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A similarity measure can take many different forms depending on the type of data being clustered and the specific problem being solved. One of the most commonly used similarity measures is the Euclidean distance, which is used in many clustering techniques including K-means clustering and Hierarchical clustering. The Euclidean distance is a ...
An analysis by Schwarzer et al. [4] showed that the citation-based measures CPA and co-citation analysis, have complementary strengths compared to text-based similarity measures. Text-based similarity approaches reliably identified more narrowly similar articles out of a test collection of Wikipedia articles, e.g. articles sharing identical ...
Bibliographic coupling, like co-citation, is a similarity measure that uses citation analysis to establish a similarity relationship between documents. Bibliographic coupling occurs when two works reference a common third work in their bibliographies. It is an indication that a probability exists that the two works treat a related subject matter.
Like bibliographic coupling, co-citation is a semantic similarity measure for documents that makes use of citation analyses. The figure to the right illustrates the concept of co-citation and a more recent variation of co-citation which accounts for the placement of citations in the full text of documents.
Obviously, similarity of other domain-specific aspects are important as well; these can — and should be combined with relational structural-context similarity for an overall similarity measure. For example, for Web pages SimRank can be combined with traditional textual similarity; the same idea applies to scientific papers or other document ...
Given a matrix of rank dissimilarities between a set of samples, each belonging to a single site (e.g. a single treatment group), the ANOSIM tests whether we can reject the null hypothesis that the similarity between sites is greater than or equal to the similarity within each site. The test statistic R is calculated in the following way:
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