AIMar 6, 2013
Inference Algorithms for Similarity Networks
arXiv:1303.1493v21 citations
Originality Synthesis-oriented
AI Analysis
This work addresses inference challenges in similarity networks, but it appears incremental as it builds on existing network types with algorithmic improvements.
The paper tackles the problem of inference in similarity networks by presenting efficient algorithms for two network types, with one algorithm requiring no restrictions but being less efficient.
We examine two types of similarity networks each based on a distinct notion of relevance. For both types of similarity networks we present an efficient inference algorithm that works under the assumption that every event has a nonzero probability of occurrence. Another inference algorithm is developed for type 1 similarity networks that works under no restriction, albeit less efficiently.