokarev Madem
Faculty of Biomedical Engineering, Technion – Israel Institute of Technology, Haifa, Israel
, - Orr Bar-Natan
Faculty of Biomedical Engineering, Technion – Israel Institute of Technology, Haifa, Israel
, - Yoav Goldberg
Allen Institute for AI, Tel Aviv, Israel
Bar-Ilan University, Ramat-Gan, Israel
, - Yosi Shamay
Faculty of Biomedical Engineering, Technion – Israel Institute of Technology, Haifa, Israel
Journal of Biomedical Informatics, Volume 142, Issue C•Jun 2023 • https://doi.org/10.1016/j.jbi.2023.104383Graphical abstractDisplay Omitted
Abstract ObjectiveTo demonstrate and develop an approach enabling individual researchers or small teams to create their own ad-hoc, lightweight knowledge bases tailored for specialized scientific interests, using text-mining over scientific literature, ...
- 2Citation
MetricsTotal Citations2
- Shaked Launer-Wachs
- research-articlePublished By ACMPublished By ACM
Human Interpretation of Saliency-based Explanation Over Text
- Hendrik Schuff
Bosch Center for Artificial Intelligence, Germany and University of Stuttgart, Germany
, - Alon Jacovi
Bar Ilan University, Israel
, - Heike Adel
Bosch Center for Artificial Intelligence, Germany
, - Yoav Goldberg
Bar Ilan University, Israel and Allen Institute for Artificial Intelligence, Israel
, - Ngoc Thang Vu
University of Stuttgart, Germany
FAccT '22: Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency•June 2022, pp 611-636• https://doi.org/10.1145/3531146.3533127While a lot of research in explainable AI focuses on producing effective explanations, less work is devoted to the question of how people understand and interpret the explanation. In this work, we focus on this question through a study of saliency-based ...
- 12Citation
- 338
- Downloads
MetricsTotal Citations12Total Downloads338Last 12 Months72Last 6 weeks6
- Hendrik Schuff
- research-article
Extracting automata from recurrent neural networks using queries and counterexamples (extended version)
- Gail Weiss
https://ror.org/03qryx823Technion, Haifa, Israel
, - Yoav Goldberg
https://ror.org/03kgsv495Bar Ilan University, Ramat Gan, Israel
, - Eran Yahav
https://ror.org/03qryx823Technion, Haifa, Israel
Machine Language, Volume 113, Issue 5•May 2024, pp 2877-2919 • https://doi.org/10.1007/s10994-022-06163-2AbstractWe consider the problem of extracting a deterministic finite automaton (DFA) from a trained recurrent neural network (RNN). We present a novel algorithm that uses exact learning and abstract interpretation to perform efficient extraction of a ...
- 0Citation
MetricsTotal Citations0
- Gail Weiss
- research-articlePublished By ACMPublished By ACM
Formalizing Trust in Artificial Intelligence: Prerequisites, Causes and Goals of Human Trust in AI
- Alon Jacovi
Bar Ilan University
, - Ana Marasović
Allen Institute for Artificial Intelligence, University of Washington
, - Tim Miller
School of Computing and Information Systems, The University of Melbourne
, - Yoav Goldberg
Bar Ilan University, Allen Institute for Artificial Intelligence
FAccT '21: Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency•March 2021, pp 624-635• https://doi.org/10.1145/3442188.3445923Trust is a central component of the interaction between people and AI, in that 'incorrect' levels of trust may cause misuse, abuse or disuse of the technology. But what, precisely, is the nature of trust in AI? What are the prerequisites and goals of ...
