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Table 2. Commonly used notations with explanations.
wherein, h(K)i denotes the vector representations of the user node i of layer K, h(K)j presents the vector representations of the user node j of layer K. The loss function of this component is formulated as follows:
TABLE 4
CrossRef Full Text | Google Scholar
CrossRef Full Text | Google Scholar
Luca, M., and Zervas, G. (2016). Fake it till you make it: reputation, competition, and yelp review fraud. Manage. Sci. 62, 3412–3427. doi: 10.1287/mnsc.2015.2304
Rayana, S., and Akoglu, L. (2015). "Collective opinion spam detection: bridging review networks and metadata," in Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD '15, Sydney, NSW, 985–994. doi: 10.1145/2783258.2783370
Shehnepoor, S., Togneri, R., Liu, W., and Bennamoun, M. (2021). Hin-RNN: a graph representation learning neural network for fraudster group detection with no handcrafted features. IEEE Trans. Neural Netw. Learn. Syst. doi: 10.1109/TNNLS.2021.3123876
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5, 2.
5, 3.
5, etc.
One of the most popular goals markets for betting is the over/under 2.
Over 0.
5 Goals Explained
5 goals in a match mean that 1 or more goals are required to win the bet, and 0 goals mean the bet loses.
The same applies to under 0.
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