Falcon-AO: Aligning Ontologies with Falcon
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Falcon-AO is a tool that aligns ontologies using two matching techniques: 1. LMO performs linguistic matching using techniques like string similarity, document similarity, and term weighting in a vector space model. 2. GMO performs graph matching using a bipartite graph model and similarity accumulation. The tool was tested on a number of ontology matching tasks and achieved high accuracy, recall, and precision on tasks with high linguistic comparability, demonstrating its effectiveness at ontology alignment.
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Presented at WWW'15, Florence.
Gong Cheng, Danyun Xu, Yuzhong Qu. Summarizing Entity Descriptions for Effective and Efficient Human-centered Entity Linking. In Proceedings of the 24th International World Wide Web Conference (WWW), pages 184--194, 2015.
Explass: Exploring Associations between Entities via Top-K Ontological Patter...
This document describes Explass, a system for exploring associations between entities via top-k ontological patterns and facets. It discusses challenges in exploring the over 1,000 associations within 4 hops in DBpedia and proposes two exploration methods: clustering associations into patterns and using entity/property classes as facets. The key steps involve mining significant patterns as frequent itemsets and selecting k patterns based on frequency, informativeness, and overlap. A demo of Explass on DBpedia is presented along with results of a user study comparing it to other approaches.
Facilitating Human Intervention in Coreference Resolution with Comparative En...
The document presents a method for facilitating human intervention in coreference resolution by providing comparative entity summaries. It describes using properties and values of candidate coreferent entities to generate summaries that reflect their commonality and differences. The optimal summary maximizes commonality, difference, identity information and diversity, subject to a length limit. An evaluation involved human subjects verifying coreferent relationships for different summarization approaches. The comparative summary approach was found to improve verification efficiency without affecting accuracy as much as only showing common properties or entire descriptions.
Towards Exploratory Relationship Search: A Clustering-based Approach
This document presents an approach for exploratory relationship search through hierarchical clustering. It aims to address the challenge of too many relationship search results by organizing them into a cluster hierarchy based on common relationship patterns. An evaluation with participants performing lookup and exploratory search tasks on DBpedia data found that the clustering approach outperformed simple listing and faceted categorization alternatives. User feedback suggested areas for improvement like more concise visualizations and cognitive support. The authors conclude it is a promising approach and future work could combine facets and clustering or explore alternatives.
More from Gong Cheng (20)
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Generating Illustrative Snippets for Open Data on the Web
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HIEDS: A Generic and Efficient Approach to Hierarchical Dataset Summarization
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Taking up the Gaokao Challenge: An Information Retrieval Approach
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Summarizing Entity Descriptions for Effective and Efficient Human-centered En...
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Explass: Exploring Associations between Entities via Top-K Ontological Patter...
Explass: Exploring Associations between Entities via Top-K Ontological Patter...
Facilitating Human Intervention in Coreference Resolution with Comparative En...
Facilitating Human Intervention in Coreference Resolution with Comparative En...
Towards Exploratory Relationship Search: A Clustering-based Approach
Towards Exploratory Relationship Search: A Clustering-based Approach
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Direct losses from downtime in 1 minute = $5-$10 thousand dollars. Reputation is priceless.
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We will focus special attention on the architectural patterns used in the design of the fintech system, microservices and event-driven architecture, which ensure scalability, fault tolerance, and consistency of the entire system.
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Read Taking AI to the Next Level in Manufacturing to gain insights on AI adoption in the manufacturing industry, such as:
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Folding is a recent technique for building efficient recursive SNARKs. Several elegant folding protocols have been proposed, such as Nova, Supernova, Hypernova, Protostar, and others. However, all of them rely on an additively homomorphic commitment scheme based on discrete log, and are therefore not post-quantum secure. In this work we present LatticeFold, the first lattice-based folding protocol based on the Module SIS problem. This folding protocol naturally leads to an efficient recursive lattice-based SNARK and an efficient PCD scheme. LatticeFold supports folding low-degree relations, such as R1CS, as well as high-degree relations, such as CCS. The key challenge is to construct a secure folding protocol that works with the Ajtai commitment scheme. The difficulty, is ensuring that extracted witnesses are low norm through many rounds of folding. We present a novel technique using the sumcheck protocol to ensure that extracted witnesses are always low norm no matter how many rounds of folding are used. Our evaluation of the final proof system suggests that it is as performant as Hypernova, while providing post-quantum security.
Paper Link: https://eprint.iacr.org/2024/257
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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
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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
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Mydbops Opensource Database Meetup 16
Topic: Must-Know PostgreSQL Extensions for Developers and DBAs During Migration
Speaker: Deepak Mahto, Founder of DataCloudGaze Consulting
Date & Time: 8th June | 10 AM - 1 PM IST
Venue: Bangalore International Centre, Bangalore
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* Don't miss this chance to gain practical knowledge from an industry expert and stay updated on the latest open-source database trends.
Mydbops Managed Services specializes in taking the pain out of database management while optimizing performance. Since 2015, we have been providing top-notch support and assistance for the top three open-source databases: MySQL, MongoDB, and PostgreSQL.
Our team offers a wide range of services, including assistance, support, consulting, 24/7 operations, and expertise in all relevant technologies. We help organizations improve their database's performance, scalability, efficiency, and availability.
Contact us: info@mydbops.com
Visit: https://www.mydbops.com/
Follow us on LinkedIn: https://in.linkedin.com/company/mydbops
For more details and updates, please follow up the below links.
Meetup Page : https://www.meetup.com/mydbops-databa...
Twitter: https://twitter.com/mydbopsofficial
Blogs: https://www.mydbops.com/blog/
Facebook(Meta): https://www.facebook.com/mydbops/
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Main news related to the CCS TSI 2023 (2023/1695)
An English 🇬🇧 translation of a presentation to the speech I gave about the main changes brought by CCS TSI 2023 at the biggest Czech conference on Communications and signalling systems on Railways, which was held in Clarion Hotel Olomouc from 7th to 9th November 2023 (konferenceszt.cz). Attended by around 500 participants and 200 on-line followers.
The original Czech 🇨🇿 version of the presentation can be found here: https://www.slideshare.net/slideshow/hlavni-novinky-souvisejici-s-ccs-tsi-2023-2023-1695/269688092 .
The videorecording (in Czech) from the presentation is available here: https://youtu.be/WzjJWm4IyPk?si=SImb06tuXGb30BEH .
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Falcon-AO: Aligning Ontologies with Falcon
- 7. Architecture of Falcon-AO Linguistic Comparability & Structural Comparability
- 8. Results Low High Linguistic Comparability 5s 1.00 1.00 1.00 #101 - #104 0.86 0.63 0.99 0.95 Average F-Measure 20s 60s 4s 63s Average Run Time 0.81 0.93 #301 - #304 0.60 0.71 #248 - #266 1.00 0.99 #221 - #247 0.95 0.96 #201 - #210 Average Recall Average Precision Test Cases