Uncovering the unarchived web

htmlabstractMany national and international heritage institutes realize the importance of archiving the web for future culture heritage. Web archiving is currently performed either by harvesting a national domain, or by crawling a pre-defined list of websites selected by the archiving institution. In either method, crawling results in more information being harvested than just the websites intended for preservation; which could be used to reconstruct impressions of pages that existed on the live web of the crawl date, but would have been lost forever. We present a method to create representations of what we will refer to as a web collection's (aura): the web documents that were not included in the archived collection, but are known to have existed --- due to their mentions on pages that were included in the archived web collection. To create representations of these unarchived pages, we exploit the information about the unarchived URLs that can be derived from the crawls by combining crawl date distribution, anchor text and link structure. We illustrate empirically that the size of the aura can be substantial: in 2012, the Dutch Web archive contained 12.3M unique pages, while we uncover references to 11.9M additional (unarchived) pages

Uncovering the unarchived web

Many national and international heritage institutes realize the importance of archiving the web for future culture heritage. Web archiving is currently performed either by harvesting a national domain, or by crawling a pre-defined list of websites selected by the archiving institution. In either method, crawling results in more information being harvested than just the websites intended for preservation; which could be used to reconstruct impressions of pages that existed on the live web of the crawl date, but would have been lost forever. We present a method to create representations of what we will refer to as a web collection's (aura): the web documents that were not included in the archived collection, but are known to have existed --- due to their mentions on pages that were included in the archived web collection. To create representations of these unarchived pages, we exploit the information about the unarchived URLs that can be derived from the crawls by combining crawl date distribution, anchor text and link structure. We illustrate empirically that the size of the aura can be substantial: in 2012, the Dutch Web archive contained 12.3M unique pages, while we uncover references to 11.9M additional (unarchived) pages

Dynamic Collective Entity Representations for Entity Ranking

Entity ranking, i.e., successfully positioning a relevant entity at the top of the ranking for a given query, is inherently difficult due to the potential mismatch between the entity's description in a knowledge base, and the way people refer to the entity when searching for it. To counter this issue we propose a method for constructing dynamic collective entity representations. We collect entity descriptions from a variety of sources and combine them into a single entity representation by learning to weight the content from different sources that are associated with an entity for optimal retrieval effectiveness. Our method is able to add new descriptions in real time and learn the best representation as time evolves so as to capture the dynamics of how people search entities. Incorporating dynamic description sources into dynamic collective entity representations improves retrieval effectiveness by 7% over a state-of-the-art learning to rank baseline. Periodic retraining of the ranker enables higher ranking effectiveness for dynamic collective entity representations

Using the Web Infrastructure for Real Time Recovery of Missing Web Pages

Given the dynamic nature of the World Wide Web, missing web pages, or 404 Page not Found responses, are part of our web browsing experience. It is our intuition that information on the web is rarely completely lost, it is just missing. In whole or in part, content often moves from one URI to another and hence it just needs to be (re-)discovered. We evaluate several methods for a \justin- time approach to web page preservation. We investigate the suitability of lexical signatures and web page titles to rediscover missing content. It is understood that web pages change over time which implies that the performance of these two methods depends on the age of the content. We therefore conduct a temporal study of the decay of lexical signatures and titles and estimate their half-life. We further propose the use of tags that users have created to annotate pages as well as the most salient terms derived from a page\u27s link neighborhood. We utilize the Memento framework to discover previous versions of web pages and to execute the above methods. We provide a work ow including a set of parameters that is most promising for the (re-)discovery of missing web pages. We introduce Synchronicity, a web browser add-on that implements this work ow. It works while the user is browsing and detects the occurrence of 404 errors automatically. When activated by the user Synchronicity offers a total of six methods to either rediscover the missing page at its new URI or discover an alternative page that satisfies the user\u27s information need. Synchronicity depends on user interaction which enables it to provide results in real time