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

Explore how Vector-Space (Distributional) Lexical Semantics represent word meanings as points in a high-dimensional space. Learn about Semantic similarity, creating sample lexical vector spaces, and using word vectors to measure semantic relatedness. Discover how other contextual features and featur

0 views • 33 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

Explore the importance of text similarity in NLP, how it aids in understanding related concepts and processing language, human judgments of similarity, automatic similarity computation using word embeddings like word2vec, and various types of text similarity such as semantic, morphological, and sent

3 views • 8 slides

Analyzing the concept of structural similarity within Information Networks (INs), the study introduces P-Rank as a more advanced alternative to SimRank. By addressing the limitations of SimRank and offering a more efficient computational approach, P-Rank aims to provide a comprehensive measure of si

0 views • 17 slides

Investigating the impact of semantic knowledge and similarity on verbal short-term memory, this study delves into how imageability of words influences recall. Key findings highlight the influence of semantic relatedness and the imageability effect on memory retention, shedding light on the mechanism

0 views • 47 slides

Polarity-Inducing Latent Semantic Analysis (PILSA) introduces a novel vector space model that distinguishes antonyms from synonyms. By encoding polarity information, synonyms cluster closely while antonyms are positioned at opposite ends of a unit sphere. Existing models struggle with finer distinct

1 views • 29 slides

This content discusses the concepts of structural equivalence and regular equivalence in network analysis. Structural equivalence is based on shared network neighbors, while regular equivalence considers the similarities of neighboring vertices. Various measures, such as cosine similarity and Pearso

0 views • 12 slides

Explore the world of Artificial Intelligence through CS188 course slides by Dan Klein and Pieter Abbeel at the University of California, Berkeley. Dive into topics like Case-Based Learning, Nearest-Neighbor Classification, Parametric vs. Non-Parametric models, Similarity Functions, and more. Discove

0 views • 41 slides

Explore the concept of similarity and distance in data analysis, major clustering techniques, and algorithms. Learn how similarity is essential in decision-making methods and predictive modeling, such as using nearest neighbors for classification and regression. Discover (dis)similarity functions, n

0 views • 35 slides

This project focuses on developing a system to provide top-k similar regions on a map based on user-specified query regions. By incorporating content and spatial similarity measures, the algorithm aims to accurately retrieve regions with similar shapes, scales, and representative categories. Challen

0 views • 12 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

Explore practice questions demonstrating the similarity of triangles based on angle relationships. Understand how to prove similarity using given angle measurements in various triangle configurations. Delve into the concept of similar triangles through visual examples and step-by-step solutions.

0 views • 34 slides

Exploring the concepts of similarity and distance in data mining is crucial for tasks like finding similar items, grouping customers, and detecting near-duplicate documents. Metrics like Jaccard similarity help quantify similarities between sets of data objects, enabling effective analysis and decis

0 views • 46 slides

Data mining involves quantifying the closeness of objects through similarity and distance measures. These measures are crucial for various tasks like recommending similar items, grouping customers, and detecting duplicates in web documents. Similarity metrics ensure objects are ranked correctly base

0 views • 65 slides

This research explores improving similarity measures for short text segments, essential for various applications such as query suggestions, keyword expansion in online ads, and web search ranking. Challenges like non-overlapping segments and ambiguous terms are addressed, with contributions includin

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

Explore the importance of string similarity search in handling dirty data, with applications in duplicate detection, spelling correction, and bioinformatics. Learn about similarity measurement using edit distance and the challenge of time complexity in validation. Discover the filter-and-verificatio

0 views • 30 slides

Explore the world of Natural Language Processing (NLP) through images and explanations, covering topics such as text similarity, dimensionality reduction, semantic matching, and the challenges with vector similarity. Dive into the concept space, TOEFL synonyms, SAT analogies, and the importance of r

0 views • 39 slides

Explore various text similarity techniques in Natural Language Processing (NLP), including word order, length, synonym, spelling, word importance, and word frequency considerations. Topics covered include bag-of-words representation, vector-based word similarities, TF-IDF weighting scheme, normalize

2 views • 62 slides

Explore the process of representing text as numerical vectors using approaches like Bag of Words and Latent Semantic Analysis for quantifying text similarity. Dive into clustering methods like k-means clustering and stream clustering to group data points based on similarity patterns. Learn about app

0 views • 25 slides

This content delves into understanding triangle congruence and similarity through various scenarios and visual representations. It discusses how to determine congruence using side-side-side, side-angle-side, and angle-side-angle criteria, and explores the concept of similarity in triangles based on

0 views • 21 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

An exploration of how semantic technologies facilitate data management, knowledge extraction, and understanding in the realm of big data. Topics covered include semantic graphs, content information extraction, and the impact of semantic models on enhancing data value and relationships. The importanc

0 views • 38 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

Delve into the realm of neural semantic parsing with a focus on data recombination techniques, traditional parsers, and the shift towards domain-general models. Explore the application of sequence-to-sequence models and attention-based neural frameworks in semantic parsing tasks. Discover the evolvi

0 views • 67 slides

Explore term-weighting functions for similarity measures in information retrieval, focusing on TFIDF vectors, vector-based similarity measures, and the TWEAK learning framework for fine-tuning similarity metrics.

0 views • 22 slides