The amount of available information has been growing at a phenomenal rate, so that it is more and more difficult to process it. The challenge now consists in developing technologies that can help us sift through all this information. To uncover relationships in data, statistical techniques have been used for many years. Although traditional statistical techniques are still effective for problems involving small datasets and a manageable number of variables, their use make difficulties when applied to problems involving millions of records and thousands of variables. Data mining is thus emerging as a class of techniques enhancing statistics when examining large datasets. This work, suggesting various ways for computing similarities between n...
Appropriately defining and efficiently calculating similarities from large data sets are often essen...
We consider the problem of determining how similar two networks (without known node-correspondences)...
<p>We first calculate pairwise similarities between users via cosine similarity measure or Jaccard i...
This work presents a new perspective on characterizing the similarity between elements of a database...
Abstract—Memory-based methods for recommending data services predict the ratings of active users bas...
This work presents a systematic comparison between seven kernels (or similarity matrices) on a graph...
This work tackles different aspects of how to predict users' interest and behavior with social netwo...
This work presents a new perspective on characterizing the similarity between elements of a database...
In this paper we provide a method that allows the visualization of similarity relationships present ...
We suggest a new similarity measure to improve the quality of data mining, especially for recommende...
Collaborative filtering as a classical method of information retrieval is widely used in helping peo...
Recommender systems are designed to assist individual users to navigate through the rapidly growing ...
Abstract—Similarity method is the key of the user-based collaborative filtering recommend algorithm....
Dataset interlinking is a great important problem in Linked Data. We consider this problem from the ...
Measures of similarity play a subtle but important role in a large number of disciplines. For exampl...
Appropriately defining and efficiently calculating similarities from large data sets are often essen...
We consider the problem of determining how similar two networks (without known node-correspondences)...
<p>We first calculate pairwise similarities between users via cosine similarity measure or Jaccard i...
This work presents a new perspective on characterizing the similarity between elements of a database...
Abstract—Memory-based methods for recommending data services predict the ratings of active users bas...
This work presents a systematic comparison between seven kernels (or similarity matrices) on a graph...
This work tackles different aspects of how to predict users' interest and behavior with social netwo...
This work presents a new perspective on characterizing the similarity between elements of a database...
In this paper we provide a method that allows the visualization of similarity relationships present ...
We suggest a new similarity measure to improve the quality of data mining, especially for recommende...
Collaborative filtering as a classical method of information retrieval is widely used in helping peo...
Recommender systems are designed to assist individual users to navigate through the rapidly growing ...
Abstract—Similarity method is the key of the user-based collaborative filtering recommend algorithm....
Dataset interlinking is a great important problem in Linked Data. We consider this problem from the ...
Measures of similarity play a subtle but important role in a large number of disciplines. For exampl...
Appropriately defining and efficiently calculating similarities from large data sets are often essen...
We consider the problem of determining how similar two networks (without known node-correspondences)...
<p>We first calculate pairwise similarities between users via cosine similarity measure or Jaccard i...