The document provides an overview of how to specify crawls using the ARCOMEM crawler cockpit. It begins with an introduction to how the web works and key concepts like HTTP, HTML, URLs, and domains. It then describes the different components of the ARCOMEM crawler system including the Memory Bot crawler, Adaptive Heritrix, API Crawler, and Application Aware Helper. The document concludes by explaining the functionality of the ARCOMEM Crawler Cockpit user interface, which allows users to launch, monitor, and export crawls by focusing on keywords, entities, URLs or social media categories.

1. Specifying crawls
France Lasfargues
Internet Memory Foundation
Paris, France
france.lasfargues@internememory.net
Slide 1

2. Training Goals
➔ Help user to specify properly the campaign
➔ Make user understanding what it is going on in
the back end of the ARCOMEM platform
➔ Set-up a campaign in the crawler cockpit
Slide 2

3. Plan
What is the Web ? Challenges and SOA
ARCOMEM platform
Crawler
Set-up a campaign in the Arcomen Crawler
Cockpit
Slide 3

4. Introduction : How does web work ?
➔ The web is managed by protocols and standards :
• HTTP Hypertext Transfer Protocol
• HTML HyperText Markup Language
• URL Uniform Resource Locator
• DNS Domain Name System
➔ Each server has an address : IP address
• Example : http://213.251.150.222/ ->
http://collections.europarchive.org
4

5. WWW
The web is a large space of communication and information :
• managed by servers which talk together by convention (protocol) and
through applications in a large network.
• a naming space organized and controlled (ICANN)
 World Wide Web: abbreviated as WWW and commonly known
as the Web, is a system of interlinked hypertext documents
accessed via the internet
Slide 5

6. HTTP - Hypertext Transfer Protocol
➔ Notion client/server
•
request-response protocol in the client-server computing model
➔ How does it work ?
•
•
Server hosts the content and delivers it
•
6
Client asks for a content
The browser locates the DNS server, connects itself to the
server and sends a request to the server.

7. HTML - HyperText Markup Languag e
➔ Markup language for Web page
➔ Written in form of HTML elements
➔ Creates structured documents denoting structural
semantic elements for text as headings, paragraphs,
titles, links, quotes, and other items
➔ Allows text and embedded as images
➔ Example : http://www.w3.org/
7

8. URI - URL
➔ URL - Uniform resource Locator (URL) that specifies
where an identified resource is available and the mechanism
for retrieving it.
➔ Examples :
– http://host.domain.extension/path/pageORfile
– http://www.europarchive.org
– http://collections.europarchive.org/
– http://www.europarchive.org/about.php
Samos 2013 – Workshop : The ARCOMEM Platform
8

9. Domain name and extension
➔ Manage by l’ICANN, Internet Corporation for Assigned Names and
Numbers (ICANN), is non profit organization, allocated by registrar.
•
http://www.icann.org
➔ ICANN coordinates the allocation and assignment to ensure the
universal resolvability of :
• Domain names (forming a system referred to as «DNS»)
• Internet protocol («IP») addresses
• Protocol port and parameter numbers.
➔ Several types of TLD
•
•
gTLD : aero, .biz, .coop, .info, .museum, .name, et .pro
•
9
TLD first level : .com, .info, etc
ccTLD (country code Top Level Domains).fr

10. What kind of contents?
➔ Different type of contents : multimedia text, video, images
➔ Different type of producers :
• public : institution, government, museum, TV....
• private : foundation, company, press, people, blog...
http://ec.europa.eu/index_fr.htm
http://iawebarchiving.wordpress.com/
http://www.nytimes.com/
➔ Each producer is in charge of its content
• Information can disappear: fragility
• Size
10

11. Social web
➔ Focus on people’s socialization and interaction
• Characteristics :
•
Walled space in which users can interact
• Creation of social network
➔ WEB ARCHIVE -> challenges in term of content, privacy
and technique.
•
Examples:
• Share bookmark(Del.icio.us, Digg), videos (Dailymotion,
YouTube), photos (Flickr, Picasa)
• community (MySpace, Facebook)
11

12. Ex. of technical difficulties: Videos
➔ Standard HTTP protocol
• obfuscated links to the video files
• dynamic playlists and channels or configuration files loaded
by the player several hops and redirects to the server of the
video content
e.g.: YouTube
➔ Streaming protocols: RTSP, RTMP, MMS...
• real-time protocols implemented by the video players suited
for large video files (control commands) or live broadcasts
• sometimes proprietary protocols (e.g.: RTMP - Adobe)
available tools: MPlayer, FLVStreamer, VCL
12

13. Deep /Hidden Web
• Deep web: content accessible behind
password, database, payment... and hidden
to search engine
http://c.asselin.free.fr/french/schema_webinvisible.htm Schema établit sur la base de la figure
"Distribution des sites du Deep Web par types de contenu" de l'étude Bright Planet.
13

