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Article
Open AccessA Meta-learner approach to multistep-ahead time series prediction
The utilization of machine learning has become ubiquitous in addressing contemporary challenges in data science. Moreover, there has been significant interest in democratizing the decision-making process for s...
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Article
Open AccessAutomatic detection of weeds: synergy between EfficientNet and transfer learning to enhance the prediction accuracy
The application of digital technologies to facilitate farming activities has been on the rise in recent years. Among different tasks, the classification of weeds is a prerequisite for smart farming, and variou...
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Chapter and Conference Paper
Sentiment Analysis for Vietnamese – Based Hybrid Deep Learning Models
Sentiment analysis of public opinion expressed in social networks has been developed into various applications, especially in English. Hybrid approaches are potential models for reducing sentiment errors on in...
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Article
Open AccessA big data smart agricultural system: recommending optimum fertilisers for crops
Nutrients are important to promote plant growth and nutrient deficiency is the primary factor limiting crop production. However, excess fertilisers can also have a negative impact on crop quality and yield, ca...
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Article
Open AccessStructural textile pattern recognition and processing based on hypergraphs
The humanities, like many other areas of society, are currently undergoing major changes in the wake of digital transformation. However, in order to make collection of digitised material in this area easily ac...
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Chapter and Conference Paper
A Semantic Search Engine for Historical Handwritten Document Images
A very large number of historical manuscript collections are available in image formats and require extensive manual processing in order to search through them. So, we propose and build a search engine for aut...
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Chapter and Conference Paper
Designing and Implementing Data Warehouse for Agricultural Big Data
In recent years, precision agriculture that uses modern information and communication technologies is becoming very popular. Raw and semi-processed agricultural data are usually collected through various sourc...
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Article
Semantic Search by Latent Ontological Features
Both named entities and keywords are important in defining the content of a text in which they occur. In particular, people often use named entities in information search. However, named entities have ontologi...
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Chapter
Ontology-Based Query Expansion with Latently Related Named Entities for Semantic Text Search
Traditional information retrieval systems represent documents and queries by keyword sets. However, the content of a document or a query is mainly defined by both keywords and named entities occurring in it. N...
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Chapter and Conference Paper
Exploring Combinations of Ontological Features and Keywords for Text Retrieval
Named entities have been considered and combined with keywords to enhance information retrieval performance. However, there is not yet a formal and complete model that takes into account entity names, classes,...