- 259Citation
- 7,966
- Downloads
MetricsTotal Citations259Total Downloads7,966Last 12 Months2,411Last 6 weeks215
- Alon Jacovi
- research-articlefree
Leap-of-thought: teaching pre-trained models to systematically reason over implicit knowledge
- Alon Talmor
The Allen Institute for AI and Tel-Aviv University
, - Oyvind Tafjord
The Allen Institute for AI
, - Peter Clark
The Allen Institute for AI
, - Yoav Goldberg
The Allen Institute for AI and Bar-Ilan University
, - Jonathan Berant
The Allen Institute for AI and Tel-Aviv University
NIPS '20: Proceedings of the 34th International Conference on Neural Information Processing Systems•December 2020, Article No.: 1698, pp 20227-20237To what extent can a neural network systematically reason over symbolic facts? Evidence suggests that large pre-trained language models (LMs) acquire some reasoning capacity, but this ability is difficult to control. Recently, it has been shown that ...
- 0Citation
- 50
- Downloads
MetricsTotal Citations0Total Downloads50Last 12 Months37Last 6 weeks10
- Alon Talmor
- Article
Synthesizing Control for a System with Black Box Environment, Based on Deep Learning
- Simon Iosti
University Grenoble Alpes VERIMAG, 38410, St. Martin d’Héres, France
, - Doron Peled
Department of Computer Science, Bar Ilan University, 52900, Ramat Gan, Israel
, - Khen Aharon
Department of Computer Science, Bar Ilan University, 52900, Ramat Gan, Israel
, - Saddek Bensalem
University Grenoble Alpes VERIMAG, 38410, St. Martin d’Héres, France
, - Yoav Goldberg
Department of Computer Science, Bar Ilan University, 52900, Ramat Gan, Israel
Leveraging Applications of Formal Methods, Verification and Validation: Engineering Principles•October 2020, pp 457-472• https://doi.org/10.1007/978-3-030-61470-6_27AbstractWe study the synthesis of control for a system that interacts with a black-box environment, based on deep learning. The goal is to minimize the number of interaction failures. The current state of the environment is unavailable to the controller, ...
- 1Citation
MetricsTotal Citations1
- Simon Iosti
- research-articlefree
A little is enough: circumventing defenses for distributed learning
- Moran Baruch
Dept. of Computer Science, Bar Ilan University, Israel
, - Gilad Baruch
Dept. of Computer Science, Bar Ilan University, Israel
, - Yoav Goldberg
Dept. of Computer Science, Bar Ilan University, Israel and The Allen Institute for Artificial Intelligence
NIPS'19: Proceedings of the 33rd International Conference on Neural Information Processing Systems•December 2019, Article No.: 775, pp 8635-8645Distributed learning is central for large-scale training of deep-learning models. However, it is exposed to a security threat in which Byzantine participants can interrupt or control the learning process. Previous attack models assume that the rogue ...
- 2Citation
- 255
- Downloads
MetricsTotal Citations2Total Downloads255Last 12 Months113Last 6 weeks11
- Moran Baruch
- research-articlefree
Learning deterministic weighted automata with queries and counterexamples
- Gail Weiss
Technion
, - Yoav Goldberg
Bar Ilan University, Allen Institute for AI
, - Eran Yahav
Technion
NIPS'19: Proceedings of the 33rd International Conference on Neural Information Processing Systems•December 2019, Article No.: 768, pp 8560-8571We present an algorithm for extraction of a probabilistic deterministic finite automaton (PDFA) from a given black-box language model, such as a recurrent neural network (RNN). The algorithm is a variant of the exact-learning algorithm L*, adapted to a ...
- 1Citation
- 71
- Downloads
MetricsTotal Citations1Total Downloads71Last 12 Months28Last 6 weeks11
- Gail Weiss
- research-article
Mining fall-related information in clinical notes: Comparison of rule-based and novel word embedding-based machine learning approaches
- Maxim Topaz
School of Nursing & Data Science Institute, Columbia University, New York, NY, USA
The Visiting Nurse Service of New York, New York, NY, USA
, - Ludmila Murga
Cheryl Spencer Department of Nursing, University of Haifa, Haifa, Israel
, - Katherine M. Gaddis
School of Nursing, University of Pennsylvania, Philadelphia, PA, USA
, - Margaret V. McDonald
The Visiting Nurse Service of New York, New York, NY, USA
, - Ofrit Bar-Bachar
Cheryl Spencer Department of Nursing, University of Haifa, Haifa, Israel
, - Yoav Goldberg
Department of Computer Science, Bar Ilan University, Tel Aviv, Israel
, - Kathryn H. Bowles
The Visiting Nurse Service of New York, New York, NY, USA
School of Nursing, University of Pennsylvania, Philadelphia, PA, USA
Journal of Biomedical Informatics, Volume 90, Issue C•Feb 2019 • https://doi.org/10.1016/j.jbi.2019.103103Graphical abstractDisplay Omitted
Highlights- Labeled clinical text can be used to train machine learning classifiers.
