Research on an Agricultural Knowledge Fusion Method for Big Data
| Autor: | Fenglei Guo, Bingxian Ma, Wei Sun, Zhang Xuefu, Wensheng Wang, Nengfu Xie |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2015 |
| Předmět: |
Information retrieval
Ontology business.industry Computer science Ontology-based data integration Big data Agriculture Knowledge fusion Ontology (information science) Inconsistency Sensor fusion Data science Computer Science Applications Information integration Identification (information) Knowledge extraction Computer Science (miscellaneous) lcsh:Science (General) business Semantic Web lcsh:Q1-390 |
| Zdroj: | Data Science Journal; Vol 14 (2015); 7 Data Science Journal, Vol 14 (2015) |
| ISSN: | 1683-1470 |
| Popis: | The object of our research is to develop an ontology-based agricultural knowledge fusion method that can be used as a comprehensive basis on which to solve agricultural information inconsistencies, analyze data, and discover new knowledge. A recent survey has provided a detailed comparison of various fusion methods used with Deep Web data (Li, 2013). In this paper, we propose an effective agricultural ontology-based knowledge fusion method by leveraging recent advances in data fusion, such as the semantic web and big data technologies, that will enhance the identification and fusion of new and existing data sets to make big data analytics more possible. We provide a detailed fusion method that includes agricultural ontology building, fusion rule construction, an evaluation module, etc. Empirical results show that this knowledge fusion method is useful for knowledge discovery. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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