CN110222196A - Fishery knowledge mapping construction device, method and computer readable storage medium - Google Patents
Fishery knowledge mapping construction device, method and computer readable storage medium Download PDFInfo
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- CN110222196A CN110222196A CN201910527799.2A CN201910527799A CN110222196A CN 110222196 A CN110222196 A CN 110222196A CN 201910527799 A CN201910527799 A CN 201910527799A CN 110222196 A CN110222196 A CN 110222196A
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- fishery
- entity
- incidence relation
- knowledge mapping
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
- G06F16/36—Creation of semantic tools, e.g. ontology or thesauri
- G06F16/367—Ontology
Abstract
A kind of fishery knowledge mapping construction method, comprising: obtain the fishery FIELD Data of a target area, and extract multiple fishery entities from the fishery FIELD Data, the plurality of fishery entity includes at least fisherman's entity and at least fishery's entity；The incidence relation between multiple fishery entities is established by preset incidence relation method for building up；And according to the incidence relation between each fishery entity and each fishery entity, establish fishery knowledge mapping.The present invention also provides a kind of fishery knowledge mapping construction device and computer readable storage mediums.Above-mentioned fishery knowledge mapping construction device, method and computer readable storage medium are, it can be achieved that construct fishery knowledge mapping, the convenience that the promotion fishery FIELD Data efficiency of management and data use for fishery field.
Description
Technical field
The present invention relates to technical field of data processing more particularly to a kind of fishery knowledge mapping construction devices, method and meter
Calculation machine readable storage medium storing program for executing.
Background technique
Knowledge mapping has powerful data descriptive power, provides technical foundation for intelligent information application, passes through
Implementation of inference conceptual retrieval, while structural knowledge can be presented to user in a manner of patterned.Knowledge mapping is in multiple necks
Domain has application, such as medical treatment, finance, education, investment etc. to have industry existing for relationship.But not yet there is mature fishing at present
Industry knowledge mapping building mode.
Summary of the invention
In view of this, it is necessary to provide a kind of fishery knowledge mapping construction device, method and computer readable storage medium,
It, which can be realized, constructs fishery knowledge mapping for fishery field, and it is convenient that the promotion fishery FIELD Data efficiency of management and data use
Property.
An embodiment of the present invention provides a kind of fishery knowledge mapping construction method, which comprises obtains a target
The fishery FIELD Data in region, and multiple fishery entities are extracted from the fishery FIELD Data, the plurality of fishery is real
Body includes at least fisherman's entity and at least fishery's entity；Multiple institutes are established by preset incidence relation method for building up
State the incidence relation between fishery entity；And according to the association between each fishery entity and each fishery entity
Relationship establishes fishery knowledge mapping.
Preferably, the fishery entity further includes an at least fish class instance, described to mention from the fishery FIELD Data
The step of taking multiple fishery entities includes: extraction fisherman's data from the fishery FIELD Data；And from fisherman's data
Extract an at least fish class instance.
Preferably, the step of incidence relation established between multiple fishery entities includes: that acquisition is each described
The fish classification information of fisherman's entity fishing；Fish classification information based on the fishing establishes fisherman's entity and the fish
Fishing relationship between other entity.
Preferably, the method also includes: updated according to presupposed information and Rule and update the fish class instance
The information of information, the information of fisherman's entity and fishery's entity；And it is based on the updated fish class instance
Information, fisherman's entity information and fishery's entity information are updated the fishery knowledge mapping.
Preferably, the fishery entity further includes an at least fish class instance, the association between multiple fishery entities
Relationship includes incidence relation, fishery's entity and the fish between fishery's entity and fisherman's entity
The incidence relation between incidence relation and fisherman's entity and the fish class instance between class instance.
Preferably, the incidence relation according between each fishery entity and each fishery entity, builds
The step of vertical fishery knowledge mapping includes:
It obtains and is constructed based on the name identification of fishery's entity, fisherman's entity and the fish class instance
Fishery knowledge mapping frame；And
By between fishery's entity and fisherman's entity incidence relation, fishery's entity with it is described
The incidence relation between incidence relation and fisherman's entity and the fish class instance between fish class instance is filled to institute
Fishery knowledge mapping frame is stated, the fishery knowledge mapping is obtained.
Preferably, the incidence relation between fishery's entity and the fish class instance is established by following steps
It obtains:
Obtain the other entity information of fish of fishery's entity sale and/or purchase；
The other entity information of fish sold and/or bought based on fishery's entity, it is real to establish the fishery
Incidence relation between body and the fish class instance.
