MediaFinder: Collect, Enrich and Visualize Media Memes Shared by the CrowdRaphael Troncy
"MediaFinder: Collect, Enrich and Visualize Media Memes Shared by the Crowd", talk given at the 2nd Real Time Analysis and Mining of Social Streams Workshop (RAMSS) colocated with WWW 2013, Rio de Janeiro, Brazil
Use of Open Data in Hong Kong (LegCo 2014)Sammy Fung
Presentation on use of open data in HK given to Legislative Council Secretariat. Content is mixed from my presentations at startmeup 2013 and opendatahk meetup.
Semantics at the multimedia fragment level SSSW 2013Raphael Troncy
"Semantics at the multimedia fragment level or how enabling the remixing of online media" - Invited Talk given at the Semantic Web Summer School (SSSW), 12 July 2013
Multimedia Semantics:Metadata, Analysis and InteractionRaphael Troncy
Multimedia Semantics:Metadata, Analysis and Interaction. Keynote Talk at the Latin-American Conference on Networked Electronic Media (LACNEM), August 2009, Bogota, Colombia
Stream reasoning: mastering the velocity and the variety dimensions of Big Da...Emanuele Della Valle
More and more applications require real-time processing of heterogeneous data streams. In terms of the “Vs” of Big Data (volume, velocity, variety and veracity), they require addressing velocity and variety at the same time. Big Data solutions able to handle separately velocity and variety have been around for a while, but only Stream Reasoning approaches those two dimensions at once. Current results in the Stream Reasoning field are relevant for application areas that require to: handle massive datasets, process data streams on the fly, cope with heterogeneous incomplete and noisy data, provide reactive answers, support fine-grained information access, and integrate complex domain models. This talk starting from those requirements, frames the problem addressed by Stream Reasoning. It poses the research question and operationalise it with four simpler sub-questions. It describes how the database group of Politecnico di Milano positively answered those sub-questions in the last 7 years of research. It briefly surveys alternative approaches investigated by other research groups world wide and it elaborates on current limitations and open challenges.
MediaFinder: Collect, Enrich and Visualize Media Memes Shared by the CrowdRaphael Troncy
"MediaFinder: Collect, Enrich and Visualize Media Memes Shared by the Crowd", talk given at the 2nd Real Time Analysis and Mining of Social Streams Workshop (RAMSS) colocated with WWW 2013, Rio de Janeiro, Brazil
Use of Open Data in Hong Kong (LegCo 2014)Sammy Fung
Presentation on use of open data in HK given to Legislative Council Secretariat. Content is mixed from my presentations at startmeup 2013 and opendatahk meetup.
Semantics at the multimedia fragment level SSSW 2013Raphael Troncy
"Semantics at the multimedia fragment level or how enabling the remixing of online media" - Invited Talk given at the Semantic Web Summer School (SSSW), 12 July 2013
Multimedia Semantics:Metadata, Analysis and InteractionRaphael Troncy
Multimedia Semantics:Metadata, Analysis and Interaction. Keynote Talk at the Latin-American Conference on Networked Electronic Media (LACNEM), August 2009, Bogota, Colombia
Stream reasoning: mastering the velocity and the variety dimensions of Big Da...Emanuele Della Valle
More and more applications require real-time processing of heterogeneous data streams. In terms of the “Vs” of Big Data (volume, velocity, variety and veracity), they require addressing velocity and variety at the same time. Big Data solutions able to handle separately velocity and variety have been around for a while, but only Stream Reasoning approaches those two dimensions at once. Current results in the Stream Reasoning field are relevant for application areas that require to: handle massive datasets, process data streams on the fly, cope with heterogeneous incomplete and noisy data, provide reactive answers, support fine-grained information access, and integrate complex domain models. This talk starting from those requirements, frames the problem addressed by Stream Reasoning. It poses the research question and operationalise it with four simpler sub-questions. It describes how the database group of Politecnico di Milano positively answered those sub-questions in the last 7 years of research. It briefly surveys alternative approaches investigated by other research groups world wide and it elaborates on current limitations and open challenges.
