Graph Theory #searchlove The theory that underpins how all search engines work @kelvinnewman

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At #searchlove I spoke about Graph Theory which is a theory that underpins how all the search engines work.

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Graph Theory #searchlove The theory that underpins how all search engines work @kelvinnewman

  1. 1. LINK SOCIAL GRAPH graph GRAPH theory ! The theory that underpins how all search KNOWLEDGE work engines ETC. GRAPH @kelvinnewman
  2. 2. Graph Theory The most important theory in search that nobody talks about Kelvin Newman @kelvinnewman JD Hancock
  3. 3. Organiser BrightonSEO / Content Marketing Show / MeasureFest Three Free (and awesome) Conferences
  4. 4. Strategy Director SiteVisibility A digital agency specialising in retail, travel and financial services
  5. 5. Co-Founder Clockwork Talent Decent Digital Recruitment
  6. 6. shhhhh! JD Hancock
  7. 7. JD Hancock I might get in trouble for this JD Hancock
  8. 8. I’ve been let into a secret future beta of Google, and I’m going to reveal it to you
  9. 9. Joking aside; I think FB GraphSearch is a great indicator of the future of G JD Hancock
  10. 10. as it helps us better understand one of the theories that underlies all search engines JD Hancock
  11. 11. graph theory !
  12. 12. graph theory ! Hugely Important
  13. 13. graph theory ! Rarely Spoken About
  14. 14. LINK GRAPH
  15. 15. LINK GRAPH SOCIAL GRAPH
  16. 16. LINK GRAPH KNOWLEDGE GRAPH SOCIAL GRAPH
  17. 17. LINK GRAPH SOCIAL GRAPH KNOWLEDGE GRAPH OPEN GRAPH
  18. 18. LINK GRAPH SOCIAL GRAPH KNOWLEDGE GRAPH SORT OF
  19. 19. LINK GRAPH SOCIAL GRAPH KNOWLEDGE GRAPH ETC.
  20. 20. LINK SOCIAL GRAPH graph GRAPH theory ! ETC. Hugely Important KNOWLEDGE GRAPH
  21. 21. but we’ve been distracted, from what our job really is
  22. 22. which is understanding how the search engines fundamentally work jronaldlee
  23. 23. LINK SOCIAL GRAPH graph GRAPH theory KNOWLEDGE is central to that GRAPH ! understanding ETC.
  24. 24. this presentation may contain maths Benson Kua
  25. 25. hartjeff12
  26. 26. Will Critchlow Maths MA - University of Cambridge will - cambridge maths Dana Lookadoo - Yo! Yo! SEO
  27. 27. Tom Anthony PhD Artificial Intelligence University of Hertfordshire
  28. 28. Kelvin Newman Media Studies University of Sussex
  29. 29. I’m no computer scientist or mathematician jlwo
  30. 30. graph theory ! “a mathematical model for any system involving a binary relation” Frank Harary, 1969
  31. 31. “perhaps even more than to the contact between mankind and nature, graph theory owes to the contact of human beings between each other” Dénes König, 1936
  32. 32. http://www.slideshare.net/digitalmethods/gephi-rieder-23834788
  33. 33. Vertices or Nodes dominicotine
  34. 34. edges Matt Seppings
  35. 35. Nodes are Nouns
  36. 36. Edges are Verbs
  37. 37. basic graph visualisation
  38. 38. This Graph is Isomorphic of the other one, aka it’s the same but looks different
  39. 39. Matrix view of graph V1 V1 V2 V3 V4 V5 V6 V2 V3 V4 V5 V6
  40. 40. Matrix view of graph V1 V1 V2 V3 V4 V5 V6 0 V2 V3 V4 V5 V6
  41. 41. Matrix view of graph V1 V1 V2 V3 V4 V5 V6 V2 0 1 V3 V4 V5 V6
  42. 42. Matrix view of graph V1 V1 V2 V3 V4 V5 V6 V2 V3 V4 0 1 1 1 V5 V6
  43. 43. Matrix view of graph V1 V1 V2 V3 V4 V5 V6 V2 V3 V4 V5 V6 0 1 1 1 0 0
  44. 44. Matrix view of graph V1 V2 V3 V4 V5 V6 V1 0 1 1 1 0 0 V2 1 0 V3 V4 V5 V6
  45. 45. Matrix view of graph V1 V2 V3 V4 V5 V6 V1 0 1 1 1 0 0 V2 1 0 0 0 0 0 V3 1 0 0 0 0 0 V4 V5 V6
  46. 46. Matrix view of graph V1 V2 V3 V4 V5 V6 V1 0 1 1 1 0 0 V2 1 0 0 0 0 0 V3 1 0 0 0 0 0 V4 1 0 0 0 1 0 V5 0 0 0 1 0 1 V6 0 0 0 0 1 0
  47. 47. Or maybe? Blogger 1 Blogger 2 Blogger 3 Blogger 4 Blogger 5 Blogger 6 Blogger1 0 1 1 1 0 0 Blogger 2 1 0 0 0 0 0 Blogger 3 1 0 0 0 0 0 Blogger 4 1 0 0 0 1 0 Blogger 5 0 0 0 1 0 1 Blogger 6 0 0 0 0 1 0
  48. 48. Cardinality is the number of Nodes or Vertices in a Graph Prayitno/
  49. 49. Degrees of Vertex is how many edges a vertex has. chedder
