Delve into the depths of Semantic Web technologies with a focus on RDFa, GRDDL, and POWDER through the guidance of Dr. Nicholas Gibbins. Learn about embedding Semantic Web data, republishing embedded data, and the usage of GRDDL for XML transformations.

13 views • 38 slides

An intriguing mathematical problem is presented where new faculty members at TIMS must be assigned to coffee lounge alcoves in a way that ensures no two new members meet after the first day. By constructing a graph based on meet-up timings, analyzing clashes, and determining intervals, this scenario

1 views • 19 slides

In this study by Uriel Feige and Roee David from the Weizmann Institute, the effect of randomness on planted 3-coloring models is investigated. The research delves into the NP-hard nature of 3-coloring problems, introducing a hosted coloring framework that involves choices like the host graph and th

0 views • 55 slides

This research discusses the challenges in managing large graphs on multi-core systems and introduces Grace, an in-memory graph management and processing system with optimizations for graph-specific and multi-core-specific operations. The system keeps the entire graph in memory in smaller parts and p

0 views • 14 slides

Semantic Web technologies such as RDF, RDFS, OWL, and SPARQL form the basis of a web of data designed for machine understanding. Knowledge representation languages play a crucial role in AI, with Semantic Web languages like OWL leading the current generation. Contrasting database and knowledge base

0 views • 50 slides

Maria's bike journey graph depicts her distance from home as she rode to meet friends and run errands before returning home. The graph shows her stops for errands, changes in direction, and her path back home. By interpreting the key features of the graph, such as intercepts and intervals, we can an

0 views • 15 slides

This research delves into multimodal semantic indexing methods for image retrieval, focusing on extending Latent Semantic Indexing (LSI) and probabilistic LSI to a multi-modal setting. Contributions include the refinement of graph models and partitioning algorithms to enhance image retrieval from tr

1 views • 28 slides

Balanced graph edge partitioning is a crucial problem in graph computation, machine learning, and graph databases. It involves partitioning a graph's vertices or edges into balanced components while minimizing cut costs. This process is essential for various real-world applications such as iterative

0 views • 17 slides

This research delves into the cutting-edge topic of query-driven on-the-fly knowledge base construction, focusing on acquiring facts for a vast array of predicates and capturing billions of facts about entities in the world. Motivated by the limitations of existing knowledge bases, the study explore

0 views • 49 slides

Explore the concept of spanning trees and minimum spanning trees in graph theory through an in-depth lecture outline covering topics like Cut Property, Cycle Property, Kruskal's Algorithm, and more. Delve into the significance of Minimum Spanning Trees (MSTs) as the lowest-cost spanning tree of a gr

0 views • 41 slides

Graph pattern matching in social networks presents challenges such as costly queries, excessive results, and query focus issues. The complexity of top-k and diversified pattern matching problems requires heuristic algorithms for efficient solutions. Finding best candidates for project roles involves

0 views • 19 slides

Aphasia often involves semantic breakdown, and Semantic Feature Analysis (SFA) is a foundational technique for various treatments addressing semantic impairments. This presentation explores the effectiveness of SFA in improving naming, generalization to spontaneous speech, and treatment goals beyond

0 views • 16 slides

In this detailed piece, Subhash Khot, Dor Minzer, Dana Moshkovitz, and Muli Safra explore the fascinating concept of Small Set Expansion in Johnson Graphs. The Johnson Graph is defined as a representation where nodes are sets of size K in a universe of size N, and two sets are connected if they inte

0 views • 14 slides

Seastar presents a vertex-centric programming approach for Graph Neural Networks, showcasing better performance in graph analytic tasks compared to traditional methods. The research introduces the SEAStar computation pattern and discusses GNN programming abstractions, execution, and limitations. Dee

0 views • 17 slides

Explore testable bounded degree graph properties, sparse graphs, d-bounded degree graphs, hyperfinite graphs, arboricity, maximum matching algorithms, and sublinear time approximation algorithms in graph data streams. Learn about various graph models and properties with examples, showcasing the impo

0 views • 53 slides

Explore the world of graph modeling and DFS applications through lectures on graph vocabulary, edge classification in directed graphs, and the use of DFS to find cycles. Discover the significance of tree edges, back edges, forward edges, and cross edges in graph traversal. Learn how DFS can be utili

0 views • 32 slides

This content delves into graph-based knowledge representation in modelling, detailing concepts such as recipe-ingredient relationships, formalisms for generalizing graph representation, and conceptual graphs by John F. Sowa. It explores how different interpretations describe the association between

0 views • 19 slides

Graph databases offer a flexible way to manage data by representing relationships between nodes. Neo4j is a popular graph database system that uses Cypher for querying. This guide provides insights into graph database concepts, advantages, and getting started with Neo4j, including creating nodes and

0 views • 39 slides

Presented by Manvitha Nellore, this content addresses real-world train track problems in busy cities by proposing solutions through interval graphs and graph theory. The approach involves allotting tracks to trains by scheduling with time intervals to avoid conflicts. An interval graph is defined, a

0 views • 15 slides

Miguel Figueres-Esteban, a Telecommunications Engineer with a PhD in Psychology, leads the Digital Transformation and Training at Renfe. He is instrumental in developing a Safety Enterprise Architecture and a Safety Knowledge Graph to enhance risk management in railway safety. Renfe, under his leade

0 views • 4 slides

This chapter delves into semantic issues in translation, aiming to assist students in annotating their translations from a semantic viewpoint. It emphasizes using semantic information to aid in translating data accurately while maintaining communicative effectiveness. The story discussed highlights

0 views • 19 slides

This content delves into the preprocessing, computing, post-processing, and analysis of raw XML data for graph-based algorithms. It covers topics such as data ETL, graph analytics, PageRank computation, and identifying top users. Various tools and frameworks like GraphX, Spark, Giraph, and GraphLab

0 views • 8 slides

Explore the critical aspects of semantic interoperability in biobanking, highlighting the need for formal ontologies, comprehensive annotations, and model of meaning data. The (Generalized) Biomedical Retrieval Scenario underscores the importance of effective resource retrieval based on content-base

0 views • 16 slides

Graph algorithms play a crucial role in solving problems represented as networks, maps, paths, plans, and resource flow. This content delves into ways to find connectivity in graphs and algorithms for determining shortest paths. It discusses graph representations using adjacency matrices and lists,

1 views • 32 slides

Exploring the concepts of cliques, independent sets, and theorems in graph theory regarding enemy relationships, maximum number of edges in 3-free graphs, and properties of multipartite graphs. The propositions and theorems discussed shed light on graph structures and their properties, providing val

0 views • 32 slides