Connections between big data and open data. Includes a case study of Data.gov and the ways that companies, charities, and others are using open data to improve the lives of people around the planet.
H. Purohit, Y. Ruan, A. Joshi, S. Parthasarathy, A. Sheth. Understanding User-Community Engagement by Multi-faceted Features: A Case Study on Twitter. in SoME 2011 (Workshop on Social Media Engagement, in conjunction with WWW 2011), March 29, 2011.
Paper: http://knoesis.org/library/resource.php?id=1095
More on Social Media @ Kno.e.sis at http://knoesis.org/research/semweb/projects/socialmedia/
@ WU Reading Group
* Status of thesis
* Relation to other work
* Next steps and ideas
Topic Modeling, Event Extraction, Target-dependent Sentiment Analysis...
Abstract:
This article examines how online groups are formed and sustained during crisis periods, especially when political polarization in society is at its highest level. We focus on the use of Vkontakte (VK), a popular social networking site in Ukraine, to understand how it was used by Pro- and Anti-Maidan groups during the 2013/2014 crisis in Ukraine. In particular, we ask whether and to what extent the ideology (or other factors) of a particular group shapes its network structure. We find some support that online social networks are likely to represent local and potentially preexisting social networks, likely due to the dominance of reciprocal (and often close) relationships on VK and opportunities for group members to meet face-to-face during offline protests. We also identify a number of group-level indicators, such as degree centralization, modularity index and average engagement level, that could help to classify groups based on their network properties. Community researchers can start applying these group-level indicators to online communities outside VK; they can also learn from this article how to identify networks of spam and marketing accounts.
Invited talk at Session on Semantic Knowledge for Commodity Computing, at Microsoft Research Faculty Summit 2011, July 19-20, 2011, Redmond, WA. http://research.microsoft.com/en-us/events/fs2011/default.aspx
Associated video at: https://youtu.be/HKqpuLiMXRs
A Framework Concept for Profiling Researchers on Twitter using the Web of DataLaurens De Vocht
Based upon findings and results from our recent research we propose a generic frame-
work concept for researcher profiling with appliance to the areas of ”Science 2.0” and ”Research 2.0”. Intensive growth of users in social networks, such as Twitter generated a vast amount of information. It has been shown in many previous works that social networks users produce valuable content for profiling and recommendations. Our research focuses on identifying and locating experts for specific research area or topic. In our approach we apply semantic technologies like (RDF, SPARQL), common vocabularies (SIOC , FOAF, MOAT, Tag Ontology) and Linked Data (GeoNames , COLINDA).
Connections between big data and open data. Includes a case study of Data.gov and the ways that companies, charities, and others are using open data to improve the lives of people around the planet.
H. Purohit, Y. Ruan, A. Joshi, S. Parthasarathy, A. Sheth. Understanding User-Community Engagement by Multi-faceted Features: A Case Study on Twitter. in SoME 2011 (Workshop on Social Media Engagement, in conjunction with WWW 2011), March 29, 2011.
Paper: http://knoesis.org/library/resource.php?id=1095
More on Social Media @ Kno.e.sis at http://knoesis.org/research/semweb/projects/socialmedia/
@ WU Reading Group
* Status of thesis
* Relation to other work
* Next steps and ideas
Topic Modeling, Event Extraction, Target-dependent Sentiment Analysis...
Abstract:
This article examines how online groups are formed and sustained during crisis periods, especially when political polarization in society is at its highest level. We focus on the use of Vkontakte (VK), a popular social networking site in Ukraine, to understand how it was used by Pro- and Anti-Maidan groups during the 2013/2014 crisis in Ukraine. In particular, we ask whether and to what extent the ideology (or other factors) of a particular group shapes its network structure. We find some support that online social networks are likely to represent local and potentially preexisting social networks, likely due to the dominance of reciprocal (and often close) relationships on VK and opportunities for group members to meet face-to-face during offline protests. We also identify a number of group-level indicators, such as degree centralization, modularity index and average engagement level, that could help to classify groups based on their network properties. Community researchers can start applying these group-level indicators to online communities outside VK; they can also learn from this article how to identify networks of spam and marketing accounts.
