This presentation on Twitter Dynamics is part of the ARCOMEM training curriculum. Feel free to roam around or contact us on Twitter via @arcomem to learn more about ARCOMEM training on archiving Social Media.
This presentation on Opinion Mining is part of the ARCOMEM training curriculum. Feel free to roam around or contact us on Twitter via @arcomem to learn more about ARCOMEM training on archiving Social Media.
Arcomem training Topic Analysis Models advancedarcomem
This presentation on Topic Analysis Models is part of the ARCOMEM training curriculum. Feel free to roam around or contact us on Twitter via @arcomem to learn more about ARCOMEM training on archiving Social Media.
This presentation on Named Entity Evolution Recognition is part of the ARCOMEM training curriculum. Feel free to roam around or contact us on Twitter via @arcomem to learn more about ARCOMEM training on archiving Social Media.
This presentation on data enrichment is part of the ARCOMEM training curriculum. Feel free to roam around or contact us on Twitter via @arcomem to learn more about ARCOMEM training on archiving Social Media.
This presentation on data enrichment is part of the ARCOMEM training curriculum. Feel free to roam around or contact us on Twitter via @arcomem to learn more about ARCOMEM training on archiving Social Media.
This presentation on Opinion Mining is part of the ARCOMEM training curriculum. Feel free to roam around or contact us on Twitter via @arcomem to learn more about ARCOMEM training on archiving Social Media.
Arcomem training Topic Analysis Models advancedarcomem
This presentation on Topic Analysis Models is part of the ARCOMEM training curriculum. Feel free to roam around or contact us on Twitter via @arcomem to learn more about ARCOMEM training on archiving Social Media.
This presentation on Named Entity Evolution Recognition is part of the ARCOMEM training curriculum. Feel free to roam around or contact us on Twitter via @arcomem to learn more about ARCOMEM training on archiving Social Media.
This presentation on data enrichment is part of the ARCOMEM training curriculum. Feel free to roam around or contact us on Twitter via @arcomem to learn more about ARCOMEM training on archiving Social Media.
This presentation on data enrichment is part of the ARCOMEM training curriculum. Feel free to roam around or contact us on Twitter via @arcomem to learn more about ARCOMEM training on archiving Social Media.
This slideshow highlights the Tweet Analyzer machine, a tool created by Paterva and enabled through Maltego Carbon 3.5.3 and Maltego Chlorine 3.6.0. The Tweet Analyzer enables real-time captures of Tweets (from Twitter's streaming API) along with real-time sentiment analysis (based on polarities: positive, negative, and neutral), based on the Alchemy API.
10-15-13 “Metadata and Repository Services for Research Data Curation” Presen...DuraSpace
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Semantic Web & Information Brokering: Opportunities, Commercialization and Ch...Amit Sheth
Amit Sheth, "Semantic Web & Info. Brokering Opportunities, Commercialization and Challenges," Keynote talk at the workshop on Semantic Web: Models, Architecture and Management, September 21, 2000, Lisbon, Portugal.
This was the keynote given at probably the first international event with "Semantic Web" in title (and before the well known SciAm article). As in TBL's use of Semantic Web in his 1999 book, (semantic) metadata plays central role. The use of Worldmodel/Ontology is consistent with our use of ontology for (Web) information integration in 1994 CIKM paper. Summary of the talk by event organizers and other details are at: http://knoesis.org/library/resource.php?id=735
Prof. Sheth started a Semantic Web company Taalee, Inc. in 1999 (product was called MediaAnywhere A/V search engine- discussed in this paper in the context of one of its use by a customer Redband Broadcasting). The product included Semantic Web/populated Ontology based semantic (faceted) search, semantic browsing, semantic personalization, semantic targeting (advertisement), etc as is described in U.S. Patent #6311194, 30 Oct. 2001 (filed 2000). MediaAnywhere has about 25 ontologies in News/Business, Sports, Entertainment, etc.
Taalee merged to become Voquette in 2001 (product was called SCORE), Semagix in 2004 (product was called Semagix Freedom), and then Fortent in 2006 (products included Know Your Customers).
Paper submitted in Interaccion 2014 http://interaccion2014.ull.es/ where we propose a set de semantic web end-user tasks.
A paper written by Roberto García, Marta Oliva, Toni Granollers and Alfons Palacios
Duraspace Hot Topics Series 6: Metadata and Repository ServicesMatthew Critchlow
Presented by Declan Fleming, Arwen Hutt, and Matt Critchlow. The second in a three part Webinar series on Research Data Curation at UC San Diego, as part of the larger Research Cyberinfrastructure initiative.
At the Technology Trends seminar, with HCMC University of Polytechnics' lecturers, KMS Technology's CTO delivered a topic of Big Data, Cloud Computing, Mobile, Social Media and In-memory Computing.
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This presentation on data enrichment is part of the ARCOMEM training curriculum. Feel free to roam around or contact us on Twitter via @arcomem to learn more about ARCOMEM training on archiving Social Media.
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This slideshow highlights the Tweet Analyzer machine, a tool created by Paterva and enabled through Maltego Carbon 3.5.3 and Maltego Chlorine 3.6.0. The Tweet Analyzer enables real-time captures of Tweets (from Twitter's streaming API) along with real-time sentiment analysis (based on polarities: positive, negative, and neutral), based on the Alchemy API.
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This was the keynote given at probably the first international event with "Semantic Web" in title (and before the well known SciAm article). As in TBL's use of Semantic Web in his 1999 book, (semantic) metadata plays central role. The use of Worldmodel/Ontology is consistent with our use of ontology for (Web) information integration in 1994 CIKM paper. Summary of the talk by event organizers and other details are at: http://knoesis.org/library/resource.php?id=735
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Which contributions of the social web will stay in the future and will be preserved? And how will they be accessible and explorable for users? ARCOMEM creates tools which helps archivists to exploit the social web.
Internet Memory Foundation (IMF), Südwestrundfunk (SWR) and the Dutch Beeld en Geluid institute held a joint workshop about web archiving at FIAT IFTA World Conference 2011 in Turino, Italy. IMF and SWR introduced the ARCOMEM project to the international audiovisual archivist community.
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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/
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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:
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And...
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Charlie Greenberg, Host
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In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
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Unsubscribed: Combat Subscription Fatigue With a Membership Mentality by Head...
Arcomem training twitter-dynamics_beginner
1. Twitter Dynamics
ATHENA – Research and Innovation Center in Information,
Communication and Knowledge Technologies
2. Objective
• Based on data extracted from Twitter, we construct
a network of time-stamped term associations
• Queries that can be answered
– “What are the hashtags associated with #obama at time instance t?”
– “Give me the tweets that mention #cnn during the periods that
#obama is associated with #romney”
– “How the hashtags associated with #obamawins have evolved over
time?”
2Twitter Dynamics
3. Implementation
• Developed in JAVA
• Wide range of storage options for models
– Relational databases (MySQL, Postgresql)
– Graph database (Neo4J)
– RDF triplestore (H2RDF)
• Tested with up to 13 millions of Tweets
3Twitter Dynamics
4. UI For Exploring Twitter Dynamics
• Interface for Twitter Dynamics will provide a view on
the important hashtags for a campaign
– How their importance has evolved over time
– How their association with other hashtags has evolved
– Viewing evolution of associations with different time
granularities: hourly, daily, weekly
4Twitter Dynamics