JCDL 2016 Doctoral Consortium - Web Archive Profiling

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Information about JCDL 2016 Doctoral Consortium - Web Archive Profiling

Published on June 28, 2016

Author: ibnesayeed

Source: slideshare.net

1. Web Archive Profiling For Efficient Memento Aggregation Sawood Alam Old Dominion University, Norfolk, Virginia - 23529 Advisor: Michael L. Nelson Doctoral Consortium JCDL’16 June 19, 2016 Supported in part by the International Internet Preservation Consortium (IIPC)

2. Motivation

3. Motivation

4. Motivation

5. Memento Aggregator

6. Memento Aggregator

7. Memento Aggregator

8. Memento Aggregator

9. Memento Aggregator

10. Memento Aggregator

11. From: Michael Nelson [mailto:mln@cs.odu.edu] Sent: Wednesday, December 02, 2015 12:33 PM To: Jones, Gina Cc: Rourke, Patrick; Grotke, Abigail Subject: Re: WebSciDL Hi Gina, I'll investigate. memgator is software that one my students wrote, but I suspect the traffic you're seeing is b/c it is deployed in http: //oldweb.today/ can you share the IP addr from where you're seeing the traffic? I presume the requests are for Memento TimeMaps? It should not being actually scraping HTML pages. regards, Michael On Wed, 2 Dec 2015, Jones, Gina wrote: > Hi Michael, we have a slight configuration issue with the current OW > set up for our webarchives. I think, from looking at the logs, that > "MemGator:1.0-rc3 <@WebSciDL>" is really causing some issues on our wayback. > Do you know who is running this scraper? Itʼs not part of memento is it? > > Gina Jones > Web Archiving Team > Library of Congress From: Ilya Kreymer <ikreymer@gmail.com> Date: Wed, 2 Dec 2015 10:33:56 -0800 Subject: high traffic on oldweb! To: Herbert Van de Sompel <hvdsomp@gmail.com>, Sawood Alam <ibnesayeed@gmail.com> Hi Herbert, Sawood, Herbert: Perhaps you are lucky that I am not using the LANL aggregator, as the traffic has gotten really high, and also I was asked to remove an archive due to the traffic it was causing temporarily.. I am thinking that ability to remove source archives quickly is an important aspect of an aggregator. Sawood: Hopefully yours will support something like this so I don't need to restart the container to change the archivelist ;) Ilya Broadcasting is Bad

12. Availability and Overlap ● Archives are sparse ● Broadcasting is wasteful, both clients and archives suffer

13. Memento Routing

14. Routing Pros & Cons ● Pros ○ Minimizes traffic and resources consumption ○ Improves throughput ● Cons ○ Upfront profile maintenance cost ○ May miss Mementos (false negatives)

15. Why Small Archives Matter?

16. Why Small Archives Matter? ● 400B+ web pages at IA do not cover everything ● Top three archives after IA produce full TimeMap 52% of the time (AlSum et al, TPDL 2013) ● Targeted crawls ● Special focus archives ● Restricted resources ● Private archives ● Censorship

17. While the IA was Down... $ memgator -f cdxj example.org | cut -c-4 | grep -v "^@" | uniq -c 2 2002 1 2005 1 2008 6 2009 67 2010 17 2011 64 2012 108 2013 108 2014 186 2015 51 2016

18. Research Questions ● What do individual web archives hold? ● How much do we need to know about an archive’s holdings? ● What is the optimal level of summarization for better accuracy and increased freshness? ● What are various ways to learn about archives’ holdings? ● How to store and update archives’ profiles to efficiently scale?

