Ontology-based question understanding with the constraint of Spatio-temporal geological knowledge

Li, Wenjia; Wu, Liang; Xie, Zhen; Tao, Liufeng; Zou, Kuanmao; Li, Fengdan; Miao, Jinli

doi:10.1007/s12145-019-00402-2

Cited by 11 publications

(6 citation statements)

References 26 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…At present, unstructured data are stored in different file formats, such as Word, Excel, tables, PDF, etc., and are managed by file-based systems or relational databases [13][14][15]. However, due to the heterogeneous and fragmented nature of unstructured data, using traditional file systems or relational databases to manage the data will lead to inefficient data querying, counting, and updating operations, making it difficult to make effective use of the explicit content information and even more difficult to explore the richer knowledge information implicitly contained in the data [16,17].…”

Section: Introductionmentioning

confidence: 99%

Developing a Base Domain Ontology from Geoscience Report Collection to Aid in Information Retrieval towards Spatiotemporal and Topic Association

Tao,

Ma,

Tian

et al. 2023

IJGI

Self Cite

View full text Add to dashboard Cite

The efficient and precise retrieval of desired information from extensive geological databases is a prominent and pivotal focus within the realm of geological information services. Conventional information retrieval methods primarily rely on keyword matching approaches, which often overlook the contextual and semantic aspects of the keywords, consequently impeding the retrieval system’s ability to accurately comprehend user query requirements. To tackle this challenge, this study proposes an ontology-driven information-retrieval framework for geological data that integrates spatiotemporal and topic associations. The framework encompasses the development of a geological domain ontology, extraction of key information, establishment of a multi-feature association and retrieval framework, and validation through a comprehensive case study. By employing the proposed framework, users are empowered to actively and automatically retrieve pertinent information, simplifying the information access process, mitigating the burden of comprehending information organization and software application models, and ultimately enhancing retrieval efficiency.

show abstract

Section: Introductionmentioning

confidence: 99%

Developing a Base Domain Ontology from Geoscience Report Collection to Aid in Information Retrieval towards Spatiotemporal and Topic Association

Tao,

Ma,

Tian

et al. 2023

IJGI

Self Cite

View full text Add to dashboard Cite

show abstract

“…However, semantic analysis, including data mining and knowledge reasoning [18], is difficult to achieve with these methods, and the potential knowledge implied in massive RS images is still underutilized [19]. The value of RS Big Data lies in the valuable knowledge behind the RS data generated from the multi-temporal [20], multi-level [21], and multi-faceted [22] reflection of the earth's surface. Therefore, how to mine the relevant knowledge efficiently and intelligently from RS Big Data remains a topic of interest.…”

Section: Introductionmentioning

confidence: 99%

Remote Sensing Image Interpretation With Semantic Graph-Based Methods: A Survey

Sun

Dustdar

Ranjan

et al. 2022

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

View full text Add to dashboard Cite

With the significant improvements in Earth observation (EO) technologies, remote sensing (RS) data exhibit the typical characteristics of Big Data. Propelled by the powerful feature extraction capabilities of intelligent algorithms, remote sensing image interpretation has drawn remarkable attention and achieved progress. However, the semantic relationship and domain knowledge hidden in massive RS images have not been fully exploited. To the best of our knowledge, a comprehensive review of recent achievements regarding semantic graph-based methods for comprehension and interpretation of remote sensing images is still lacking. Specifically, this article discusses the main challenges of remote sensing image interpretation and presents a systematic survey of typical semantic graph-based methodologies for RS knowledge representation and understanding, including the Ontology Model, Geo-Information Tupu, and Semantic Knowledge Graph. Furthermore, we categorize and summarize how the existing technologies address different challenges in RS image interpretation based on semantic graph-based methods, which indicates that the semantic information about potential relationships and prior knowledge of variant RS targets are central to the solution. In addition, a case study of RS geological interpretation based on the semantic knowledge graph is demonstrated to show the promising capability of intelligent RS image interpretation. Finally, the future directions are discussed for further research.

show abstract

“…Indeed, quarrying is the basis of all infrastructures. We need only recall its geological definition to understand this [3]. It is an artificial excavation, generally open to the sky, used to extract building materials (limestone, granite, gypsum, sand [4] [5].…”

Section: Introductionmentioning

confidence: 99%

Impact of Limestone Deposit Operation on the Yield of Surrounding Agricultural Land: Case of the Western Rif, Morocco

et al. 2022

View full text Add to dashboard Cite

The exploitation of the limestone deposit is carried out in the open air. Its exploitation process has obvious effects on its environment, and in particular on agricultural production in neighboring lands, by suspending fine particles of matter in the air, which can potentially settle in the soil and the water. The latter being essential resources in the agricultural production process. The analysis of the quality of these resources located near the exploited zone as well as in a control zone (reference zone), both located at the level of the mountain of Haouz, of the western Rif, made it possible to assess the ’impact of the exploitation of the limestone deposit on the physico-chemical characteristics of soils and surface water. Soil and water samples were taken in these areas. The results of these analyzes made it possible to assess the level of soil fertility at each identified sampling point, as well as the characterization of surface water intended for irrigation. The results revealed that this exploitation leads to a significant modification of the soil profile of the neighboring agricultural lands, making them less fertile. This exploitation also causes a hardening of the surface layer of the soil, favoring the phenomenon of encrustation of the soil. The only positive point is that surface water is endowed with essential nutrients such as magnesium and phosphorus originating from the dust emitted during the extraction of limestone. An excessive presence of suspended matter could be accompanied by an increase in pH and thus promote the phenomenon of encrustation of soils when they are irrigated. This reveals that the exploitation of the deposits has generally negative physical and chemical impacts on the soil and consequently on agricultural production.

show abstract

Ontology-based question understanding with the constraint of Spatio-temporal geological knowledge

Cited by 11 publications

References 26 publications

Developing a Base Domain Ontology from Geoscience Report Collection to Aid in Information Retrieval towards Spatiotemporal and Topic Association

Developing a Base Domain Ontology from Geoscience Report Collection to Aid in Information Retrieval towards Spatiotemporal and Topic Association

Remote Sensing Image Interpretation With Semantic Graph-Based Methods: A Survey

Impact of Limestone Deposit Operation on the Yield of Surrounding Agricultural Land: Case of the Western Rif, Morocco

Contact Info

Product

Resources

About