IEEE International Conference on Data Mining
E91280
The IEEE International Conference on Data Mining is a leading annual research conference that focuses on advances in data mining, machine learning, and knowledge discovery in databases.
All labels observed (2)
| Label | Occurrences |
|---|---|
| ICDM | 1 |
| IEEE International Conference on Data Mining canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T768076 — 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: IEEE International Conference on Data Mining Context triple: [IEEE conferences, example, IEEE International Conference on Data Mining]
-
A.
ACM Transactions on Knowledge Discovery from Data
ACM Transactions on Knowledge Discovery from Data is a peer-reviewed scholarly journal published by the Association for Computing Machinery that focuses on research in data mining, knowledge discovery, and related areas of data science and machine learning.
-
B.
SIGKDD
SIGKDD is the ACM Special Interest Group on Knowledge Discovery and Data Mining, best known for its flagship KDD conference and contributions to data mining and machine learning research.
-
C.
ACM Transactions on Data Science
ACM Transactions on Data Science is a peer-reviewed scholarly journal published by the Association for Computing Machinery that focuses on research in data science, including theory, methods, and applications.
-
D.
ACM International Conference on Web Search and Data Mining
The ACM International Conference on Web Search and Data Mining (WSDM) is a leading annual computer science research conference focusing on web search, data mining, and related areas of information retrieval and machine learning.
-
E.
ACM International Conference on Web Intelligence
The ACM International Conference on Web Intelligence is a leading research conference focused on the theory and applications of artificial intelligence, data mining, and knowledge discovery on the web and related online systems.
- 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: IEEE International Conference on Data Mining Target entity description: The IEEE International Conference on Data Mining is a leading annual research conference that focuses on advances in data mining, machine learning, and knowledge discovery in databases.
-
A.
ACM Transactions on Knowledge Discovery from Data
ACM Transactions on Knowledge Discovery from Data is a peer-reviewed scholarly journal published by the Association for Computing Machinery that focuses on research in data mining, knowledge discovery, and related areas of data science and machine learning.
-
B.
SIGKDD
SIGKDD is the ACM Special Interest Group on Knowledge Discovery and Data Mining, best known for its flagship KDD conference and contributions to data mining and machine learning research.
-
C.
ACM Transactions on Data Science
ACM Transactions on Data Science is a peer-reviewed scholarly journal published by the Association for Computing Machinery that focuses on research in data science, including theory, methods, and applications.
-
D.
ACM International Conference on Web Search and Data Mining
The ACM International Conference on Web Search and Data Mining (WSDM) is a leading annual computer science research conference focusing on web search, data mining, and related areas of information retrieval and machine learning.
-
E.
ACM International Conference on Web Intelligence
The ACM International Conference on Web Intelligence is a leading research conference focused on the theory and applications of artificial intelligence, data mining, and knowledge discovery on the web and related online systems.
- F. None of above. chosen
Statements (49)
| Predicate | Object |
|---|---|
| instanceOf |
academic conference
ⓘ
computer science conference ⓘ data mining conference ⓘ |
| acronym |
IEEE International Conference on Data Mining
self-linksurface differs
ⓘ
surface form:
ICDM
|
| area |
artificial intelligence
ⓘ
computer science ⓘ data science ⓘ |
| category | top-tier data mining conference ⓘ |
| community |
data mining research community
ⓘ
knowledge discovery community ⓘ machine learning research community ⓘ |
| field |
data mining
ⓘ
knowledge discovery in databases ⓘ machine learning ⓘ |
| frequency | annual ⓘ |
| goal |
advance the state of the art in data mining
ⓘ
provide a forum for researchers and practitioners ⓘ |
| hasFeature |
competitive acceptance rate
ⓘ
peer-reviewed ⓘ proceedings published ⓘ research-focused ⓘ |
| hasTopic |
anomaly detection
ⓘ
applications of data mining ⓘ big data analytics ⓘ classification ⓘ clustering ⓘ data mining algorithms ⓘ deep learning for data mining ⓘ graph mining ⓘ knowledge discovery in databases ⓘ pattern mining ⓘ privacy-preserving data mining ⓘ recommender systems ⓘ social network analysis ⓘ spatiotemporal data mining ⓘ stream data mining ⓘ text mining ⓘ web mining ⓘ |
| includes |
industry track
ⓘ
keynote talks ⓘ poster sessions ⓘ research paper sessions ⓘ tutorials ⓘ workshops ⓘ |
| language | English ⓘ |
| organizer | IEEE Computer Society ⓘ |
| publisherOfProceedings |
Institute of Electrical and Electronics Engineers
ⓘ
surface form:
IEEE
|
| scope | international ⓘ |
| sponsor |
Institute of Electrical and Electronics Engineers
ⓘ
surface form:
IEEE
|
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: IEEE International Conference on Data Mining Description of subject: The IEEE International Conference on Data Mining is a leading annual research conference that focuses on advances in data mining, machine learning, and knowledge discovery in databases.
Referenced by (2)
Full triples — surface form annotated when it differs from this entity's canonical label.
IEEE International Conference on Data Mining
→
acronym
→
IEEE International Conference on Data Mining
self-linksurface differs
ⓘ
this entity surface form:
ICDM