Querying Capability Modeling
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Presentation for CS 690 course at Purdue of Querying Capability Modeling and Construction of Deep Web Sources.
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This video focuses on integration of Salesforce with Bonterra Impact Management.
Interested in deploying an integration with Salesforce for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
Introduction of Cybersecurity with OSS at Code Europe 2024
I develop the Ruby programming language, RubyGems, and Bundler, which are package managers for Ruby. Today, I will introduce how to enhance the security of your application using open-source software (OSS) examples from Ruby and RubyGems.
The first topic is CVE (Common Vulnerabilities and Exposures). I have published CVEs many times. But what exactly is a CVE? I'll provide a basic understanding of CVEs and explain how to detect and handle vulnerabilities in OSS.
Next, let's discuss package managers. Package managers play a critical role in the OSS ecosystem. I'll explain how to manage library dependencies in your application.
I'll share insights into how the Ruby and RubyGems core team works to keep our ecosystem safe. By the end of this talk, you'll have a better understanding of how to safeguard your code.
Programming Foundation Models with DSPy - Meetup Slides
Prompting language models is hard, while programming language models is easy. In this talk, I will discuss the state-of-the-art framework DSPy for programming foundation models with its powerful optimizers and runtime constraint system.
5th LF Energy Power Grid Model Meet-up Slides
5th Power Grid Model Meet-up
It is with great pleasure that we extend to you an invitation to the 5th Power Grid Model Meet-up, scheduled for 6th June 2024. This event will adopt a hybrid format, allowing participants to join us either through an online Mircosoft Teams session or in person at TU/e located at Den Dolech 2, Eindhoven, Netherlands. The meet-up will be hosted by Eindhoven University of Technology (TU/e), a research university specializing in engineering science & technology.
Power Grid Model
The global energy transition is placing new and unprecedented demands on Distribution System Operators (DSOs). Alongside upgrades to grid capacity, processes such as digitization, capacity optimization, and congestion management are becoming vital for delivering reliable services.
Power Grid Model is an open source project from Linux Foundation Energy and provides a calculation engine that is increasingly essential for DSOs. It offers a standards-based foundation enabling real-time power systems analysis, simulations of electrical power grids, and sophisticated what-if analysis. In addition, it enables in-depth studies and analysis of the electrical power grid’s behavior and performance. This comprehensive model incorporates essential factors such as power generation capacity, electrical losses, voltage levels, power flows, and system stability.
Power Grid Model is currently being applied in a wide variety of use cases, including grid planning, expansion, reliability, and congestion studies. It can also help in analyzing the impact of renewable energy integration, assessing the effects of disturbances or faults, and developing strategies for grid control and optimization.
What to expect
For the upcoming meetup we are organizing, we have an exciting lineup of activities planned:
-Insightful presentations covering two practical applications of the Power Grid Model.
-An update on the latest advancements in Power Grid -Model technology during the first and second quarters of 2024.
-An interactive brainstorming session to discuss and propose new feature requests.
-An opportunity to connect with fellow Power Grid Model enthusiasts and users.
TrustArc Webinar - 2024 Global Privacy Survey
How does your privacy program stack up against your peers? What challenges are privacy teams tackling and prioritizing in 2024?
In the fifth annual Global Privacy Benchmarks Survey, we asked over 1,800 global privacy professionals and business executives to share their perspectives on the current state of privacy inside and outside of their organizations. This year’s report focused on emerging areas of importance for privacy and compliance professionals, including considerations and implications of Artificial Intelligence (AI) technologies, building brand trust, and different approaches for achieving higher privacy competence scores.
See how organizational priorities and strategic approaches to data security and privacy are evolving around the globe.
This webinar will review:
- The top 10 privacy insights from the fifth annual Global Privacy Benchmarks Survey
- The top challenges for privacy leaders, practitioners, and organizations in 2024
- Key themes to consider in developing and maintaining your privacy program
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Querying Capability Modeling
- 1. CS-690 Fall-2009 Querying Capability Modelling and Construction of Deep Web Sources Paper by: Liangcai Shu, Weiyi Meng, Hai Fe, and Clement Yu Presentation by: Fabian Alenius
- 3. Information in Deep Web is 400-550 times larger than the surface web
- 4. Crawlers need to extract
- 5. information
- 7. A form submission consists of a set of values, one for every field of the form
- 9. An attribute is a field in a form
- 10. A query is a set of attributes
- 11. A set query instances are a set of attribute and value pairs, e.g. {<Author, Tolkien>, <Title, Bilbo>}
- 12. Four types of attributes Functional Attribute Range Attribute Categorical Attribute Value-Infinite Attribute
- 14. Conditional dependency – value of C insignificant if A is null
- 15. A -> C
- 17. T is not attribute type, but value type (e.g. phone, zip code, etc.)
- 18. Valid queries – accepted; Invalid queries – rejected
- 20. Formally: Given valid query S = {AU 1 ,..., Au n }, atomic iff any query T ⊂ S is invalid
- 21. Goal is to find Atomic Queries
- 22. Assign value only if attribute is part of query
- 25. {<Title, Bilbo>}
- 26. {<ISBN, 9780140285000 >}
- 29. <Query> ::= <AtomicQuery> [<OptionalQuery>]
- 30. …
- 31. <CheckboxGroup> ::= <Checkbox> | ADJ(<Checkbox>, <CheckboxGroup>)
- 32. Used to determine if Query is valid
- 34. System overview
- 36. Exploit proper subset property
- 37. Start with empty set and add attributes, stop at acceptance
- 40. Large result page size
- 42. Similarity to original search interface
- 43. Small result page size
- 45. TEL-I dataset
- 46. Total of 64 sources
- 47. Result
- 49. Bigger dataset
Editor's Notes
- blabla
- Functional Attribute – only affects the display of results Range Attribute – specifies a range, for example price or year Categorical Attribute – fixed set of distinct value, usually selections lists Value-Infinite Attribute – Infinite number of possible values, typically textboxes Value-Infinite can be categorized into more types, like phone-number, zip code, etc. Not addressed in this paper
- Enough to fill in one field
- A query is deemed accepted even if it returns no results Goal is find the types of queries that are accepted
- First extract HTML form and output XML Feed into Query Capability Analyzer Submit Queries and get result Output is a set of atomic queries
- Recall is lower than precision Method is conservative, if no strong evidence the system treats as rejected