Top 10 algorithms in data mining
E1099621
UNEXPLORED
"Top 10 algorithms in data mining" is a widely cited survey paper that summarizes and evaluates the most influential data mining algorithms across key tasks such as classification, clustering, and association analysis.
All labels observed (1)
| Label | Occurrences |
|---|---|
| Top 10 algorithms in data mining canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T14447112 — 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: Top 10 algorithms in data mining Context triple: [Xindong Wu, notableWork, Top 10 algorithms in data mining]
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A.
Data Mining: Concepts and Techniques
Data Mining: Concepts and Techniques is a widely used academic textbook that systematically introduces the principles, algorithms, and practical methods of data mining and knowledge discovery from large datasets.
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B.
IEEE International Conference on Data Mining
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.
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C.
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.
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D.
Apriori algorithm
The Apriori algorithm is a classic data mining method used to discover frequent itemsets and association rules in large transactional databases.
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E.
KDD
KDD is the commonly used abbreviation for Norway’s Ministry of Local Government and Regional Development, a government body responsible for municipal affairs, regional policy, and housing.
- 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: Top 10 algorithms in data mining Target entity description: "Top 10 algorithms in data mining" is a widely cited survey paper that summarizes and evaluates the most influential data mining algorithms across key tasks such as classification, clustering, and association analysis.
-
A.
Data Mining: Concepts and Techniques
Data Mining: Concepts and Techniques is a widely used academic textbook that systematically introduces the principles, algorithms, and practical methods of data mining and knowledge discovery from large datasets.
-
B.
IEEE International Conference on Data Mining
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.
-
C.
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.
-
D.
Apriori algorithm
The Apriori algorithm is a classic data mining method used to discover frequent itemsets and association rules in large transactional databases.
-
E.
KDD
KDD is the commonly used abbreviation for Norway’s Ministry of Local Government and Regional Development, a government body responsible for municipal affairs, regional policy, and housing.
- F. None of above. chosen
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.