Predictive Crawling for Commercial Web Content-Reference-Cited by-同舟云学术

Predictive Crawling for Commercial Web Content

Published:2019 Issue: Volume: Page:
ISSN:
Container-title:The World Wide Web Conference on - WWW '19
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Author:

Han Shuguang¹,Brodowsky Bernhard²,Gajda Przemek²,Novikov Sergey²,Bendersky Mike¹,Najork Marc¹,Dua Robin¹,Popescul Alexandrin¹

Affiliation:

1. Google, USA

2. Google, Switzerland

Publisher

ACM Press

Reference33 articles.

1. Martín Abadi, Paul Barham, Jianmin Chen, Zhifeng Chen, Andy Davis, Jeffrey Dean, Matthieu Devin, Sanjay Ghemawat, Geoffrey Irving, Michael Isard, 2016. Tensorflow: a system for large-scale machine learning.. In Proceedings of the 12th USENIX Symposium on Operating Systems Design and Implementation (OSDI '16), Vol. 16. 265-283.

2. Eytan Adar, Jaime Teevan, Susan T Dumais, and Jonathan L Elsas. 2009. The web changes everything: understanding the dynamics of web content. In Proceedings of the Second ACM International Conference on Web Search and Data Mining. ACM, 282-291.

3. Yossi Azar, Eric Horvitz, Eyal Lubetzky, Yuval Peres, and Dafna Shahaf. 2018. Tractable near-optimal policies for crawling. Proceedings of the National Academy of Sciences 115, 32(2018), 8099-8103.

4. Brian E Brewington and George Cybenko. 2000. How dynamic is the web? 1. Computer Networks 33, 1-6 (2000), 257-276.

5. Maria Carla Calzarossa and Daniele Tessera. 2015. Modeling and predicting temporal patterns of web content changes. Journal of Network and Computer Applications 56 (2015), 115-123.

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