  50. 50. Trees & Circuits Our Graph here is known as a tree, because you can’t loop back on yourself. If you could loop back on yourself it would be known as a circuit This is interesting to think about in the context of your site, or an area of the link graph
  51. 51. Watch PatrickJMT’s Graph Theory Videos http://patrickjmt.com/graph-theory-an-introduction/
  52. 52. What’s the first thing you teach your team? http://i.imgur.com/PGE2D2n.gif
  53. 53. For me it is PageRank http://computationalculture.net/article/what_is_in_pagerank
  54. 54. Jim Seward is a legend http://computationalculture.net/article/what_is_in_pagerank
  55. 55. What is PageRank? http://i.imgur.com/aNXqGNT.gif
  56. 56. A set of rules which can be used to give a numerical weighting to assess the importance of document within linked data set
  57. 57. A set of rules which can be used to give a numerical weighting to assess the importance of nodes document within linked data set
  58. 58. it is not
  59. 59. PageRank is used for than the Algo natalielucier
  60. 60. Understand Lung Cancer http://www.news-medical.net/news/20130326/Algorithm-similar-to-Google-PageRank-helps-map-spread-of-lung-cancer.aspx jasleen_kaur
  61. 61. Rank Scientific Significance http://bulib4research.blogspot.co.uk/2008/11/eigenfactor-scimago-journal-rankings.html
  62. 62. Predict Traffic http://iopscience.iop.org/1742-5468/2008/07/P07008/ deepsan
  63. 63. three different surfers Chris Hunkeler
  64. 64. three different surfers Random Surfer Chris Hunkeler
  65. 65. Random Surfer Reflects the chance that the random surfer will leave the site through a link chosen at random, so all equally likely, and therefore valuable
  66. 66. three different surfers Reasonable Surfer Chris Hunkeler
  67. 67. Reasonable Surfer The reasonable surfer model supposes that some links are more likely to be clicked on and therefore should be given more value.
  68. 68. three different surfers Intentional Surfer Chris Hunkeler
  69. 69. Intentional Surfer The intentional surfer model supposes that links which ‘actually’ receive the most links should be given more value. http://en.wikipedia.org/wiki/PageRank#The_intentional_surfer_model
  70. 70. A lot has changed at Google, but it will always be a search engine which relies upon PageRank; which is a practical application of Graph Theory
  71. 71. Insert Audience Participation
  72. 72. Hands up who thinks FB GraphSearch is the best search engine in the world?
  73. 73. Just me?
  74. 74. Not here to convince you GraphSearch will catch on but...
  75. 75. If the area of this slide represents all the traffic on the internet
  76. 76. This much is Facebook http://mashable.com/2010/11/19/facebook-traffic-stats/
  77. 77. And every thing in white is the rest of the internet
  78. 78. Google, YouTube, Wikipedia, The Daily Mail, etc.
  79. 79. your website, my website, her website etc.
  80. 80. If anyone can build a Google-Killer it’s Facebook...
  81. 81. There’s a fundamental difference between Facebook & Google
  82. 82. is about...
  83. 83. documents and links JD Hancock
  84. 84. is about...
  85. 85. things and relationships JD Hancock
  86. 86. this difference is subtle but huge
  87. 87. but I think it works better for the web as we know it JD Hancock
  88. 88. Google are trying to catchup but will struggle zoom images
  89. 89. Facebook’s data has a far more explicit structure than traditional web text JD Hancock
  90. 90. it’s not that tricky for Google to parse “I Like Nerf Guns” porkist
  91. 91. they could even have a go at “I was at Bodeans on Poland Street for Lunch Yesterday”* *if you mark it up in the right way R_Savvy
  92. 92. but has a much harder job understanding “Kelvin is married to Carolyn”
  93. 93. Facebook knows that happened in 2007
  94. 94. And who attended the ceremony
  95. 95. And when we got engaged
  96. 96. etc.
  97. 97. Google have to infer structure
  98. 98. Facebook know the structure
  99. 99. On GraphSearch you’re not really making a search. You’re just filtering a structured database of all the data Facebook has.
  100. 100. On GraphSearch you’re not really making a search. You’re just filtering a structured database of all the data Facebook has.