14. How do we archive it ?
➔ Challenges for archiving :
– dynamic websites
➔ Technical barriers:
•
•
•
•
•
some javascript
animation on Flash
pop-up
video and audio on streaming
restricted access
➔Traps : Spam and loop
14

15. What do user need to do some web archiving ?
➔ Define the target content (Website, URL, Topic…)
➔ A tool to manage its campaign
➔ Intelligent crawler to archive content
15

16. Management tools (1)
Several tool exist already developed by Libraries which are doing some Library.
➔Netarchivesuite (http://netarchive.dk/suite/)
➔The NetarchiveSuite software was originally developed by the two national deposit
libraries in Denmark, The Royal Library and The State and University Library and has
been running in production, harvesting the Danish world wide web since 2005. The
French National Library and the Austrian National Libraries joined the project in 2008.
➔Web curator tool: http://webcurator.sourceforge.net
Open-source workflow management application for selective web archiving
developed by the National Library of New Zealand and the British Library, initiated
by the International Internet Preservation Consortium
➔Archive-it http://www.archive-it.org/
A subscription service by Internet Archive to build and preserve collections: allows
to harvest, catalogue, manage and browse archived collections
➔Archivethe.net http://archivethe.net/fr/
Service provides by the Internet Memory Foundation.
➔Arcomem crawler cockpit
16

17. How does a crawler work ?
➔ A crawler is a bot parsing web pages in order to index
or and archive them. Robot navigates following links
➔ Link in the center of crawl’s problematic
• Explicit links : source code is available and full path is
explicitly stated
• Variable link : source code is available but use
variables to encode the path
• Opaque links: source code not available
Example : http://www.thetimes.co.uk/tto/news/
17

18. Parameters
➔ Scoping function is used to define how depth the crawl
will go
• Complete or specific content of a website
• Discovery or focus crawl
➔ Politeness
• Follow the common rules of politeness
➔ Robots.txt
• Follow
➔ Frequency
• How often I want to launch a crawl on this target ?
18

19. Source code: http:/www.arcomem.eu/
!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd">
<html xmlns="http://www.w3.org/1999/xhtml" dir="ltr" lang="de-DE">
<head profile=http://gmpg.org/xfn/11>
<meta http-equiv="Content-Type" content="text/html; charset=UTF-8" />
<meta name="distribution" content="global" />
<meta name="robots" content="follow, all" />
<meta name="language" content="en" />
<meta name="bitly-verification" content="59eb4f9028ea"/>
<meta name="verify-v1" content="7XvBEj6Tw9dyXjHST/9sgRGxGymxFdHIZsM6Ob/xo5E=" />
<title> ARCOMEM</title>
• <div id="navbar">
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19

20. ARCOMEM Workflow
20

21. Memory Bot
• Component Name: IMF Large Scale Crawler
– The large scale crawler retrieves content from the web and
stores it in an HBase repository. It aims at being scalable:
crawling at a fast rate from the start and slowing down as
little as possible as the amount of visited URLs grows to
hundreds of millions, all while observing politeness
conventions (rate regulation, robots.txt compliance, etc.).
• Input:
– URLs with a score (seeds, then URLs output by the
analysis process)
• Output:
– Web resources written to WARC files. We also have
developed an importer to load these WARC files into
HBase. Some metadata is also extracted: HTTP status
code, identified out links, MIME type, etc.
21

22. WARC: example
22

23. Adaptative Heritrix
➔ Component Name: Adaptive Heritrix
➔ Description: Adaptive Heritrix is a modified version of the
open source crawler Heritrix that allows the dynamic
reordering of queued URLs and receiving URLs from the
Online Analysis module.
23

24. How does adaptative Heritrix work ?
➔ Prioritization module communicates new scores to the
crawler queue using a JSON over HTTP Prioritisation
module sends POST to http://QUEUE_SERVER/update.
The request body is a JSON encoded array of update
objects.
➔ {"url": "http://google.com/", "score": 0.3, "parentUrl":
"http://seed.tld/page"},
➔ {"url": "http://spam.net/", "blacklisted": true, "parentUrl":
"http://seed.tld/page"}
24

25. API Crawler
➔ Component Name: API Crawler
➔ Description:
•
The API Crawler is a solution to manage keyword-based crawls of
different social platforms using their Web APIs. It is controlled via
a RESTful Web interface. Scalability and Performance: 3000
requests per hour, millions of triples per hour, millions of links per
hour
➔ Input: List of tuples (keyword, platform)
➔ Output: Triples stored in the triple store and WARC files
stored in the HDFS
➔ Twitter restriction: 180 request /15mn one request is
one criteria. Each request give back 100 answers
25