Preferably, the incidence relation according between each fishery entity and each fishery entity, builds
The step of vertical fishery knowledge mapping includes:
Incidence relation between the name identification of each fishery entity and each fishery entity is directed into
Preset pattern database, and carry out visualization and be converted to the fishery knowledge mapping.
An embodiment of the present invention provides a kind of fishery knowledge mapping construction device, the fishery knowledge mapping construction device
Including processor and memory, several computer programs are stored on the memory, the processor is for executing memory
The step of above-mentioned fishery knowledge mapping construction method is realized when the computer program of middle storage.
An embodiment of the present invention also provides a kind of computer readable storage medium, and the computer readable storage medium is deposited
A plurality of instruction is contained, a plurality of described instruction can be executed by one or more processor, to realize above-mentioned fishery knowledge mapping
The step of construction method.
Compared with prior art, above-mentioned fishery knowledge mapping construction device, method and computer readable storage medium, can be with
It realizes the fishery knowledge mapping in one specified region of building, promotes the convenience that the fishery FIELD Data efficiency of management and data use,
Facilitate the transaction of fishery Yu fisherman both sides, and aid decision can be provided for fishery and fisherman.
Detailed description of the invention
Fig. 1 is the structural schematic diagram of the fishery knowledge mapping construction device of an embodiment of the present invention.
Fig. 2 is the functional block diagram of the fishery knowledge mapping building system of an embodiment of the present invention.
Fig. 3 is the flow chart of the fishery knowledge mapping construction method of an embodiment of the present invention.
Main element symbol description
The present invention that the following detailed description will be further explained with reference to the above drawings.
Specific embodiment
In order to make the objectives, technical solutions, and advantages of the present invention clearer, with reference to the accompanying drawings and embodiments, right
The present invention is further elaborated.It should be appreciated that described herein, specific examples are only used to explain the present invention, not
For limiting the present invention.Based on the embodiments of the present invention, those of ordinary skill in the art are not before making creative work
Every other embodiment obtained is put, shall fall within the protection scope of the present invention.
Explanation is needed further exist for, herein, the terms "include", "comprise" or its any other variant are intended to contain
Lid non-exclusive inclusion, so that process, method, article or device including a series of elements are not only wanted including those
Element, but also including other elements that are not explicitly listed, or further include for this process, method, article or device
Intrinsic element.In the absence of more restrictions, the element limited by sentence "including a ...", it is not excluded that
There is also other identical elements in process, method, article or device including the element.
Referring to Fig. 1, being the schematic diagram of fishery knowledge mapping construction device preferred embodiment of the present invention.
The fishery knowledge mapping construction device 100 is including memory 10, processor 20 and is stored in the memory
In 10 and the computer program 30 that can be run on the processor 20, such as fishery knowledge mapping construction procedures.The processing
Device 20 realizes the step in fishery knowledge mapping construction method embodiment when executing the computer program 30, such as shown in Fig. 3
Step S300~S306.Alternatively, the processor 20 realizes the building of fishery knowledge mapping when executing the computer program 30
The function of each module in system embodiment, such as the module 101~104 in Fig. 2.
The computer program 30 can be divided into one or more modules, and one or more of modules are stored
It is executed in the memory 10, and by the processor 20, to complete the present invention.One or more of modules can be energy
The series of computation machine program instruction section of specific function is enough completed, described instruction section is for describing the computer program 30 in institute
State the implementation procedure in fishery knowledge mapping construction device 100.For example, the computer program 30 can be divided into Fig. 2
Extraction module 101, first establish module 102, second establish module 103 and update module 104.Each module concrete function referring to
Fishery knowledge mapping constructs the function of each module in system embodiment.
The fishery knowledge mapping construction device 100 can be computer, server etc. and calculate equipment.Those skilled in the art
It is appreciated that the schematic diagram is only the example of fishery knowledge mapping construction device 100, do not constitute to fishery knowledge mapping structure
The restriction for building device 100 may include perhaps combining certain components or different portions than illustrating more or fewer components
Part, such as the fishery knowledge mapping construction device 100 can also include input-output equipment, network access equipment, bus etc..
Alleged processor 20 can be central processing unit (Central Processing Unit, CPU), can also be
Other general processors, digital signal processor (Digital Signal Processor, DSP), specific integrated circuit
(Application Specific Integrated Circuit, ASIC), ready-made programmable gate array (Field-
Programmable Gate Array, FPGA) either other programmable logic device, discrete gate or transistor logic,
Discrete hardware components etc..General processor can be microprocessor or the processor 20 is also possible to any conventional processing
Device etc., the processor 20 can use the various pieces of various interfaces and connection fishery knowledge mapping construction device 100.
