Study On The Environment Big-Data Heterogeneous Information Fusion

In the era of big data,there are many types of data,and the scale of data is increasing day by day.The need to obtain higher utilization value from these data becomes more urgent.There is no method to measure the information contained in big data,and big data analysis urgently needs to unify a variety of data sources.Obviously,the traditional information processing method cannot complete the task well.Due to the large differences in the structure of data,the wide range of data sources,and the low-value density of data,the use of big data has created great challenges,and multi-source heterogeneous information is fused for information acquisition,organization,and organization in a big data environment.Utilization provides very effective means and methods.For the fusion of heterogeneous information,constructing an ontology-based knowledge map is an effective method.Ontology is a formal description of a shared conceptual model,which can formally describe information in the environmental domain.This formal description can mine hidden information through automatic reasoning.Knowledge graphs use the semantic network of relationships between entities to make knowledge more shareable and efficient.Therefore,the use of ontology-based knowledge maps to fuse various types of information in the environmental field can integrate various types of data for analysis.Aiming at the above problems,this paper uses the top-down knowledge map to construct the theoretical basis,optimize the extraction of triples in short texts,and display the prototype new system application in the environmental knowledge map collection.First,the process of constructing general knowledge graphs is improved,and the ontology modeling tool protege is used to construct the ontology of the environmental information field.Second,for text data,the basic triples are extracted using the syntactic dependency extraction method,and the general knowledge graph and the special domain knowledge graph are fused,And stored it in the Neo4 j graphic database to initially build a knowledge map of the environment data field.Finally,a prototype of an environment knowledgemap collection and display system was designed and developed to store and manage the knowledge of the environmental field.This subject studies data fusion and knowledge maps,and establishes a foundation for the collection and management of heterogeneous environmental data information.First,the basic data types are modeled based on the ontology modeling method to solve the problem of partial heterogeneous data fusion.Second,the information in the short text can be extracted through the triple extraction of short text to achieve the information extraction of text.To solve the problem of difficult storage and utilization of large texts;third,by combining various types of environmental data and knowledge maps,and using the display interface provided by the front-end display technology,various environmental information can be obtained intuitively,providing environmental decision Decision basis.