26. How does API crawler work ?
➔ Principles: a crawler runs crawls. Each crawl has a crawl
ID assigned by the pipeline. The pipeline ensures crawl
IDs are unique. A crawl has four states: running, stopped,
being deleted, deleted. A crawl runs until it ends by itself
or until a stop order is received. Only a stopped crawl can
be deleted.
➔ The APCrawler produces three kind of data:
– semi-structured data stored as triples in the triple
store,
– outlinks sent to Heritrix or the IMF crawler,
– and WARC files saved in the file system, that will also
possibly be inserted into HBase.
26

27. Output: triples
27

28. ICS: Intelligent crawl specifications
28

29. Application Aware helper
➔ Component Name: Application-aware helper
– The goal of this software component is to make the
crawler aware of the particular kind of Web application
being crawled, in terms of general classification of
websites (wiki, social network, blog, web forum, etc.),
technical implementation (Mediawiki, Wordpress, etc.),
and their specific instances (Twitter, CNN, etc.).
➔ Input:
– HTML content as string, base URL, list of out-links
➔ Output:
– Augmented document (original text document and
structured objects extracted from web page) and
extracted links with score will be sent to ARCOMEM
framework module. Extracted semantic objects, crawling
actions, and out-links with score will also be stored in the
ARCOMEM database.
29

30. ARCOMEM Crawler
30

31. How does AAH work ?
➔ The application aware helper will be assisted with a knowledge base that
will help in recognizing a specific web application and related crawling
actions
➔ Since the knowledge base will grow and there will exist several detection
patterns for many web applications, we have to ensure the web
application detection module does not slow up the crawling process and
affect overall performance.
➔ To ensure scalability, after integration of the application aware helper with
the crawler, we have used the Yfilter system (a NFA based filtering
system) for efficient indexing of detection patterns in order to quickly find
the relevant Web application.
➔ Here each state is represented by XPath expression patterns and
common steps of the path expression are represented only once in a
structure. The introduction of Yfilter in the Web application detection
module improves the performance dynamically and now the system is well
synchronized with the other sub modules of crawling process.
31

32. ARCOMEM Crawler Cockpit

33. ARCOMEM Crawler Cockpit
• Requirements
described by
ARCOMEM user
partners (SWR – DW)
• Designed and
implemented by IMF
• A UI on top of the
ARCOMEM system
• Demo: Crawler cockpit
33

34. How does it work ?
34

35. Crawler Cockpit: Functionality
• Launch crawls following
scheduler specifications
• Monitor crawls and get realtime feedback on the
progress of the crawlers
• Run crawl with HTML Crawler
(Heritrix and IMF Crawler)
• Export the crawled content to
a WARC file
•
Set-up a campaign by focusing,
event, keyword, entity and URL
• Focus on target content in Social
Media Category (blog, forum,
video, photo...)
• Run crawl by using API crawler
(Twitter, Facebook, YouTube,
Flickr)
• Get a campaign overview with
qualified statistics
• Do some refinement at crawls
time to have a better focus on the
target content
• decide what content to archive
35

36. Crawler Cockpit Navigation
• Set-up: A campaign is described by an intelligent crawl
definition, which associates content target to crawl
parameters (schedule and technical parameters).
• Monitor tab give access to statistics provide by the crawler
at running time
• Overview: global dashboard on a campaign. The
information is organized following different topics: general
description of the campaign, metadata, current status, crawl
activity, statistics and analysis
• Inspector: A tool to have access into the content as it is
stored into Hbase.
• Report: specfications and parameters of a campaign
36

37. CC: Overview Tab
Global
dashboard
on
campaign:
• General description of the
campaign
• Crawl activity
• Keywords
• Statistics
• Refine Mode: User can give
more or less weight to a
keyword.
37
a

38. CC Set-up tab
•General description
•Distinct named entities
(e.g. person, geo location,
and organization),Time
period Free keywords and
Language
•A selection of up to nine
SMC (Social Media
Categories)
•Schedule: Each campaign
has a start and end date.
Frequency of the craw is
defined by choosing an
interval.
38

39. Focus on Scoping function
Domain: entire web site
http://www.site.com
Path: only a specific directory of
a website
http://www.site.com/actu
Sub domain:
http://sport.site.com
Page + context:
http://www.site.comhome.html
39

40. Focus on scheduler
Frequency: weekly, monthly, quaterly …
Interval: 1 to 9
Calendar: a campaign has a start date and
an end date.
40

41. CC Inspector Tab
Inspector tab allows user to
•Check the quality of the content
before indexing
•Access to the content (from
HBase), metadata and triples
directly related to a resource
•Browse a list of URLs ranked by
on-line analysis scores is
provided.
41

42. CC Monitor Tab
The Monitor tab gives real time
statistics on the running crawl.
42

43. Crawler cockpit demo
• Online demo
• Feedback
43