Semantic Search Tools Based on Ontological Representations of Documentary Information

Maksimov, N. V.; Golitsina, O. L.; Monankov, K. V.; Лебедев, А. А.; Bal, N. A.; Kyurcheva, S. G.

doi:10.3103/s0005105519040046

Cited by 10 publications

(6 citation statements)

References 11 publications

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“…From a visual and perceptual standpoint, this allows the graph's dimensionality to be reduced to a more manageable level. Keyword or shallow semantic parsing, the two most common efficient and reliable cipher text search techniques, cannot fully meet users' search intents [32]. It outperforms most current RGB-D networks because of its high accuracy and fast inference speed of 22 Hz at full 2048 1024 resolution.…”

Section: Related Workmentioning

confidence: 99%

Feature Extraction of English Semantic Translation Relying on Graph Regular Knowledge Recognition Algorithm

Yang

2023

IJCAI

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Under the background of big data, people are not only pursuing the quantity but also the accuracy of knowledge in acquiring knowledge, especially for English. Because of the ambiguity, variety, and irregularity of English translation, people's reading has brought a lot of trouble. This paper aims to study the feature extraction of English semantic translation and suggests a recognition algorithm that relies on graph common knowledge. Through the analysis of graph regularization and the construction of the model, the recognition algorithm is improved, and the feature extraction methods are compared and analyzed. At the same time, experiments are intended to investigate the improvement of the English semantic translation of the improved recognition algorithm after feature extraction. The experimental results in this paper show that the improved English semantic translation has increased by 10%-15% in terms of translation accuracy. This degree of improvement has great application significance in actual English semantic translation.Povzetek: Opisana je raziskava izboljšav angleškega semantičnega prevoda z uporabo izboljšanega algoritma prepoznavanja značilnosti.

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Section: Related Workmentioning

confidence: 99%

Feature Extraction of English Semantic Translation Relying on Graph Regular Knowledge Recognition Algorithm

Yang

2023

IJCAI

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“…Some researchers proposed interfaces by adapting visualisation, categorisation, or clustering methods to foster learning and browsing when conducting exploratory searches [1,5,13,14,18,19]. Other researchers used ontology or knowledge graphs as "navigation maps, " [10,17] or as tools to help searchers when crafting queries [6]. Despite the increased interest in exploratory search and designing interfaces to help and support users who conduct exploratory strategies, there is still room for improvement.…”

Section: Motivation and Related Workmentioning

confidence: 99%

“…Some researchers worked on using ontology graphs as a "navigation map". For example, Maksimov et al [10] built an ontology based on a set of documents relevant to a search topic. Hoper et al [6] used a concept knowledge base to help searchers who struggle with crafting queries by generating a query space that represents the query terms concerning the concepts searchers describe.…”

Section: Phase 2: Toward Better Support Interfacesmentioning

confidence: 99%

Towards Understanding and Supporting Exploratory Searches

Soufan

2023

Proceedings of the 2023 Conference on Human Information Interaction and Retrieval

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Exploratory search is an intuitive concept in interactive information retrieval. It is known that searchers use exploratory search strategies when learning and investigating a new domain. Many definitions for Exploratory Search have been proposed. However, the main dimensions involve high uncertainty with respect to the problem context, the user expertise, and the search process. In this work, we study exploratory search in the literature, and we provide a conceptual model of exploratory search. We also conduct a user study to examine how literature searches are exploratory and what factors influence the exploratory dimensions and characteristics. Moreover, we review the exploratory support tasks, and we try to better design and evaluate exploratory user interfaces. CCS CONCEPTS• Information systems → Search interfaces.

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“…The library indexes can utilize similar web-available vocabularies for listing and increasing things with the most applicable terms for the space of concept hierarchy. At that point, web search tools [43] can utilize similar vocabularies in their pursuit to guarantee that the most applicable data details are returned. Figure 5 illustrates the concept of digital libraries.…”

Section: Semantic Web and Digital Librariesmentioning

confidence: 99%

A Contemporary Review on Utilizing Semantic Web Technologies in Healthcare, Virtual Communities, and Ontology-Based Information Processing Systems

Narayanasamy

Srinivasan

et al. 2022

Electronics

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The semantic web is an emerging technology that helps to connect different users to create their content and also facilitates the way of representing information in a manner that can be made understandable for computers. As the world is heading towards the fourth industrial revolution, the implicit utilization of artificial-intelligence-enabled semantic web technologies paves the way for many real-time application developments. The fundamental building blocks for the overwhelming utilization of semantic web technologies are ontologies, and it allows sharing as well as reusing the concepts in a standardized way so that the data gathered from heterogeneous sources receive a common nomenclature, and it paves the way for disambiguating the duplicates very easily. In this context, the right utilization of ontology capabilities would further strengthen its presence in many web-based applications such as e-learning, virtual communities, social media sites, healthcare, agriculture, etc. In this paper, we have given the comprehensive review of using the semantic web in the domain of healthcare, some virtual communities, and other information retrieval projects. As the role of semantic web is becoming pervasive in many domains, the demand for the semantic web in healthcare, virtual communities, and information retrieval has been gaining huge momentum in recent years. To obtain the correct sense of the meaning of the words or terms given in the textual content, it is deemed necessary to apply the right ontology to fix the ambiguity and shun any deviations that persist on the concepts. In this review paper, we have highlighted all the necessary information for a good understanding of the semantic web and its ontological frameworks.

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Semantic Search Tools Based on Ontological Representations of Documentary Information

Cited by 10 publications

References 11 publications

Feature Extraction of English Semantic Translation Relying on Graph Regular Knowledge Recognition Algorithm

Feature Extraction of English Semantic Translation Relying on Graph Regular Knowledge Recognition Algorithm

Towards Understanding and Supporting Exploratory Searches

A Contemporary Review on Utilizing Semantic Web Technologies in Healthcare, Virtual Communities, and Ontology-Based Information Processing Systems

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