ACM Transactions on Evolutionary Learning and Optimization
E61022
ACM Transactions on Evolutionary Learning and Optimization is a peer-reviewed scholarly journal published by the Association for Computing Machinery that focuses on research in evolutionary computation, machine learning, and optimization methods.
All labels observed (1)
| Label | Occurrences |
|---|---|
| ACM Transactions on Evolutionary Learning and Optimization canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T488008 — resolving that mention is where its identity was fixed. The disambiguator weighed these candidate entities and picked the highlighted one (or “None”, minting a new entity). This is how homonymy is resolved: the same surface form can point to different entities.
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: ACM Transactions on Evolutionary Learning and Optimization Context triple: [ACM Transactions series, hasMemberJournal, ACM Transactions on Evolutionary Learning and Optimization]
-
A.
ACM SIGEVO
ACM SIGEVO is the Association for Computing Machinery’s Special Interest Group on Genetic and Evolutionary Computation, focusing on research and conferences in evolutionary algorithms and related fields.
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B.
ACM Transactions series
The ACM Transactions series is a collection of peer-reviewed scholarly journals published by the Association for Computing Machinery, each focusing on a specific area of computer science and information technology research.
-
C.
IEEE Transactions on Automation Science and Engineering
IEEE Transactions on Automation Science and Engineering is a peer-reviewed scholarly journal focusing on the theory, design, and applications of automation in areas such as manufacturing, logistics, healthcare, and service systems.
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D.
ACM Digital Library
The ACM Digital Library is a comprehensive online research repository providing access to the Association for Computing Machinery’s journals, conference proceedings, technical magazines, and other computing-related publications.
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E.
IEEE Xplore Digital Library
IEEE Xplore Digital Library is an online research platform providing access to a vast collection of scientific and technical literature in electrical engineering, computer science, and related fields.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: ACM Transactions on Evolutionary Learning and Optimization Target entity description: ACM Transactions on Evolutionary Learning and Optimization is a peer-reviewed scholarly journal published by the Association for Computing Machinery that focuses on research in evolutionary computation, machine learning, and optimization methods.
-
A.
ACM SIGEVO
ACM SIGEVO is the Association for Computing Machinery’s Special Interest Group on Genetic and Evolutionary Computation, focusing on research and conferences in evolutionary algorithms and related fields.
-
B.
ACM Transactions series
The ACM Transactions series is a collection of peer-reviewed scholarly journals published by the Association for Computing Machinery, each focusing on a specific area of computer science and information technology research.
-
C.
IEEE Transactions on Automation Science and Engineering
IEEE Transactions on Automation Science and Engineering is a peer-reviewed scholarly journal focusing on the theory, design, and applications of automation in areas such as manufacturing, logistics, healthcare, and service systems.
-
D.
ACM Digital Library
The ACM Digital Library is a comprehensive online research repository providing access to the Association for Computing Machinery’s journals, conference proceedings, technical magazines, and other computing-related publications.
-
E.
IEEE Xplore Digital Library
IEEE Xplore Digital Library is an online research platform providing access to a vast collection of scientific and technical literature in electrical engineering, computer science, and related fields.
- F. None of above. chosen
Statements (45)
| Predicate | Object |
|---|---|
| instanceOf |
academic journal
ⓘ
peer-reviewed journal ⓘ scientific journal ⓘ |
| academicDiscipline |
artificial intelligence
ⓘ
computer science ⓘ evolutionary computation ⓘ machine learning ⓘ optimization ⓘ |
| field |
artificial intelligence
ⓘ
computer science ⓘ operations research ⓘ |
| focusesOn |
applications of evolutionary computation
ⓘ
computational intelligence ⓘ data-driven optimization ⓘ evolutionary algorithms ⓘ evolutionary learning ⓘ hybrid evolutionary and machine learning methods ⓘ learning-based optimization ⓘ metaheuristics ⓘ optimization methods ⓘ theoretical foundations of evolutionary computation ⓘ |
| format | journal articles ⓘ |
| hasAbbreviation | ACM TELO ⓘ |
| language | English ⓘ |
| medium | online ⓘ |
| publisher | Association for Computing Machinery ⓘ |
| publishingOrganization | ACM ⓘ |
| reviewProcess | peer-reviewed ⓘ |
| subjectArea |
applied optimization
ⓘ
bio-inspired computation ⓘ black-box optimization ⓘ combinatorial optimization ⓘ continuous optimization ⓘ evolutionary game theory ⓘ evolutionary learning ⓘ multi-objective optimization ⓘ optimization theory ⓘ reinforcement learning for optimization ⓘ stochastic optimization ⓘ surrogate-assisted optimization ⓘ |
| targetAudience |
academics
ⓘ
optimization specialists ⓘ practitioners in evolutionary computation ⓘ practitioners in machine learning ⓘ researchers ⓘ |
How these facts were elicited
The pipeline generated the facts above by prompting gpt-5.1 with this entity's name + description and the instruction below.
Instruction
You are a knowledge base construction expert. Given a subject entity and a description of it, return factual statements that you know for the subject as a JSON list of dictionaries(triples), where keys must be "subject", "predicate" and "object". The number of facts may be very high, between 25 to 50 or more, for very popular subjects. For less popular subjects, the number of facts can be very low, like 5 or 10. # Requirements - If you don't know the subject at all, return an empty list. - If the subject is not a named entity, return an empty list. - Include at least one triple where predicate is "instanceOf". - Do not get too wordy. - Separate several objects into multiple triples with one object.
Input
Subject: ACM Transactions on Evolutionary Learning and Optimization Description of subject: ACM Transactions on Evolutionary Learning and Optimization is a peer-reviewed scholarly journal published by the Association for Computing Machinery that focuses on research in evolutionary computation, machine learning, and optimization methods.
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.
ACM Transactions series
→
hasMemberJournal
→
ACM Transactions on Evolutionary Learning and Optimization
ⓘ