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Knowledge extraction

About: Knowledge extraction is a research topic. Over the lifetime, 20251 publications have been published within this topic receiving 413401 citations.


Papers
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Journal ArticleDOI
TL;DR: An approach to combine visual and computational methods for knowledge discovery in large geospatial data, an integrated visualization‐geocomputation environment has been developed based on the Self‐Organizing Map, the map and the parallel coordinate plot.
Abstract: The use of new representation forms and interactive means to visualize geospatial data requires an understanding of the impact of the visual tools used for data exploration and knowledge construction. Use and usability assessment of implemented methods and tools is an important part of our efforts to build this understanding. Based on an approach to combine visual and computational methods for knowledge discovery in large geospatial data, an integrated visualization‐geocomputation environment has been developed based on the Self‐Organizing Map (SOM), the map and the parallel coordinate plot. This environment allows patterns and attribute relationships to be explored. A use and usability assessment is conducted to evaluate the ability of each of these visual representations to meet user performance and satisfaction goals. In the test, different representations are compared while exploring a socio‐demographic dataset.

145 citations

ReportDOI
TL;DR: Issues associated with Level 2 Information Fusion (Situation Assessment) including: user perception and perceptual reasoning representation, knowledge discovery process models, procedural versus logical reasoning about relationships, userfusion interaction through performance metrics, and syntactic and semantic representations are presented.
Abstract: : Situation assessment (SA) involves deriving relations among entities, e.g., the aggregation of object states (i.e., classification and location). While SA has been recognized in the information fusion and human factors literature, there still exist open questions regarding knowledge representation and reasoning methods to afford SA. For instance, while lots of data is collected over a region of interest, how does this information get presented to an attention constrained user? The information overload can deteriorate cognitive reasoning so a pragmatic solution to knowledge representation is needed for effective and efficient situation understanding. In this paper, we present issues associated with Level 2 Information Fusion (Situation Assessment) including: (1) user perception and perceptual reasoning representation, (2) knowledge discovery process models, (3) procedural versus logical reasoning about relationships, (4) userfusion interaction through performance metrics, and (5) syntactic and semantic representations. While a definitive conclusion is not the aim of the paper, many critical issues are proposed in order to characterize future successful strategies for knowledge representation, presentation, and reasoning for situation assessment.

145 citations

Journal ArticleDOI
TL;DR: The study proposed the ontology-based risk management (ORM) framework to enhance the RM performance by improving the RM workflow and knowledge reuse and demonstrated that the ORM framework greatly increased the effectiveness of project RM.

144 citations

Patent
30 Jun 2006
TL;DR: In this paper, a system and method of making unstructured data available to structured data analysis tools is presented, which includes middleware software that can be used in combination with structured data tools to perform analysis on both structured and unstructural data.
Abstract: A system and method of making unstructured data available to structured data analysis tools. The system includes middleware software that can be used in combination with structured data tools to perform analysis on both structured and unstructured data. Data can be read from a wide variety of unstructured sources. The data may then be transformed with commercial data transformation products that may, for example, extract individual pieces of data and determine relationships between the extracted data. The transformed data and relationships may then be passed through an extraction/transform/load (ETL) layer and placed in a structured schema. The structured schema may then be made available to commercial or proprietary structured data analysis tools.

144 citations

Journal ArticleDOI
01 May 2011
TL;DR: A case study on agrometeorological disasters that occurred in China between 1997 and 2001 demonstrates that the combination of data mining and MCDM methods can provide objective and comprehensive assessments of incident risks.
Abstract: An effective incident information management system needs to deal with several challenges. It must support heterogeneous distributed incident data, allow decision makers (DMs) to detect anomalies and extract useful knowledge, assist DMs in evaluating the risks and selecting an appropriate alternative during an incident, and provide differentiated services to satisfy the requirements of different incident management phases. To address these challenges, this paper proposes an incident information management framework that consists of three major components. The first component is a high-level data integration module in which heterogeneous data sources are integrated and presented in a uniform format. The second component is a data mining module that uses data mining methods to identify useful patterns and presents a process to provide differentiated services for pre-incident and post-incident information management. The third component is a multi-criteria decision-making (MCDM) module that utilizes MCDM methods to assess the current situation, find the satisfactory solutions, and take appropriate responses in a timely manner. To validate the proposed framework, this paper conducts a case study on agrometeorological disasters that occurred in China between 1997 and 2001. The case study demonstrates that the combination of data mining and MCDM methods can provide objective and comprehensive assessments of incident risks.

144 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
2023120
2022285
2021506
2020660
2019740
2018683