Abstract

AbstractMost digital library resources and the Web more generally are dynamic and ever-changing collections of information. However, most of the tools that have been developed for interacting with Web and DL content, such as browsers and search engines, focus on a single static snapshot of the information. In this talk, I will present analyses of how web content changes over time, how people re-visit web pages over time, and how re-visitation patterns are influenced by user intent and changes in content. These results have implications for many aspects of search including crawling, ranking algorithms, result presentation and evaluation. I will describe a prototype that supports people in understanding how information they interact with changes over time, by highlighting what content has changed since their last visit. Finally, I will describe a new retrieval model that represents features about the temporal evolution of content to inform crawl policy and improve ranking.

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