Item handling intelligent recommendation method based on data graph and service graph
A recommendation method and map technology, applied in the field of map-based item recommendation, can solve the problems of lack of understanding, high error rate of guide information, inconvenient use, etc., and achieve the effect of improving accuracy and reducing the interaction process
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Embodiment 1
[0063] This embodiment provides a Figure 4-6 The shown intelligent recommendation method for handling matters based on data graph and business graph includes the following steps:
[0064] Step S1, constructing a data map ontology;
[0065] Extract vocabulary related to the ontology model from several government affairs policy documents, organize the vocabulary in the form of a relational network including several connecting lines, and form an ontology model; import the ontology model into a graph database; The vocabulary related to the model refers to the element information related to government services, including handling materials, handling materials, handling agencies, parties, and rule labels. The relationship network diagram of the above-mentioned several connecting lines is the reference relationship between the elements of government services.
[0066] Taking "Registration of Adopted Children" as an example, the extraction method is as follows:
[0067] As a "gover...
Embodiment 2
[0101] This embodiment provides a Figure 7-8 The steps S1-S3 of the shown intelligent recommendation method for handling matters based on the data graph and business graph are the same as those in the embodiment, and will not be repeated here. Steps S4-S5 are also included after steps S1-S3, specifically as follows:
[0102] Step S4, business map data update;
[0103] After the parties complete the scheduled matters, the status and relationship of the parties change, and the data of the business graph is updated.
[0104] Step S5, recommending potentially actionable items;
[0105] After the data related to the business map is updated, the data is regrouped into big data, and the status or relationship of the parties changes. Combined with the dependencies between the items, other items that can potentially be handled are automatically recommended.
[0106] Among them, automatic recommendation methods such as Figure 8 shown, including:
[0107] Step S501, inputting the ...
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