Abstracting PageRank To Dynamic Asset Valuation


  1. Sawilla, R.
Corporate Authors
Defence R&D Canada - Ottawa, Ottawa ONT (CAN)
We present a method that quickly and dynamically calculates a relative value for all assets in an organization in any context in which dependencies may be specified. The idea is a novel application of the Google PageRank algorithm that extends it to all assets and all contexts. In fact, web pages become a special case of asset ranking in a functionality context. Additionally, our algorithm provides the capability to specify individual dependency weights that one asset has upon another and individual intrinsic values for each asset. An asset category dependency model is proposed and entity-relationship structures are given to assist in continued development. Our scheme works in general and will provide asset valuation in any context, be it confidentiality, integrity, availability, or even political capital. In this document we combine the idea of asset dependency with an established web page ranking technique. Google’s PageRank algorithm is generalized in two key areas, creating an algorithm we call Asset-Rank. It calculates a relative importance ranking for every asset in the organization from information to tanks to partners. The ranking will assist decision makers by highlighting which assets are the most highly depended upon by the organization.

Il y a un résumé en français ici.

Report Number
DRDC-OTTAWA-TM-2006-243 — Technical Memorandum
Date of publication
01 Dec 2006
Number of Pages
Electronic Document(PDF)

Permanent link

Document 1 of 1

Date modified: