On near-uniform URL sampling

By Monika Henzinger, Allan Heydon, Michael M. Mitzenmacher, Marc Najork. Comput. Networks, 2000

294 citations recorded by the source corpus.

Subfields: Information Systems, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/cf52296ddd05ee6c7f6bab0d7cdf740e6862ed7a

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In Information Systems

In Statistical and Nonlinear Physics

Citations in the corpus

Towards Scaling Fully Personalized PageRank: Algorithms, Lower Bounds, and Experiments (2005, methodology): “…al. 02] Random walks were used earlier to compute various web statistics, mostly focused on sampling the web (uniformly or according to static PR) [Henzinger et al. 00, Rusmevichientong et al. 01, The lower bounds of Section 4 show that precise PPR requires a signiﬁcantly larger database than…”
Walking in Facebook: A Case Study of Unbiased Sampling of OSNs (2010, methodology): “They have been used for sampling the Web [15], P2P networks [8], [16], [17], and other large graphs [18].”
Breadth-first crawling yields high-quality pages (2001, background): “In other words, Google — which, according to a recent measurement [6], has the greatest coverage of all search engines — covers only about 0.”
LinkBERT: Pretraining Language Models with Document Links (2022, methodology): “To adjust so that all documents appear with a similar frequency in training, we sample a linked document with probability inversely proportional to its in-degree, as done in graph data mining literature (Henzinger et al., 2000).”
Estimating and sampling graphs with multidimensional random walks (2010, background): “In networks that cannot be crawled (e.g., the Internet topology), samples must be obtained along shortest paths, and vertex degrees cannot be queried, [1] shows that observed vertex degrees are biased.”
Detecting Automation of Twitter Accounts: Are You a Human, Bot, or Cyborg? (2012, methodology): “Inspired by [32], [33], we randomly select five users as seeds.”
Design and implementation of a high-performance distributed Web crawler (2002, background): “Random Walking and Sampling: Several techniques have been studied that use random walks on the web graph (or a slightly modified graph) to sample pages or estimate the size and quality of search engines [3, 15, 14].”
Topical locality in the Web (2000, background): “As a result, the unbiased selection of a random subset of the Web is an open question [BB98], although some progress is being made [ HHMN00 ].”
When Social Influence Meets Item Inference (2015, background): “s, together with their neighbors, are more likely to be sampled. On the other hand, since no user IDs are provided by an OSN, uniform sampling by testing if a random number corresponding to a user ID [14, 16] tends to involve a large number of trials [13] when the number of users is much smaller tha”
Review of "Mining the Web: discovering knowledge from hypertext data" by Soumen Chakrabati. Morgan Kaufman 2003. (2002, unknown): “Henzinger and others [99] propose to use the “random surfer” notion underlying PageRank (see §7.”
Who is tweeting on Twitter: human, bot, or cyborg? (2010, methodology): “Inspired by [15, 18], we randomly select five users as seeds.”