open recommender

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Post on 04-Jul-2015

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OpenRecommender is an open source project to create the world's most reliable and scalable Recommendation Engine software for filtering and suggesting content & services of all types, in the right place, at the right time.

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  • 1. OpenRecommenderOpenRecommender A Cross-Platform Semantic Recommendation Engine Bryan Copeland, BCmoney MobileTV

2. SW Adoption (Major Issues)SW Adoption (Major Issues) Data linkage & integration Vocabulary selection Service & Content discovery Search-equivalent paradigm 3. RecommendationsRecommendations What is a recommendation? Interesting video (Video + Discussion) Shocking News story (News + Text + Organization) Delicious recipe/restaurant (Food + Text/Location) Favorite song/band (Person + Organization/Audio) My shows (Video + Person + Event) Medical Dataset to query (Species + Text + License) Medical treatment (Species + Person + Text) Legal services (Person + Organization + Profession + Event) I like it, so you must like it too! 4. TaxonomyTaxonomy Audio Celestial Code Device Discussion Event Food Image License Location News Organization Person Profession Species Text Video 5. SchemaSchema { "recommendations": [ { "recommendation" : { "title":"", "image":"", "link":"", "description":" } } ] } XML JSON 6. SemanticsSemantics RDF Bryan Copeland AkuninVillain... http://www.akunin.jp/ n3 @prefix foaf: . @prefix dc: . @prefix owl: . @prefix rec: . foaf:name Bryan Copeland"; dc:publisher Facebook; rec:recommends . dc:Title "Akunin"; dc:Title Villain"; owl:sameAs ; owl:sameAs . 7. OntologyOntology Mobile Phones Mobile TV Broadcast Type One-seg DMB IPTV XMLTV Dublin Core FOAF Music 8. ArchetypesArchetypes Lean Forward Researcher Techie Channel Surfer Armchair Activist Super Fan Party organizer Bargain hunter Lean Back Busy Executive Business Owner Couch Potato Concerned Parent Jock/Cheerleader Party hopper Pack rat 9. AlgorithmsAlgorithms Machine Learning (Stats) Non-negative matrix factorization Single Value Decomposition LaBarrie Theory (EQ) Collaborative Filtering (CF) Natural Language Processing (NLP) Fuzzy String Matching Intelligent Randomization 10. RelevanceRelevance Ranking factor plots performance of algorithms for each Archetype against each Semantic type from Taxonomy P x Q x R matrix Height = 10 (# of algorithms) Width = 500 (# of users) Depth = 17 (# of categories in Taxonomy) 11. ExampleExample User 1 User 2 User N CF 0.014 0.173 ML 0.158 0.092 A(n) Audio Video P Q R P = 12. Cross-Platform?Cross-Platform? Platform-specific plugins/apps: WordPress MediaWiki Firefox, IE, Safari, Opera browser plugin iPhone Blackberry Android Java Desktop client? Web Service API (w/ SPARQL endpoint) PHP, AJAX, HTML5 toolkits W3C Widgets 13. Looking ForLooking For Code Contributors Sponsors (contest) Project Champion (industry) Collaboration, Feedback 14. QuestionsQuestions Recommendations replacement for Search? How can Recommendation Engines (like Search Engines) be gamed? Ideas on ways to prevent attacks? Privacy issues? Others?