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ShareIt: Mining SocialMedia Activities for Detecting Events
Published on Jul 18, 20114464 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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Chapter list
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