  101. 101. But it’s a bloody big database JD Hancock
  102. 102. 1 Billion Users Every Month
  103. 103. 240 Million Photo’s Per Day
  104. 104. 2.7 Billion Likes Everyday
  105. 105. People share billions of pieces of content everyday
  106. 106. One trillion connections of a thousand different types
  107. 107. 1,000,000,000,000
  108. 108. http://mashable.com/2013/07/08/facebook-launch-graph-search/
  109. 109. Every User, Page, Photo, Post & Place is a Node https://thetribe.s3.amazonaws.com/ferris.gif
  110. 110. http://maxlutz.com/blog/wp-content/uploads/2013/05/coffee2.gif Every friendship, checkin, tag or like is an Edge
  111. 111. Each Node has Meta-Data like description, this how the old FB Search “worked”
  112. 112. GraphSearch Allows you search the Edges as well as the Nodes JD Hancock JD Hancock
  113. 113. GraphSearch makes it easy to find nodes that are connected to another node by searching for an edge-type combined with an input node.  E.g.: ■Your friends:  friend:10003 ■People who live in new york: lives-in:111 ■People who like downtown abbey: like:222
  114. 114. ‘Facebook use query-independent signals to come up with a numeric value for importance. This value is called the “static rank” of the entity.’ JD Hancock
  115. 115. What makes up static rank is still up for debate, but sensibly could be informed by the elements of Edgerank aka the (old name for) newsfeed algo
  116. 116. Affinity
  117. 117. Weight
  118. 118. Decay
  119. 119. The value of legitimate likes from well connected people just increased
  120. 120. There’s also been lot going on at Google
  121. 121. not a new update Martin Cathrae
  122. 122. but a new paradigm
  123. 123. introducing Knowledge Graph*
  124. 124. introducing Knowledge Graph* *and things not technically Knowledge Graph but sort of along the same lines
  125. 125. The Knowledge Graph enables you to search for things, people or places that Google knows about—landmarks, celebrities, cities, sports teams, buildings, geographical features, movies, celestial objects, works of art and more—and instantly get information that’s relevant to your query. Amit Singhal, Google
  126. 126. Knowledge Graph is part of a huge change in how Google deliver search results
  127. 127. I’m now going to give you lots of examples of changes in the way Google present results, not all of them are truly ‘Knowledge Graph’ but do indicate a general shift in the way they present results.
  128. 128. There’s more than 85 of these features that Dr. Pete from Moz has documented http://www.slideshare.net/crumplezone/ beyond-10-blue-links-the-future-of-ranking
  129. 129. But they’re just for informational queries... Right?
  130. 130. a change in purpose: help find pages help find answers
  131. 131. a change in purpose: help find pages help find answers
  132. 132. You can no longer rely on Google to send you traffic
  133. 133. or even tell you about it Alex E. Proimos
  134. 134. for nearly a year iPhone search traffic appeared as direct JD Hancock
  135. 135. and we’re rapidly approaching the point where we have no data on keyword traffic
  136. 136. Search isn’t about keywords anymore
  137. 137. It's about entities. chukgawlikphotography
  138. 138. Entities are normally, people, places, brands etc JD Hancock
  139. 139. but can be any ‘thing’ which has a relationship to another ‘thing’ JD Hancock
  140. 140. how can you make money if nobody ever goes to your site? JD Hancock
  141. 141. You may need to revisit your business model kennymatic
  142. 142. I love the Business Model Canvas http://en.wikipedia.org/wiki/Business_Model_Canvas
  143. 143. sit down and ask yourself could your business have an api
  144. 144. as every business is really just a database and a front end JD Hancock
  145. 145. and Google wants to become that front-end JD Hancock
  146. 146. So what can I do?
  147. 147. Familiarize yourself with Freebase http://www.freebase.com/
  148. 148. And DBpedia http://wiki.dbpedia.org/Datasets
  149. 149. It’s amazing the data they have yaph
  150. 150. If any of your keywords contain entities you MUST be prepared http://i.imgur.com/GLCC0bd.gif
  151. 151. Use BlueNod to Visualise Social Networks http://bluenod.com/
  152. 152. Different communities manifest themselves in different ways http://www.beautifullife.info/wp-content/uploads/2012/12/11/05.gif
  153. 153. Play with VisualDataWeb http://www.visualdataweb.org/relfinder
  154. 154. Mark Up using the Open Graph Protocol http://ogp.me/
  155. 155. Implement Schema.org http://schema.org/
  156. 156. No schema? Create one/extend one http://schema.org/docs/extension.html
  157. 157. Follow Peter Mika @pmika
  158. 158. Read Matthew J. Brown’s Mozcon Deck http://www.slideshare.net/MatthewBrownPDX/strings-to-things-the-move-to-semantic-seo-mozcon-2013
  159. 159. Watch WSDM Videos Web Search and Data Mining Conference http://videolectures.net/wsdm/
  160. 160. Do Good Marketing
  161. 161. tl;dr SEO is changing it’s not about optimising your website for search engines, it’s about optimising your business for search engines
  162. 162. Kelvin Newman kelvin@brightonseo.com @kelvinnewman

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