The memory 10 can be used for storing the computer program 30 and/or module, and the processor 20 passes through operation
Or the computer program and/or module being stored in the memory 10 are executed, and call the number being stored in memory 10
According to realizing the various functions of the fishery knowledge mapping construction device 100.The memory 10 may include high random access
Memory can also include nonvolatile memory, such as hard disk, memory, plug-in type hard disk, intelligent memory card (Smart
Media Card, SMC), secure digital (Secure Digital, SD) card, flash card (Flash Card), at least one disk
Memory device, flush memory device or other volatile solid-state parts.
Fig. 2 is the functional block diagram that fishery knowledge mapping of the present invention constructs system preferred embodiment.
As shown in fig.2, fishery knowledge mapping building system 40 may include extraction module 101, first establish module
102, second module 103 and update module 104 are established.In one embodiment, above-mentioned module can be to be stored in the storage
In device 10 and the programmable software instruction executed can be called by the processor 20.It is understood that in other embodiment party
In formula, above-mentioned module can also be to solidify program instruction or firmware (firmware) in the processor 20.
The extraction module 101 is used to obtain the fishery FIELD Data of a target area, and from the fishery FIELD Data
Middle to extract multiple fishery entities, the plurality of fishery entity includes that at least fisherman's entity and an at least fishery are real
Body.
In one embodiment, the target area can be set according to actual use demand, than if necessary
The fishery knowledge mapping in a specified city is established, then the fishery FIELD Data of the target area can be the fishery field in the specified city
If desired data establish the fishery knowledge mapping in a specified county, then it is specified to can be this for the fishery FIELD Data of the target area
The fishery FIELD Data in county.The fishery FIELD Data can be the fishery in the target area database and/
Or the data that fisherman reports.
In one embodiment, the fishery FIELD Data may include the fishery -ies product sales data of fishery, fishery
The fish of company are stocked up data, fishing data of fisherman etc..The extraction module 101 can be mentioned from the fishery FIELD Data
Multiple fishery entities are taken, multiple fishery entities may include multiple fisherman's entities and multiple fishery's entities, such as more
A fishery entity includes 100 fisherman A1~A100 and 5 fishery B1~B5.In other embodiments of the invention
In, multiple fishery entities may include multiple fisherman's entities, multiple fishery's entities and multiple fish class instances.
In one embodiment, the extraction module 101 can first extract fisherman's data from the fishery FIELD Data
(data that fisherman reports) then extract an at least fish class instance from fisherman's data again.The fish class instance can
To be the type for characterizing the fish of fisherman's fishing.For example the fish class instance may include yellow croaker, hairtail, squid, gadus, perch
Fish etc..
Described first establishes module 102 for establishing multiple fishery entities by preset incidence relation method for building up
Between incidence relation.
In one embodiment, the incidence relation may include fishing relationship, sell relationship, purchase relationship etc..Institute
State the incidence relation between fishery entity may include incidence relation between fishery's entity and fisherman's entity,
Incidence relation and fisherman's entity and the fish class instance between fishery's entity and the fish class instance
Between incidence relation.
In one embodiment, the incidence relation between fishery's entity and the fish class instance can refer to
Incidence relation between fishery's entity and its fish class instance sold and/or bought, specifically, described first establishes mould
Block 102 can obtain the other entity information of fish of fishery's entity sale and/or purchase, then base from fishery's database
In the fish classification information of its sale and/or purchase, foundation is obtained between fishery's entity and the fish class instance
Incidence relation.Incidence relation between fisherman's entity and the fish class instance can refer to that fisherman's entity and the fisherman are real
Incidence relation between the fish class instance of body fishing, specifically, described first establishes the available each fishing of module 102
The fish classification information of people's entity fishing, then the fish classification information caught based on each fisherman's entity, foundation obtain described
Fishing relationship between fisherman's entity and the fish class instance.For example, it described first establishes module 102 and is establishing fisherman
When incidence relation between entity A 1 and fish class instance, described first, which establishes module 102, can first obtain 1 institute of fisherman's entity A
The fish classification information of fishing is stated, then the fish classification information caught based on fisherman's entity A 1 is established to obtain fisherman's entity A 1 and be caught with it
Incidence relation between the fish class instance of fishing.
In one embodiment, the preset incidence relation method for building up can be the correlation rule pre-established, than
The incidence relation between multiple fisherman's entities and multiple fishery's entities is such as pre-established, then according to the pass pre-established
The regular incidence relation to establish multiple fisherman's entities Yu multiple fishery's entities of connection.
Described second establishes module 103 for according between each fishery entity and each fishery entity
Incidence relation establishes fishery knowledge mapping.
In one embodiment, after the incidence relation between each fishery entity is established, described second is established
Module 103 can be established to obtain according to the incidence relation between each fishery entity and each fishery entity described
Fishery knowledge mapping.
