a novel measure is proposed to determine the similarity of each pair of nodes based on the number of common neighbours and correlation between the neighbourhood vectors of the nodes Experimental results, on a range of different real-world networks, suggest that the proposed method results in higher...
Yet, similarity in and of itself has yet to be concisely defined. A simple — and slightly circular — definition of it, “is a numerical measure of the degree to which two data objects are alike” (Tan et al., 2005). What makes two entities “alike” can vary depending on what the...
Computer Science - Social and Information NetworksIn many applications, we need to measure similarity between nodes in a large network based on features of their neighborhoods. Although in-network node similarity based on proximity has been well investigated, surprisingly, measuring in-network node ...
[27] locate peers with similar interests, based on their ability to provide files to each other, in order to improve the overall performance of a peer-to-peer network. Xiao et el. [32] measure similarity of interests among web users based on different access log parameters, such as ...
The study claimed substantially improved model in predicting ILI cases using social media. Author in Ref. [9] examine twitter streams to track public sentiments in context of H1N1. Authors have used twitter to measure the actual disease activity in the context of health-related events. The study...
In addition, we provide the following resources and materials [23]: the code for using SIMREC in practice to perform similarity measure recommendation; the code for reproducing the experiments; the meta-datasets used to train the meta-models so they can be continuously extended with new datasets...
In addition, we provide the following resources and materials [23]: the code for using SIMREC in practice to perform similarity measure recommendation; the code for reproducing the experiments; the meta-datasets used to train the meta-models so they can be continuously extended with new datasets...
(3) below. The proposed loss function can not only implicitly define the similarity measure which is the end-to-end similarity value of the output two characters images but also achieve the goal of metric learning that the similarity of similar characters is high while the similarity of ...
The Similarity Index (SI) in a TSSP, first proposed by Palaćın et al. (2018), is an aggregated measure of how similar the recourse variables are among the scenarios, i.e., an indication of the solution robustness. It is calculated by fuzzifying the discrete decisions over a specifi...
we can understand how people communicate with each other and how the information spreads in social networks. Naturally, when defining similarity, we should take the influence analysis into account and the similarity measure should be multi-dimensional. Therefore, our design is based on the following...