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Graph Theory #searchlove The theory that underpins how all search engines work @kelvinnewman
The document discusses the importance of graph theory in understanding search engines, particularly in the context of Facebook's Graph Search and Google's Knowledge Graph. It emphasizes how both platforms use structured databases to manage and filter vast amounts of data, illustrating the shift from keyword-based search to entity-centric approaches. The document also suggests that businesses should adapt to these changes by leveraging data and optimizing not just for search engines, but for their overall business models.
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Similar to Graph Theory #searchlove The theory that underpins how all search engines work @kelvinnewman
Graph Theory #searchlove The theory that underpins how all search engines work @kelvinnewman
- 1. LINK SOCIAL GRAPH graph GRAPH theory ! The theorythat underpins how all search KNOWLEDGE work engines ETC. GRAPH @kelvinnewman
- 2. Graph Theory The mostimportant theory in search that nobody talks about Kelvin Newman @kelvinnewman JD Hancock
- 3. Organiser BrightonSEO / ContentMarketing Show / MeasureFest Three Free (and awesome) Conferences
- 4. Strategy Director SiteVisibility A digitalagency specialising in retail, travel and financial services
- 5. Co-Founder Clockwork Talent Decent DigitalRecruitment
- 6.
- 7. JD Hancock I mightget in trouble for this JD Hancock
- 8. I’ve been letinto a secret future beta of Google, and I’m going to reveal it to you
- 10. Joking aside; Ithink FB GraphSearch is a great indicator of the future of G JD Hancock
- 11. as it helpsus better understand one of the theories that underlies all search engines JD Hancock
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- 21.
- 22. but we’ve beendistracted, from what our job really is
- 23. which is understandinghow the search engines fundamentally work jronaldlee
- 24. LINK SOCIAL GRAPH graph GRAPH theory KNOWLEDGE is centralto that GRAPH ! understanding ETC.
- 25. this presentation may containmaths Benson Kua
- 26.
- 27. Will Critchlow Maths MA- University of Cambridge will - cambridge maths Dana Lookadoo - Yo! Yo! SEO
- 28. Tom Anthony PhD ArtificialIntelligence University of Hertfordshire
- 29.
- 30. I’m no computerscientist or mathematician jlwo
- 31. graph theory ! “a mathematical modelfor any system involving a binary relation” Frank Harary, 1969
- 32. “perhaps even more thanto the contact between mankind and nature, graph theory owes to the contact of human beings between each other” Dénes König, 1936
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- 42. This Graph isIsomorphic of the other one, aka it’s the same but looks different
- 43. Matrix view ofgraph V1 V1 V2 V3 V4 V5 V6 V2 V3 V4 V5 V6
- 44. Matrix view ofgraph V1 V1 V2 V3 V4 V5 V6 0 V2 V3 V4 V5 V6
- 45. Matrix view ofgraph V1 V1 V2 V3 V4 V5 V6 V2 0 1 V3 V4 V5 V6
- 46. Matrix view ofgraph V1 V1 V2 V3 V4 V5 V6 V2 V3 V4 0 1 1 1 V5 V6
- 47. Matrix view ofgraph V1 V1 V2 V3 V4 V5 V6 V2 V3 V4 V5 V6 0 1 1 1 0 0
- 48. Matrix view ofgraph V1 V2 V3 V4 V5 V6 V1 0 1 1 1 0 0 V2 1 0 V3 V4 V5 V6
- 49. Matrix view ofgraph 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
- 50. Matrix view ofgraph 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
- 51. Or maybe? Blogger 1 Blogger2 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
- 52. Cardinality is thenumber of Nodes or Vertices in a Graph Prayitno/
- 53. Degrees of Vertexis how many edges a vertex has. chedder
- 54. Trees & Circuits OurGraph 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
- 55. Watch PatrickJMT’s Graph TheoryVideos http://patrickjmt.com/graph-theory-an-introduction/
- 56. What’s the firstthing you teach your team? http://i.imgur.com/PGE2D2n.gif
- 57. For me itis PageRank http://computationalculture.net/article/what_is_in_pagerank
- 58. Jim Seward is alegend http://computationalculture.net/article/what_is_in_pagerank
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- 60. A set ofrules which can be used to give a numerical weighting to assess the importance of document within linked data set
- 61. A set ofrules which can be used to give a numerical weighting to assess the importance of nodes document within linked data set
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- 63. PageRank is usedfor than the Algo natalielucier
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- 67. three different surfers ChrisHunkeler
- 68. three different surfers RandomSurfer Chris Hunkeler
- 69. Random Surfer Reflects thechance that the random surfer will leave the site through a link chosen at random, so all equally likely, and therefore valuable
- 70. three different surfers ReasonableSurfer Chris Hunkeler
- 71. Reasonable Surfer The reasonablesurfer model supposes that some links are more likely to be clicked on and therefore should be given more value.
- 72. three different surfers IntentionalSurfer Chris Hunkeler
- 73. Intentional Surfer The intentionalsurfer 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
- 74. A lot haschanged at Google, but it will always be a search engine which relies upon PageRank; which is a practical application of Graph Theory
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- 76. Hands up whothinks FB GraphSearch is the best search engine in the world?