- ...
Abstract BackgroundNatural language processing (NLP) of health-related data is still an expertise demanding, and resource expensive process. We created a novel, open source rapid clinical text mining system called NimbleMiner. ...
- 2Citation
MetricsTotal Citations2
- Maxim Topaz
- Articlefree
On-the-fly operation batching in dynamic computation graphs
- Graham Neubig
Language Technologies Institute, Carnegie Mellon University
, - Yoav Goldberg
Computer Science Department, Bar-Ilan University
, - Chris Dyer
DeepMind
NIPS'17: Proceedings of the 31st International Conference on Neural Information Processing Systems•December 2017, pp 3974-3984Dynamic neural network toolkits such as PyTorch, DyNet, and Chainer offer more flexibility for implementing models that cope with data of varying dimensions and structure, relative to toolkits that operate on statically declared computations (e.g., ...
- 4Citation
- 76
- Downloads
MetricsTotal Citations4Total Downloads76Last 12 Months43Last 6 weeks9
- Graham Neubig
- article
Analysis of sentence embedding models using prediction tasks in natural language processing
- Y. Adi
IBM Research, Haifa, Israel
, - E. Kermany
IBM Research, Haifa, Israel
, - Y. Belinkov
MIT, Computer Science and Artificial Intelligence Laboratory, Cambridge, MA
, - O. Lavi
IBM Research, Haifa Research Labs, Haifa, Israel
, - Y. Goldberg
Bar Ilan University, Ramat Gan, Israel
IBM Journal of Research and Development, Volume 61, Issue 4-5•July/September 2017, pp 3:1-3:9 • https://doi.org/10.1147/JRD.2017.2702858The tremendous success of word embeddings in improving the ability of computers to perform natural language tasks has shifted the research on language representation from word representation to focus on sentence representation. This shift introduced a ...
- 1Citation
MetricsTotal Citations1
- Y. Adi
- article
Greedy transition-based dependency parsing with stack lstms
- Miguel Ballesteros
IBM T. J. Watson Research Center
, - Chris Dyer
Carnegie Mellon University
, - Yoav Goldberg
Bar-Ilan University
, - Noah A. Smith
University of Washington
Computational Linguistics, Volume 43, Issue 2•June 2017, pp 311-347 • https://doi.org/10.1162/COLI_a_00285We introduce a greedy transition-based parser that learns to represent parser states using recurrent neural networks. Our primary innovation that enables us to do this efficiently is a new control structure for sequential neural networks-the stack long ...
- 5Citation
- 54
- Downloads
MetricsTotal Citations5Total Downloads54
- Miguel Ballesteros
Neural Network Methods in Natural Language Processing
Neural networks are a family of powerful machine learning models. This book focuses on the application of neural network models to natural language data. The first half of the book (Parts I and II) covers the basics of supervised machine learning and ...
- 28Citation
MetricsTotal Citations28
- article
A primer on neural network models for natural language processing
- Yoav Goldberg
Computer Science Department, Bar-Ilan University, Israel
Over the past few years, neural networks have re-emerged as powerful machine-learning models, yielding state-of-the-art results in fields such as image recognition and speech processing. More recently, neural network models started to be applied also to ...
- 66Citation
MetricsTotal Citations66
- Yoav Goldberg
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