Invited talk at Session on Semantic Knowledge for Commodity Computing, at Microsoft Research Faculty Summit 2011, July 19-20, 2011, Redmond, WA. http://research.microsoft.com/en-us/events/fs2011/default.aspx
Associated video at: https://youtu.be/HKqpuLiMXRs
A Framework Concept for Profiling Researchers on Twitter using the Web of DataLaurens De Vocht
Based upon findings and results from our recent research we propose a generic frame-
work concept for researcher profiling with appliance to the areas of ”Science 2.0” and ”Research 2.0”. Intensive growth of users in social networks, such as Twitter generated a vast amount of information. It has been shown in many previous works that social networks users produce valuable content for profiling and recommendations. Our research focuses on identifying and locating experts for specific research area or topic. In our approach we apply semantic technologies like (RDF, SPARQL), common vocabularies (SIOC , FOAF, MOAT, Tag Ontology) and Linked Data (GeoNames , COLINDA).
Location Embeddings for Next Trip RecommendationRaphael Troncy
Joint work wih Amadeus presenting a recommender system for your next destination using knowledge graphs and deep learning network, presented at the LocWeb 2019 Workshop colocated with TheWebConf 2019 (San Francisco, USA)
NERD: an open source platform for extracting and disambiguating named entitie...Raphael Troncy
"NERD: an open source platform for extracting and disambiguating named entities in very diverse documents" - Keynote Talk given at the NLP&DBpedia International Workshop (NLP&DBpedia), 22 October 2013
Deep-linking into Media Assets at the Fragment Level SMAM 2013Raphael Troncy
"Deep-linking into Media Assets at the Fragment Level: Specification, Model and Applications" - Keynote Talk given at the International Workshop on Semantic Music and Media (SMAM), 21 October 2013
EventMedia Live: Exploring Events Connections in Real-Time to Enhance ContentRaphael Troncy
"EventMedia Live: Exploring Events Connections in Real-Time to Enhance Content" presented at the Semantic Web Challenge, Open Track, of the 11th International Semantic Web Conference, Boston, USA, November 2012
ShareIt: Mining SocialMedia Activities for Detecting EventsRaphael Troncy
ShareIt: Mining #SocialMedia Activities for Detecting #Events, Talk given at the 2nd Summer School on Social Media Retrieval (S3MR), June 2011, Antalya, Turkey
Experiencing Events through User-Generated MediaRaphael Troncy
Experiencing Events through User-Generated Media. Talk given at the 1st International Workshop on Consuming Linked Data (COLD), November 2010, Shanghai , China
Linking Events with Media. Talk given at the 6th International Conference on Semantic Systems (I-SEMANTICS), Triplification Challenge, September 2010, Graz, Austria
Multimedia Semantics: Metadata, Analysis and Interaction. Lecture Talk at the 5th Summer School on Multimedia Semantics (SSMS), August 2010, Amsterdam, The Netherlands
LODE: Une Ontologie pour representer des evenements dans le Web de DonneesRaphael Troncy
LODE: Une Ontologie pour représenter des événements dans le Web de Données - Talk given at the 21st Journées Francophones d'Ingénierie des Connaissances (IC'2010), Nîmes, France, June 9th 2010
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
From Siloed Products to Connected Ecosystem: Building a Sustainable and Scala...
Contextualizing Events in TV News Shows - SNOW 2014
1. Contextualizing Events in
TV News Shows
José Luis Redondo García, Laurens
De Vocht, Raphaël Troncy, Erik Mannens,
Rik Van de Walle
<raphael.troncy@eurecom.fr>
2. 08/04/2014 - 2nd Workshop on Social News on the Web (SNOW) @ WWW 2014 - 2
3. Edward Snowden asks for asylum in Russia (04 / 07 / 2013)
Problem: User Perspective
08/04/2014 - 2nd Workshop on Social News on the Web (SNOW) @ WWW 2014 - 3
4. In which Russian airport is he exactly?
LSCOM:Face
LSCOM:Building
?
