datawarehousing資料倉儲(編輯修改稿)
2024-11-17 16:03 本頁面
【文章內(nèi)容簡介】 uick access to other entities in a work. – Has a short path to other entities. – Is close to other entities. – Has high visibility as to what is happening in the work. 12 Source: Social Network Analysis: Eigenvalue 13 Source: Alice and Rafael are closer to other highly close entities in the work. Bob and Frederica are also highly close, but to a lesser value. Social Network Analysis: Eigenvalue ? Eigenvalue measures how close an entity is to other highly close entities within a work. In other words, Eigenvalue identifies the most central entities in terms of the global or overall makeup of the work. ? A high Eigenvalue generally: – Indicates an actor that is more central to the main pattern of distances among all entities. – Is a reasonable measure of one aspect of centrality in terms of positional advantage. 14 Source: Social Network Analysis: Hub and Authority 15 Source: Hubs are entities that point to a relatively large number of authorities. They are essentially the mutually reinforcing analogues to authorities. Authorities point to high hubs. Hubs point to high authorities. You cannot have one without the other. Social Network Analysis: Hub and Authority ? Entities that many other entities point to are called Authorities. In Sentinel Visualizer, relationships are directional—they point from one entity to another. ? If an entity has a high number of relationships pointing to it, it has a high authority value, and generally: – Is a knowledge or anizational authority within a domain. – Acts as definitive source of information. 16 Source: Social Network Analysis 17 Source: Social Network Analysis 18 Source: Social Network Analysis 19 Source: Link Mining 20 Link Mining (Getoor amp。 Diehl, 2020) ? Link Mining – Data Mining techniques that take into account the links between objects and entities while building predictive or descriptive models. ? Link based object ranking, Group Detection, Entity Resolution, Link Prediction ? Application: – Hyperlink Mining – Relational Learning – Inductive Logic Programming – Graph Mining 21 Source: (c) Jaideep Srivastava, , Data Mining for Social Network
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