Browsing a highly connected information space: can natural language processing help?

With the continuous growth of information and its high connectivity, it is hard to follow only the relevant links and remain focused. This is true on the web, which has become a major source of information to learn about a topic, and it is also true in a research environment, where the amount of scientific material available electronically is forever increasing, making reading the published literature a difficult task. While reading a document, people often encounter a promising link (or citation), which they decide to follow, only to discover after a quick browse that the document is not relevant to their current needs. Often, people open the linked document into a new tabbed window to which they return later. In such cases, users usually have many tabs opened. When they finally get to the linked documents to read them, they sometimes wonder why they opened these documents in the first place.