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Additional resources for Web Information Systems Engineering – WISE 2014: 15th International Conference, Thessaloniki, Greece, October 12-14, 2014, Proceedings, Part I
Sample text
The average number of outliers for the median is considerably larger when compared with the push attack, while those required for the slotted aggregators are slightly smaller and, all in all, similar to those of the simple mean (similarly to above, the first column lists the outliers only for those hotels for which it was possible to alter the ranking). The no-win ratio, instead, varies noticeably: it is slightly smaller for the weekly slotted median, but almost doubled for the monthly slotted median.
Formally, given item attribute space SO =< O, A, V, g >, the Coupled Item Similarity (CIS) between two items oi and oj is defined as follows. J CIS(oi , oj ) = δkA (Vik , Vjk ) (6) k=1 where Vik and Vjk are the values of attribute j for items oi and oj , respectively; and δkA is Coupled Attribute Value Similarity. From this definition, we clearly see that the intra-couplings between values within an attribute and inter-couplings between attributes are incorporated for measuring item coupling which partly helps to uncover the intrinsic relations within items rather than considering them independently.
Item Couplings in Recommender Systems In order to capture the implicit item coupling and disclose the “iid” assumption, we first introduce several basic concepts as follows. |gj (y)| (1) where gj (x) = {oi |Vij = x, 1 ≤ j ≤ M, 1 ≤ i ≤ n} is the subset of O with corresponding attribute Aj having attribute value x, and |gj (x)| is the size of the subset. The influence of attribute value y of attribute Ak for attribute value x of attribute Aj can be calculated by: |gj,k (x, y)| Pj|k (y|x) = (2) |gj (x)| where gj,k (x, y) = {oi |(Vij = x) ∧ (Vik = y), 1 ≤ j, k ≤ M, 1 ≤ i ≤ n}.