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- 78. Not here toconvince you GraphSearch will catch on but...
- 79. If the areaof this slide represents all the traffic on the internet
- 80.
- 81. And every thingin white is the rest of the internet
- 82. Google, YouTube, Wikipedia, TheDaily Mail, etc.
- 83. your website, my website,her website etc.
- 84. If anyone can builda Google-Killer it’s Facebook...
- 85. There’s a fundamental differencebetween Facebook & Google
- 86.
- 87. documents and links JDHancock
- 88.
- 89. things and relationships JDHancock
- 90. this difference issubtle but huge
- 91. but I thinkit works better for the web as we know it JD Hancock
- 92. Google are tryingto catchup but will struggle zoom images
- 93. Facebook’s data has afar more explicit structure than traditional web text JD Hancock
- 94. it’s not that tricky forGoogle to parse “I Like Nerf Guns” porkist
- 95. they could evenhave a go at “I was at Bodeans on Poland Street for Lunch Yesterday”* *if you mark it up in the right way R_Savvy
- 96. but has amuch harder job understanding “Kelvin is married to Carolyn”
- 97. Facebook knows that happenedin 2007
- 98. And who attendedthe ceremony
- 99. And when wegot engaged
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- 101. Google have toinfer structure
- 102. Facebook know thestructure
- 103. On GraphSearch you’renot really making a search. You’re just filtering a structured database of all the data Facebook has.
- 104. On GraphSearch you’renot really making a search. You’re just filtering a structured database of all the data Facebook has.
- 105. But it’s abloody big database JD Hancock
- 106. 1 Billion UsersEvery Month
- 107. 240 Million Photo’sPer Day
- 108. 2.7 Billion LikesEveryday
- 109. People share billionsof pieces of content everyday
- 110. One trillion connectionsof a thousand different types
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- 112.
- 113. Every User, Page,Photo, Post & Place is a Node https://thetribe.s3.amazonaws.com/ferris.gif
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- 115. Each Node hasMeta-Data like description, this how the old FB Search “worked”
- 117. GraphSearch Allows you searchthe Edges as well as the Nodes JD Hancock JD Hancock
- 118. GraphSearch makes iteasy 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
- 119. ‘Facebook use query-independent signalsto come up with a numeric value for importance. This value is called the “static rank” of the entity.’ JD Hancock
- 120. What makes upstatic rank is still up for debate, but sensibly could be informed by the elements of Edgerank aka the (old name for) newsfeed algo
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- 125. The value oflegitimate likes from well connected people just increased
- 126. There’s also been lotgoing on at Google
- 127. not a newupdate Martin Cathrae
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- 129.
- 130. introducing Knowledge Graph* *and thingsnot technically Knowledge Graph but sort of along the same lines
- 131. The Knowledge Graphenables 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
- 132. Knowledge Graph is partof a huge change in how Google deliver search results
- 133. I’m now goingto 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.
- 138. There’s more than85 of these features that Dr. Pete from Moz has documented http://www.slideshare.net/crumplezone/ beyond-10-blue-links-the-future-of-ranking
- 139. But they’re justfor informational queries... Right?
- 146. a change inpurpose: help find pages help find answers
- 147. a change inpurpose: help find pages help find answers
- 148. You can nolonger rely on Google to send you traffic
- 149. or even tellyou about it Alex E. Proimos
- 150. for nearly ayear iPhone search traffic appeared as direct JD Hancock
- 151. and we’re rapidlyapproaching the point where we have no data on keyword traffic
- 152. Search isn’t about keywordsanymore
- 153.
- 154. Entities are normally, people, places, brandsetc JD Hancock
- 155. but can beany ‘thing’ which has a relationship to another ‘thing’ JD Hancock
- 156. how can youmake money if nobody ever goes to your site? JD Hancock
- 157. You may needto revisit your business model kennymatic
- 158. I love theBusiness Model Canvas http://en.wikipedia.org/wiki/Business_Model_Canvas
- 159. sit down andask yourself could your business have an api
- 160. as every business isreally just a database and a front end JD Hancock
- 161. and Google wantsto become that front-end JD Hancock
- 162. So what canI do?
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- 165. It’s amazing thedata they have yaph
- 166. If any ofyour keywords contain entities you MUST be prepared http://i.imgur.com/GLCC0bd.gif
- 167. Use BlueNod toVisualise Social Networks http://bluenod.com/
- 168. Different communities manifest themselvesin different ways http://www.beautifullife.info/wp-content/uploads/2012/12/11/05.gif
- 172.
- 174. Mark Up usingthe Open Graph Protocol http://ogp.me/
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- 176. No schema? Create one/extendone http://schema.org/docs/extension.html
- 177.
- 178. Read Matthew J.Brown’s Mozcon Deck http://www.slideshare.net/MatthewBrownPDX/strings-to-things-the-move-to-semantic-seo-mozcon-2013
- 179. Watch WSDM Videos WebSearch and Data Mining Conference http://videolectures.net/wsdm/
- 180.
- 181. tl;dr SEO is changingit’s not about optimising your website for search engines, it’s about optimising your business for search engines
- 182.