Events2Join

Clustering rule bases using ontology|based similarity measures


Clustering rule bases using ontology-based similarity measures

In this paper, we present a novel approach for grouping rules based on whether the rule elements share relationships within a domain ontology.

Clustering Rule Bases Using Ontology-Based Similarity Measures

Our method uses vector space modeling of rule atoms and an ontology based semantic similarity measure. We apply a clustering method to detect ...

Clustering rule bases using ontology-based similarity measures

Our method uses vector space modeling of rule atoms and an ontology-based semantic similarity measure. We apply a clustering method to detect rule relatedness, ...

Clustering rule bases using ontology-based similarity measures ...

Our method uses vector space modeling of rule atoms and an ontology-based semantic similarity measure. We apply a clustering method to detect rule relatedness, ...

Table 5 from Clustering rule bases using ontology-based similarity ...

A scalable method to predict the scores of atomic candidate OWL class axioms of different types relies on a semantic similarity measure derived from the ...

Clustering rule bases using ontology-based similarity measures

Clustering rule bases using ontology-based similarity measures. Saeed Hassanpour, Martin J. O'Connor, Amar K. Das∗. Stanford Center for Biomedical ...

Semantic similarity and machine learning with ontologies

One example of such a constraint is the 'true path rule' that was originally proposed in the Gene Ontology [15], which states that if a gene product G has the ...

Rule base simplification with similarity measures | IEEE Conference ...

... using techniques like fuzzy clustering or gradient learning. The result is an unnecessarily complex and a less effective linguistic description of the ...

A rule-based similarity measure - HAL

The properties of this mapping are studied with respect to both the rule set, and the induction algorithm (learner) used to derive this ruleset ...

A Better Approach to Ontology Integration using Clustering Through ...

We use Jaccard Similarity Index as a global similarity measure for clustering. Based on this measure, the popular k-means clustering algorithm is used to ...

An ontology based model for document clustering - Gale

The major challenge is to use the background knowledge in the similarity measure. This paper presents an ontology based annotation of documents and clustering ...

4.1 Clustering: Grouping samples based on their similarity

Take the last question for example. We need to define a distance or similarity metric between patients' expression profiles and use that metric to find groups ...

Medical Document Clustering Using Ontology-Based Term Similarity ...

Recent research shows that ontology as background knowledge can improve document clustering quality with its concept hierarchy knowledge. Previous studies take ...

Ontology based clustering algorithm for information retrieval

... rules from the WEKA decision tree with the help of MATLAB programming. ... Comparing four popular similarity measures in conjunction with several clustering ...

Association Rule Based Similarity Measures for the Clustering of ...

Consequently, we present a weighted Jaccard and vector cosine similarity measure to compute the similarity between the discovered rules. Finally, we group the ...

Publication – Influence of Similarity Measures for Rules and Clusters ...

... Rules and Clusters on the Efficiency of Knowledge Mining in Rule : based knowledge bases. Authors: Agnieszka Justyna Nowak-Brzezińska,; Tomasz Rybotycki ...

Influence of Similarity Measures for Rules and Clusters on the ...

The article presents how the exploration of complex KBs can be applied based on clustering and visualization of rules clusters. The article ...

Variable Clustered Fuzzy Rules for Self-Tuning Scheme for ...

To show a potential rule extraction scheme, the self-tuning fuzzy-logic-based proportional-derivative (STFLPDC) with 49 expert fuzzy rules and 49 clustered ...

Outlier Mining in Rule-Based Knowledge Bases

The goal of the paper is to analyze the influence of using different similarity measures and clustering methods on the number of outliers discovered during ...

Comparison Clustering using Cosine and Fuzzy set based Similarity ...

The rule antecedents of the sparse fuzzy rule bases are not fully covering the input universe.Therefore the applied similarity measure has to be able to ...