Problem: Technological Perspective
08/04/2014 - 2nd Workshop on Social News on the Web (SNOW) @ WWW 2014 - 4
5. List of Relevant Named Entities (1) Named Entity
(2) Filtering and Ranking
b) Expanded Entities
b) Re-ranked Entities
a) Entities from Video
Approach
08/04/2014 - 2nd Workshop on Social News on the Web (SNOW) @ WWW 2014 - 5
7. REST API2ontology1 UI3
1 http://nerd.eurecom.fr/ontology
2 http://nerd.eurecom.fr/api/application.wadl
3 http://nerd.eurecom.fr
Named Entity Expansion: step 1
08/04/2014 - 2nd Workshop on Social News on the Web (SNOW) @ WWW 2014 - 7
8. Five W´s * Four W´s
Who: nerd:Person,
nerd:Organization
What: nerd:Event, nerd:Function,
nerd:Product
Where: nerd:Location
When: news program metadata
Entity Ranking and Selection:
Ranking according extractor’s
confidence
Relative confidence falls in the
upper quarter interval
Final Query:
Concatenate Labels of the
selected entities in Who, What,
Where, for a time t
(*) J. Li and L. Fei-Fei. What, where and who? classifying events by scene and object recognition
Named Entity Expansion: step 2
08/04/2014 - 2nd Workshop on Social News on the Web (SNOW) @ WWW 2014 - 8
9. Named Entity Expansion: step 3
08/04/2014 - 2nd Workshop on Social News on the Web (SNOW) @ WWW 2014 - 9
10. Entity clustering:
Centroid-based approach
Distance metric:
Strict string similarity over the URL’s
Jaro-Winkler string distance over labels
Entity re-ranking according to:
Relative frequency in the transcripts
Relative frequency over the additional documents
Average confidence score from the extractors
Output:
Frequent entities are promoted
Entities not disambiguated can be identified with a
URL by transitivity
Same happens with erroneous labels
Relevant but non-spotted entities arise (example: N)
Named Entity Expansion: step 4
08/04/2014 - 2nd Workshop on Social News on the Web (SNOW) @ WWW 2014 - 10
12. List of Relevant Named Entities (1) Named Entity
(2) Filtering and Ranking
b) Expanded Entities
b) Re-ranked Entities
a) Entities from Video
Approach
08/04/2014 - 2nd Workshop on Social News on the Web (SNOW) @ WWW 2014 - 12
13. For each pair of results:
Iteratively generate DBpedia paths using the EiCE engine [1]
[1] http://github.com/mmlab/eice
: Barack_Obama
:Vladimir_Putin
Refining via EiCE
08/04/2014 - 2nd Workshop on Social News on the Web (SNOW) @ WWW 2014 - 13
14. :United_States
:Edward_Wilmot_Blyden_III
Path 1 = Barack Obama – Abdul Kallon – Freetown – United States -
Edward_Wilmot_Blyden_III – Russia Vladimir_Putin
: Barack_Obama
:Vladimir_Putin
Computing of initial path:
• Preferring links with lower weight first (thinner lines)
Refining via EiCE
08/04/2014 - 2nd Workshop on Social News on the Web (SNOW) @ WWW 2014 - 14
16. Iterating continues until no more paths can be found
: Barack_Obama
:Vladimir_Putin
Refining via EiCE
08/04/2014 - 2nd Workshop on Social News on the Web (SNOW) @ WWW 2014 - 16
17. Length(Path 1) = 6
Length(Path 2) = 7
…
Length(Path k) = n
____________________________________________________________________________________________
Average_Length (:Barack_Obama, :Vladimir_Putin) = (13 + … + n)/k
Distance (:Barack_Obama, :Vladimir_Putin) (*) = normalize (Average_Length)
…
…
_____________________________________________________________________
Adjacency Matrix (**)
(*) http://demo.everythingisconnected.be/estimated_normalized_distance
Computation of the average path lengths after k iterations:
(**) http://demo.everythingisconnected.be/estimated_normalized_distance_matrix
