Intelligence Semantics

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By J.C. Catford

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Each relation customer × product and user × item × tag can be written as a tensor. For the tagging scenario, the slices of the cube have been written next to each other. e. s : X → {0, 1}. 5) If for all instances x : s(x) ≤ 1 then with this transformation no information is lost and we can use sets instead of functions. 1 shows an example for observed data in the online shopping and tagging scenario. 1(a), the first customer has bought the second and third products whereas the second customer has bought the first and last product, etc.

E. ds (c, xi , x j ) > 0), computing the full gradient in each update step is not feasible for mid to large scale problems. Furthermore, for optimizing BCR-O PT with full gradient descent also the skewness in the training pairs leads to poor convergence. Imagine one instance xi ∈ Xm that is often positive. Then we have many terms of the form yˆc,xi in the loss because for many different context c, xi is compared against all negative instances x j ∈ Xm (the dominating class). Thus the gradient for model parameters depending on xi would dominate largely the gradient.

56). : Empirical analysis of predictive algorithms for collaborative filtering. In: Proceedings of the Fourteenth Conference on Uncertainty in Artificial Intelligence (UAI 1998), pp. 43–52. : Evaluating evaluation measure stability. In: SIGIR 2000: Proceedings of the 23rd Annual international ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 33–40. : Measuring classifier performance: a coherent alternative to the area under the roc curve. : Compound classification models for recommender systems.

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