Abstract
In many graph mining settings, measuring node proximity is a fundamental problem. While most of existing measurements are (implicitly or explicitly) designed for undirected graphs; edge directions in the graph provide a new perspective to proximity measurement: measuring the proximity from A to B; rather than between A and B. (See Figure 1 as an example). In this chapter, we study the role of edge direction in measuring proximity on graphs. To be specific, we will address the following fundamental research questions in the context of direction-aware proximity: 1. Problem definitions: How to define a directionaware proximity? 2. Computational issues: How to compute the proximity score efficiently? 3. Applications: How can direction-aware proximity benefit graph mining?.
| Original language | English (US) |
|---|---|
| Title of host publication | Encyclopedia of Data Warehousing and Mining |
| Subtitle of host publication | Second Edition |
| Publisher | IGI Global |
| Pages | 646-653 |
| Number of pages | 8 |
| ISBN (Electronic) | 9781605660110 |
| ISBN (Print) | 9781605660103 |
| DOIs | |
| State | Published - Jan 1 2008 |
| Externally published | Yes |
ASJC Scopus subject areas
- General Economics, Econometrics and Finance
- General Business, Management and Accounting
- General Computer Science
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