Refining via EiCE
08/04/2014 - 2nd Workshop on Social News on the Web (SNOW) @ WWW 2014 - 17
18. Adjacency Matrix Mi,j
D(ei ,ej) =Avg(lenght(Paths(ei, ej ))))
Context Coherence
Refining via EiCE: Adjacency Matrix
08/04/2014 - 2nd Workshop on Social News on the Web (SNOW) @ WWW 2014 - 18
19. Frequent Nodes and Properties
In the context of the news
program, geographical
and political themes are
dominant
Some frequent
classes already
detected are further
promoted
Refining via EiCE: Results
08/04/2014 - 2nd Workshop on Social News on the Web (SNOW) @ WWW 2014 - 19
20. NE Expansion DBPedia Connectivity
(2)Ranking
Refining via EiCE: Results
08/04/2014 - 2nd Workshop on Social News on the Web (SNOW) @ WWW 2014 - 20
21. Setup: Expert defines the list of relevant concepts for the newscast based
on a deep analysis of the main argument and the feedback of 8 users
participating in a user experience study [*]
GT Entity Expert’s Comment NE Extraction NE Expansion DBpedia
Connectivity
Edward Snowden Public figure. He is the “who” of the news
✔ ✔ ✔
Russia The location, but also an actor, the indirect
object of the main sentence “”to whom” ✔ ✔ ✔
Political Asylum This is related to the “what” of the news. This
is the Snowden’s request, the direct object. ✔ ✔
CIA Background information on related to
Snowden, since he is an ex-CIA employee.
An axe in a wider sense, not this item in
particular, but on Snowden’s history.
✔ ✔ ✔
Sheremetyevo Airport, specific location of the news
✔ ✔
Anatoly Kucherena Secondary actor and speaker in the video.
Information about an interview of person
expressing his opinion.
✔ ✔
US Department of
State
Involved organization. Not mentioned but
related with the main subject
Other Entities “human-rights”
and “extradition”
Minister of Russia, “Igor
Shuvalov”
Other Comments Better ranking: Entities like
“Sheremetyevo” scored higher
Evaluation: Edward Snowden Asylum
08/04/2014 - 2nd Workshop on Social News on the Web (SNOW) @ WWW 2014 - 21
[*] L. Perez Romero, R. Ahn, and L. Hardman. LinkedTV News: designing
a second screen companion for web-enriched news broadcasts.
23. Conclusion
Approach for context-aware annotating news events:
Start from named entities recognized in timed text
Expand this set by analyzing documents about the same event
Complete and re-rank exploring path connectivity in DBpedia
Preliminary results indicate that:
The initial set of entities is enhanced with relevant concepts not
present in the original program
By exploring DBpedia paths we:
Obtain a more accurate ranking of the relevant concepts
Bring forward more related entities and filter out the ones which are less
representative in the broader context of an event
This Entity Context provides valuable data for a second
screen application that enhances user experience
08/04/2014 - 2nd Workshop on Social News on the Web (SNOW) @ WWW 2014 - 23
24. Future Work
Evaluation involving more users and other programs
Named Entity expansion:
Study the adequacy of different extractors in NERD when:
Annotating the original transcripts of the video (representative entities)
Annotating additional documents found in the Web (relevant entities)
Introduce less ambiguity when generating the query by not only
considering the surface form
Connectivity in DBpedia:
Analysis of the relevant properties for promoting other entities
Cluster algorithms over the Adjacency Matrix for detecting
meaningful groups of entities
08/04/2014 - 2nd Workshop on Social News on the Web (SNOW) @ WWW 2014 - 24