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Authority flow techniques like PageRank and ObjectRank can provide personalized ranking of typed entity-relationship graphs. There are two main ways to personalize authority flow ranking: Node-based personalization, where authority originates from a set of user-specific nodes; Edge-based personalization, where the importance of different edge types is user-specific. The authors propose for the first time an approach to achieve efficient edge-based personalization using a combination of precomputation and runtime algorithms. In particular, they apply their method to the personalized authority flow bounds of ObjectRank, i.e., a Weight Assignment Vector (WAV) assigns different weights to each edge type or relationship type.
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