Google's research has explored methods for estimating the information gain from web page links in a more contextual manner, rather than relying solely on simple link counts or PageRank.
The key ideas include:
- Link Context Analysis: Analyzing the textual context surrounding a link (e.g. the anchor text, surrounding sentences) to better understand the relevance and value of that link, rather than just the raw link count.
- Link Quality Scoring: Developing algorithms to score the quality and informativeness of individual links, based on factors like link context, source authority, etc. This allows weighting links by their estimated value.
- Personalized Link Weighting: Accounting for a user's interests and browsing history to personalize the estimated information gain from different links. Links more relevant to a user's context would be weighted higher.
- Temporal Link Dynamics: Analyzing how the value and relevance of links changes over time, as pages and content are updated. Recent, fresh links may be weighted more heavily.
- Topical Link Relationships: Understanding how links relate to the broader topical context of a page, not just the immediate textual context. Links that fit the page's topical focus would be weighted higher.
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