Abstract: Techniques are described for ranking the relevance of electronic documents, such as web pages. An algorithm extracts keywords and recurring phrases from the anchor tag data in electronic documents to define a set of concepts. The algorithm then uses link, concept pairs to create nodes in a graph. In this graph, edges can represent both explicit and implicit conceptual links between nodes. By including conceptual data, the algorithm may model and utilize inter-concept relationships when using graph ranking algorithms. This may improve result accuracy by not only retrieving links which are more authoritative given a users' context, but also by utilizing a larger pool of web pages that are limited by concept-space, rather than keyword-space.