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How To Evaluate The Whole Web
(Without being Google)
@Majestic
The BIG Specialist Search Engine
Twitter has 500,000,000
Tweets per day on average
In the same day, Majestic
crawls 7,000,000,000 URLs (and 3
billion of these are “new”)
@Majestic
How Do We Collect That Much Data?
@Majestic
How Do We Collect That Much Data?
@Majestic
How Do We Collect That Much Data?
@Majestic
How we ANALYZE links to get CF/TF
Topical Trust
Flow using
decay
Algorithm
???
@Majestic
Works best with Universal Data set
• Every signal is small
• Individually prone to
error or opinion
• At scale the error
decreases
• Confidence increases
http://info.majestic.com/universal
@Majestic
Jon M. Kleinberg, Cornell University 1999
Hub
Hub
Hub
Authority
Authority
Authority
Authority
Authority
Authority
Authority AuthorityAuthority
In Penguin, Google Muted
the Hubs!
Knowledge
Graph
@Majestic
The Next Hard Part of Search
Information Retrieval in
the “Zeta” age;
1.Data Collection
2.Data Grouping
3.Data Indexing
4.Data Matching
@Majestic
Groups Make Search Much Better
• Find a Fact
• Find a Friend
• Find a Customer
• Find Anything
LibraryofCongresscirca1940
Research At: info.majestic.com/groupresearch
@Majestic
Why Categorize the Web?
• Categorizing into topics prevents spam:
• http://maj.to/1yZOdW5 (TrustRank Paper)
http://maj.to/1Bb1lHu (Stanford Paper)
@Majestic
Categorisation by Data Type
• Country IP/TLD
• Image Search
• Video Search
• Local Listings
• Maps
• Travel
@Majestic
Approaches to Defining Topics
@Majestic
Approaches to Defining Topics
@Majestic
How We Categorize the Web
• Content connects in
Groups
• Keywords gravitate
into Groups
@Majestic
We See AND ANALYZE Links
Topical Trust
Flow using
decay
Algorithm
???
@Majestic
MIT=Reference
MIT.edu’s Link Network
Source: Labs.majestic.com
Reference
News Arts & Society
Spam?Reference
@Majestic
MIT=Reference/Education
@Majestic
800 Topics
In 15 Super
Categories
@Majestic
Topical Trust Flow is Very Powerful
• More granular than (say) PageRank
• Updates continually
• Provides measurable context and influence at scale
• Page level AND site level tracking
• 800 topics
• Can compare all types of online data (People, Pages,
Sites, Images, Plugins)
@Majestic
Use Cases
• Already used in Search
• Finding Influencers
• Credit checking
• Comparing different media channels
• Link building
• Company evaluations
@Majestic
Who is more popular on Twitter?
Use case: Finding influencers
Lady Gaga? Barack Obama?
Trust Flow
74
Trust Flow
70
@Majestic
Let’s go and see Topical
Pagerank in Action
@Majestic
Example: Credit Cards
@Majestic
Example: “Majestic” (Low correlation)
@Majestic
Example: “the whitehouse”
@Majestic
Takeaways
• Search Results are stronger if sites are categorized first
• Google has suggested their engineers have worked on
“Topical Page Rank”
• There are correlations between rankings and topics
Strategies:
• Build content around topical themes to create hubs of
authority or
• Change brand awareness around the keyword
@Majestic
Out of Trust Flows
understanding
Real insight into the world wide web from
Majestic,the specialist search engine

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How to evaluate the whole web (without being Google)

Editor's Notes

  1. ***** GO SLOWLY ****
  2. Imagine going into a Library to find the weight of the moon. How much harder would your search be if the books were in alphabetical order only?
  3. Google do this – by separating entire data sets. Each set has its own (structured) data formats. Does not solve the problem of Contextual categorization.