Improving Website Hyperlink Structure Using Server Logs

TL;DR

This paper presents a data-driven approach using server logs to automatically identify and suggest useful new hyperlinks for websites, improving navigation and reducing manual editing efforts.

Contribution

It introduces a novel method leveraging server logs to predict beneficial nonexistent links and formulates an efficient link placement algorithm under budget constraints.

Findings

Effective on Wikipedia, matching actual new links in revision history.

Applicable to other websites like Simtk with standard server logs.

Improves website navigation without manual link curation.

Abstract

Good websites should be easy to navigate via hyperlinks, yet maintaining a high-quality link structure is difficult. Identifying pairs of pages that should be linked may be hard for human editors, especially if the site is large and changes frequently. Further, given a set of useful link candidates, the task of incorporating them into the site can be expensive, since it typically involves humans editing pages. In the light of these challenges, it is desirable to develop data-driven methods for automating the link placement task. Here we develop an approach for automatically finding useful hyperlinks to add to a website. We show that passively collected server logs, beyond telling us which existing links are useful, also contain implicit signals indicating which nonexistent links would be useful if they were to be introduced. We leverage these signals to model the future usefulness of yet nonexistent links. Based on our model, we define the problem of link placement under budget constraints and propose an efficient algorithm for solving it. We demonstrate the effectiveness of our approach by evaluating it on Wikipedia, a large website for which we have access to both server logs (used for finding useful new links) and the complete revision history (containing a ground truth of new links). As our method is based exclusively on standard server logs, it may also be applied to any other website, as we show with the example of the biomedical research site Simtk.