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ShareIt: Mining SocialMedia Activities for Detecting Events
Published on 2011-07-184480 Views
The list of social networking websites is diverse across the globe but the popularity of social media is indisputable. The 640M+ Facebook users, the 480M+ QZone users or the 200M+ Twitter users are us
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Presentation
ShareIt: Mining #SocialMedia Activities for Detecting #Events00:00
Representing Media with Media Ontology00:00
Cover of the December 25, 2006 issue00:07
What are Events?00:31
Quiz Test : who has already ...00:52
Ontology: Making an abstraction01:36
Event-based centric interfaces02:02
How much data is there?02:44
There are already many event ontologies02:51
What do you do for getting event info?02:52
Fundamental Types of Events04:09
How fast media are uploaded?04:46
Looking for more structured information?05:26
Finding more media that illustrate an event06:04
Looking for some media? - 106:10
Looking for some media? - 207:10
A. Bounding box of Nouveau Casino?07:22
Anything on Flickr/ YouTube?07:49
Events and Temporal Intervals07:59
SSMS participants were better “sharer”08:24
Looking for some live information?09:16
Facebookis the place to be, right?09:29
Flickr10:27
Events, Spaces and Places10:51
We have directory of events...10:53
eventful - 111:30
Google11:53
eventful - 212:06
Panoramio12:12
eventful - 312:25
Freebase12:48
eventful - 412:57
About13:01
Participation in events13:08
eventful - 513:14
last.fm13:24
The Journey13:36
There’s a lot of information out there ...14:06
A lot of information ...14:18
EventMedia Goals14:45
Events, Influence, Purpose and Causality14:47
B. 74 photos taken in this area this day15:04
C. 85 additional photos with a similar title15:34
Agenda - 115:35
D. 6 photos after visual pruning16:04
Events, Parts and Composition16:30
How is the visual pruning performed?16:31
From the Web to the Web of Data - 117:25
E. 66 photos after uploader heuristics17:33
Towards a Linked Data Event Model17:45
From the Web to the Web of Data - 218:11
From the Web to the Web of Data - 318:31
Some mappings in LODE18:33
From the Web to the Web of Data - 418:52
Same process for videos19:07
LODE: An ontology for Linking Open Descriptions of Events19:22
Representing Events with LODE - 119:42
Domain - dedicated microformats19:47
About Microformats20:00
RDFa - 121:00
RDFa - 221:09
RDFa stands for ...21:14
RDFa in attributes of a web page to…21:28
How illustrated are events?21:37
weaving RDFa21:39
EventMediaGoals (User-CenteredDesign)21:45
RDFa step 121:46
RDFa step 221:58
RDFa step 322:02
Take this minimal web page22:09
1st Collect some opinions ...22:13
don't look at the code22:24
Schemas for data 22:32
Data seen by users22:43
RDFa agent22:57
EventMedia Project: Questionnaire23:23
Data shared23:34
what an RDFa agent knows23:38
Brainstorm online with users24:01
RDF - 124:13
2nd Look into “real” behaviors ...24:27
RDF - 224:30
RDF - 324:34
image - 124:46
image - 224:59
image - 325:13
RDF - 425:24
Behavioral Patterns - 125:26
RDF - 525:30
image.jpg25:43
RDF - 625:56
RDF - 726:12
Generating Visual Summaries - 126:28
flick.com26:28
Generating Visual Summaries - 226:59
The RDF Data Model27:02
Generating Visual Summaries - 327:11
Generating Visual Summaries - 427:23
Behavioral Patterns - 227:24
Generating Visual Summaries - 527:26
Event Detection27:34
Example of RDF Graphs27:48
Simple example (Google Vocab)28:20
Behavioral Patterns - 328:31
Behavioral Patterns - 428:40
Rich Snippet Preview28:53
Rich Snippet Preview for Reviews29:31
Rich Snippet Preview for People29:39
Rich Snippet Preview for Recipes30:20
Rich Snippet Preview for Events30:28
Yahoo! Enhanced Results30:36
Example: the venue Koko30:46
Existing Services30:58
Yahoo! Vertical Intent Search31:11
Snippet generation using metadata31:24
How search engines get this data?32:01
Organize the mess32:14
