Search Results for author: Vuong M. Ngo

Found 7 papers, 0 papers with code

Structural Textile Pattern Recognition and Processing Based on Hypergraphs

no code implementations21 Mar 2021 Vuong M. Ngo, Sven Helmer, Nhien-An Le-Khac, M-Tahar Kechadi

For instance, digital archives for textiles offer keyword search, which is fairly well understood, and arrange their content following a certain taxonomy, but search functionality at the level of thread structure is still missing.

Clustering Retrieval

Crop Knowledge Discovery Based on Agricultural Big Data Integration

no code implementations11 Mar 2020 Vuong M. Ngo, M-Tahar Kechadi

Nowadays, the agricultural data can be generated through various sources, such as: Internet of Thing (IoT), sensors, satellites, weather stations, robots, farm equipment, agricultural laboratories, farmers, government agencies and agribusinesses.

Data Integration

A Similarity Measure for Weaving Patterns in Textiles

no code implementations10 Oct 2018 Sven Helmer, Vuong M. Ngo

We propose a novel approach for measuring the similarity between weaving patterns that can provide similarity-based search functionality for textile archives.

A Generalized Vector Space Model for Ontology-Based Information Retrieval

no code implementations20 Jul 2018 Vuong M. Ngo, Tru H. Cao

Named entities (NE) are objects that are referred to by names such as people, organizations and locations.

Information Retrieval Retrieval

WordNet-Based Information Retrieval Using Common Hypernyms and Combined Features

no code implementations15 Jul 2018 Vuong M. Ngo, Tru H. Cao, Tuan M. V. Le

Experiments on a benchmark dataset show that, in terms of the MAP measure, our search engine is 17. 7% better than the lexical search, and at least 9. 4% better than all surveyed search systems using WordNet.

Information Retrieval Retrieval +1

Ontology-Based Query Expansion with Latently Related Named Entities for Semantic Text Search

no code implementations15 Jul 2018 Vuong M. Ngo, Tru H. Cao

It exploits ontological features of named entities and their latently related ones to reveal the semantics of documents and queries.

Information Retrieval Retrieval

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