@article{10.1371/journal.pone.0104813, author = {Yildirim, , Muhammed A. AND Coscia, , Michele}, journal = {PLoS ONE}, publisher = {Public Library of Science}, title = {Using Random Walks to Generate Associations between Objects}, year = {2014}, month = {08}, volume = {9}, url = {http://dx.doi.org/10.1371%2Fjournal.pone.0104813}, pages = {e104813}, abstract = {
Measuring similarities between objects based on their attributes has been an important problem in many disciplines. Object-attribute associations can be depicted as links on a bipartite graph. A similarity measure can be thought as a unipartite projection of this bipartite graph. The most widely used bipartite projection techniques make assumptions that are not often fulfilled in real life systems, or have the focus on the bipartite connections more than on the unipartite connections. Here, we define a new similarity measure that utilizes a practical procedure to extract unipartite graphs without making