Behind the scene32:26
Get your markup with test tool32:44
Example: the venue Melkweg32:45
Róisín Murphy at Nouveau Casino - 132:53
How much structured data is out there?33:08
Translating the Ontology and the Data33:53
Representing Events with LODE - 234:08
US/English Rich Snippets Usage - 134:38
US/English Rich Snippets Usage - 235:17
Linking the Data35:20
RDFaon the rise35:30
Reasoning & Annotation35:33
Interface elements35:58
Interfaces36:09
Collaborative Filtering36:15
Future for Rich Snippets? - 136:23
The Goal36:34
The Back-end36:39
Interlinking - 136:56
User Interface - 137:02
Future for Rich Snippets? - 237:16
User Interface - 237:18
Agenda - 337:29
Interlinking - 237:33
SILK Framework - 137:50
Schema.org37:51
Citizen Sensors in Action38:11
SILK Framework - 239:08
Citizen Journalism39:15
Business Intelligence39:34
Schema.rdfs.org39:48
2011/06/27: [Announcement]40:09
Alignement for Agents40:10
What’s in a Tweet?40:32
A lot of Events Categories in Schema.org40:33
Metadata about People - 141:14
take away message41:15
don't bury your data in some HTML page41:25
when you publish a page that contains data ...41:29
Metadata about People - 241:32
do make the embedding explicit 41:33
Linked Data Principles41:48
Alignement for Locations42:25
Metadata about People - 342:39
An Example: DBpedia43:31
Metadata about Network44:01
Scraping infobox data44:18
Automatic Links Among Open Datasets45:04
Metadata about Content45:06
Alignement for Events45:27
Extracting Entities from Tweets45:33
Twitris:Semantic Social Web Mash-up45:59
Research challenges46:28
Searching on Twitter46:42
sameAs.org46:51
Issues with Multiple Keywords Search47:06
Let’s try to search with One Keyword47:14
Bogotá on Freebase47:15
Bogotá on Geonames47:22
Page 147:24
How Much Linked Data is there ?47:26
Page 247:27
Page 347:28
Page 6047:30
What are Events? - 147:35
What are Events? - 247:59
Relation Discovery Framework48:02
Linked Data Cloud – August 200748:17
Linked Data Cloud – March 200848:29
Linked Data Cloud – September 200848:31
Linked Data Cloud – March 200948:34
Linked Data Cloud – September 201048:36
Entity Extraction and Semantic Enrichment48:46
Róisín Murphy at Nouveau Casino - 249:03
Relation Learning Strategies49:08
Where do relationships emerge faster?49:28
On Conferences ... we Tweet 50:03
Media explicitly associated with the event50:08
Rich ActivityTwitter Event Data50:10
The Web of Data50:36
Find the correspondence50:44
flickr meets foursquare51:00
... but let’s STOP counting!51:12
Final Announcement: Google+51:30
Linked data summary51:47
Searching Entities in the Cloud53:02
Reconciling links in the cloud53:31
Searching Linked Data53:56
Sindicealready crawling Schema.org54:02
Niall Kennedy's Weblog54:29
Browsing Linked Data - 154:33
Conclusions55:19
Browsing Linked Data - 255:31
Browsing Linked Data - 355:33
Browsing Linked Data - 455:34
Browsing Linked Data - 555:41
VisiNav55:42
Sig.ma55:43
Freebase parallax56:09
TimBL Visionback in 199456:27
Credits56:35
slideshare56:53
FOAF History (credits: @danbri)57:38
Friend of a Friend57:54
Henry says, “My name is ‘Henry Story”58:14
FOAF (Friend-of-a-Friend) 59:13
The FOAF Specification01:00:10
Friend of a Friend (FOAF)01:00:14
Integrating SN with FOAF for reuse01:00:49
Going through the Walled Gardens01:00:59
FOAF Naut01:01:50
FOAF Builder01:01:56
FOAF hits the news01:02:07
Relationship Vocabulary01:02:08
Blank Page01:02:44
Semantically - Interlinked Online Communities01:03:18
The SIOC ontology01:04:05
Producing SIOC data01:04:33
Portable Data with SIOC and FOAF01:04:58
Collect SIOC from various sources01:05:20
Consuming SIOC via Exhibit01:05:37
Dublin Core01:05:44
Dublin Core example01:05:55
Good Relations - 101:06:05
Good Relations - 201:06:15
Best Buy01:06:29
The Open Graph Protocol01:07:40
Open Graph: Getting Started01:07:54
Open Graph Properties01:08:25
rNewsfor the Press01:08:45
Wrap up: popular vocabularies01:09:24
Agenda - 201:09:33