In this work the topic of applying clustering as a knowledge extraction method from real-world data is discussed. The authors propose hierarchical clustering method and visualization technique for knowledge base representation in the context of medical knowledge bases for which data mining techniques are successfully employed and may resolve different problems. What is more, the authors analyze the impact of different clustering parameters on the result of searching through such a structure. Particular attention was also given to the problem of cluster visualization. Authors review selected, two-dimensional approaches, stating their advantages and drawbacks in the context of representing complex cluster structures
Ontologies and hierarchical clustering are both important tools in biology and medicine to study hig...
Similarity search in database systems is becoming an increasingly important task in modern applicat...
The main aim of the article is to present the modifications of inference algorithms based on informa...
In this work the topic of applying clustering as a knowledge extraction method from real-world medic...
AbstractIn this work the topic of applying clustering as a knowledge extraction method from real-wor...
While a genuine abundance of biomedical data available nowadays becomes a genuine blessing, it also ...
There are large quantities of information about patients and their medical conditions. The discovery...
Decision support systems founded on rule-based knowledge representation should be equipped with rule...
Part 1: Long and Short PapersInternational audienceResearch Area: Information visualization, human-c...
The paper deals with the integrated use of Information Visualization techniques and clustering algor...
Similarity search in database systems is becoming an in-creasingly important task in modern applicat...
Similarity search in database systems is becoming an increasingly important task in modern applicati...
Unsupervised learning plays an important role in knowledge exploration and discovery. Two basic exam...
In this work the topic of applying clustering as a knowledge extraction method from real-world data ...
Clustering real-world data is a challenging task, since many real-data collections are characterized...
Ontologies and hierarchical clustering are both important tools in biology and medicine to study hig...
Similarity search in database systems is becoming an increasingly important task in modern applicat...
The main aim of the article is to present the modifications of inference algorithms based on informa...
In this work the topic of applying clustering as a knowledge extraction method from real-world medic...
AbstractIn this work the topic of applying clustering as a knowledge extraction method from real-wor...
While a genuine abundance of biomedical data available nowadays becomes a genuine blessing, it also ...
There are large quantities of information about patients and their medical conditions. The discovery...
Decision support systems founded on rule-based knowledge representation should be equipped with rule...
Part 1: Long and Short PapersInternational audienceResearch Area: Information visualization, human-c...
The paper deals with the integrated use of Information Visualization techniques and clustering algor...
Similarity search in database systems is becoming an in-creasingly important task in modern applicat...
Similarity search in database systems is becoming an increasingly important task in modern applicati...
Unsupervised learning plays an important role in knowledge exploration and discovery. Two basic exam...
In this work the topic of applying clustering as a knowledge extraction method from real-world data ...
Clustering real-world data is a challenging task, since many real-data collections are characterized...
Ontologies and hierarchical clustering are both important tools in biology and medicine to study hig...
Similarity search in database systems is becoming an increasingly important task in modern applicat...
The main aim of the article is to present the modifications of inference algorithms based on informa...