19. Archive Profile ● High-level summary of an archive ● Predicts presence of mementos of a URI-R in an archive ● Provides various statistics about the holdings ● Small in size ● Publicly available ● Easy to update and partially patch ● Useful for Memento query routing and other things

20. Profiling Policies ● Complete URI-R Profiling (1 URI-R = 1 Profile Key) ○ bbc.co.uk/images/logo.png?w=90 ○ cnn.com/2014/03/15/?id=128734 ● TLD-only Profiling (1 TLD = 1 Profile Key) ○ com)/ ○ uk)/ ● Middle Ground ○ uk,co)/ ○ uk,co,bbc)/images ○ uk,co,bbc)/0/2/1 ○ com,cnn)/ 201309 ar

21. Available Profiling Resources Client request Archive Response CDX Records

22. Profiling Strategies ● CDX Profiling ● Fulltext Search Profiling ● Sample URI Profiling ● Response Cache Profiling

23. Sample Profile

24. Probability Rank

25. Archives Archive URI-Rs URI-Ms Index Size Archive-It 1.9B 5.3B 1.8TB UKWA 0.7B 1.7B 0.5TB Stanford 12M 25M 8.3GB

26. Sample Query Sets Sample (1M URIs Each) In Archive-It In UKWA In Stanford Union {AIT, UK, SU} DMOZ 4.097% 3.594% 0.034% 7.575% MementoProxy 4.182% 0.408% 0.046% 4.527% IAWayback 3.716% 0.519% 0.039% 4.165% UKWayback 0.108% 0.034% 0.002% 0.134%

27. Evaluation ● Generate profiles with 23 policies ● Relate CDX Size, URI-M, URI-R, and URI-Key ● Analyze profile growth ● Estimate Relative Cost ● Evaluate Routing Efficiency

28. Resource Requirement

29. CDX Size vs URI-M (UKWA 10 Years) Alpha: 175 bytes per CDX line

30. URI-M vs URI-R (UKWA 10 Years) Gamma: 2.46 K : 2.686 Beta: 0.911

31. Space Cost (UKWA 7 Years) Phi: 8.5e-07 -- 0.70583

32. Time Cost (UKWA 7 Years) Tau: 5.7e-05 -- 6.2e-05 CDX: 45GB URI-Ms: 181M URI-Rs: 96M Time: 3 hours

33. Archive-It

34. Fulltext Search Cost

35. Partial Knowledge

36. Cost vs Accuracy Group Policies Cost Accuracy G1 H1P0/TLD Bound by # of TLDs ≈ 0.01 G2 H3P0, DDom, DSub, DPth, DQry < 0.01 ≈ 0.78 G3 DIni ≈ 2 * G2 ≈ 0.88 G4 HxP1 ≈ 5 * G3 ≈ 0.94 G5 Higher HmPn 0.4 -- 0.7 Not Explored G6 URIR 1.0 1.0

37. Work Plan ✓ Baseline Profiling Through CDX Files ✓ Profile Serialization ✓ Fulltext Search Profiling ✓ Sample URI Dataset ➢ Instrumenting Memento Aggregator ➢ Multidimensional Profiling

38. Publications TPDL15 Web Archive Profiling Through CDX Summarization TCDL15 Profiling Web Archives - For Efficient Memento Query Routing IJDL16 Web Archive Profiling Through CDX Summarization JCDL16 Poster: MemGator - A Portable Concurrent Memento Aggregator TPDL16 Web Archive Profiling Through Fulltext Search RFC Object Resource Stream (ORS) and CDX-JSON (CDXJ) Formats C4LJ MemGator - A Portable Concurrent Memento Aggregator Architecture JCDL17 Scalable, Maintainable, and Extensible Web Archive Profile Serialization for Efficient Lookup JCDL17 URI, Time, and Language Profiling from Live Archives via URI Sampling and Fulltex Search SIGIR17 Memento Aggregator Routing Based on Probability Distribution of Memento Availability with Archive Profiles IJDL17 Archive X-Ray - Web Archive Profiling for Efficient Memento Aggregation

39. Future Work ● Language profiles ● Evaluation of combination profiles such as URI-Key along with Datetime ● Utilize archive profile to generate rank ordered list of archive ● Profiles for usage other than Memento routing, such as, site classification based profiles (e.g., news, wiki, social media, blog etc.)

40. Conclusions ● Generated profiles with different policies for three archives ● Examined cost-precision tradeoffs of various policies ● Related CDX Size, URI-M, URI-R, and URI-Key ● Gained up to 80% routing accuracy with <1% relative cost while maintaining 0.9 recall

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