It in one embodiment, include that fishery's entity, fisherman's entity and fish class instance are with the fishery entity
Example, described second, which establishes module 103, can be accomplished by the following way the building fishery knowledge mapping: described second establishes
Module 103 obtains the name identification of fishery's entity, fisherman's entity and the fish class instance, and based on acquisition
Fishery's entity, fisherman's entity and the fish class instance name identification construct fishery knowledge mapping frame
Frame, then by the incidence relation between fishery's entity and fisherman's entity, fishery's entity and the fish
The incidence relation between incidence relation and fisherman's entity and the fish class instance between class instance is filled to described
Fishery knowledge mapping frame obtains the fishery knowledge mapping.
In one embodiment, described second establish module 103 can also be by the name identification of each fishery entity
And the incidence relation between each fishery entity is directed into preset pattern database, and passes through the preset pattern data
Visualization be converted to the fishery knowledge mapping.For example, the preset pattern database can be Noe4j graph data
Library, described second establishes module 103 will be between the name identification of each fishery entity and each fishery entity
Incidence relation is directed into Noe4j graphic data base and is visualized, and the fishery knowledge mapping can be generated.
It should be understood that when establish obtain fishery knowledge mapping after, can use knowledge reasoning and infer between new entity
Relationship, can also to fishery knowledge mapping carry out logic collision detection.Knowledge reasoning can be mentioned according to fishery knowledge mapping
The information that the information of confession is more implied can such as be obtained by ontology or rule-based reasoning technology from fishery knowledge mapping
Tacit knowledge existing for fishery data predicts the relationship implied between entity in map, social computing algorithm can also be used in fishing
Community present on map is calculated and obtained on industry knowledge mapping network, and associated path between profile information is provided.
Method of Knowledge Reasoning may include type inferencing method, mode inductive method etc..The type inferencing method is available
The belonging relation between entity and concept in learning knowledge map.For example utilize triple subject or predicate institute connection attribute
Statistical distribution to predict the type of entity, using summary data and AD HOC is utilized to carry out the extraction of entity type.It is described
Mode inductive method can be used for learning the relationship between concept, including the inductive method based on ILP and the conclusion side based on ARM
Method.ILP technology combines machine learning and programming in logic technology, and people is allowed to obtain logic from example and background knowledge
Conclusion, or information is obtained by SPARQL inquiry, ILP technology can be used to construct transaction table, is then engaged in using ARM technology
Some associated conceptual relations are excavated in business table.
By the powerful knowledge reasoning of knowledge mapping and interconnection organizational capacity, can be applied for intelligent information or even artificial
Intelligence provides data basis, and the present invention constructs complicated fishery-fishery-fisherman's relational network and knowledge using knowledge mapping
Inferential capability can quickly and easily find and search the associated of the knowledge mapping relationship met with it by a certain keyword
Transaction Information and/or transaction knowledge.Such as in transaction platform, when search key is " yellow croaker ", transaction backstage can be quick
Associated with yellow croaker fishery, fish, the relationship between fisherman are searched, and shows fish similar therewith, master sells Huang
The fishery of flower fish and major production areas, there are also mouthfeel similar with yellow croaker or the fish of the same area, to facilitate visitor
Family is selected.
The update module 104 is used to update Rule according to presupposed information and updates the letter of the fish class instance
The information of breath, the information of fisherman's entity and fishery's entity, and based on the updated fish class instance letter
Breath, fisherman's entity information and fishery's entity information are updated the fishery knowledge mapping.
In one embodiment, in order to ensure the accuracy of the fishery knowledge mapping, a presupposed information can be set more
New rule is updated the fishery knowledge mapping.The update module 104 can be updated according to the presupposed information advises
The information of the information of the fish class instance, the information of fisherman's entity and fishery's entity is then obtained and updates,
The other entity information of the updated fish, fisherman's entity information and fishery's entity information is then based on to know the fishery
Know map to be updated.
In one embodiment, the presupposed information updates rule and can be set according to actual use demand, such as
It may include updating the fish classification information of fisherman's entity fishing daily that the presupposed information, which updates rule, daily described in update
The fish classification information of fishery's entity purchase, updates weekly fisherman's entity information and fishery's entity information.
Such as when Zhou Youxin fisherman be added or there is fisherman to exit the fishery knowledge mapping, then need to update fisherman's entity information,
When the fishery of Zhou Youxin is added or has fishery to exit the fishery knowledge mapping, then it is real to need to update the fishery
Body information.
Fig. 3 is the flow chart of fishery knowledge mapping construction method in an embodiment of the present invention.Institute according to different requirements,
The sequence for stating step in flow chart can change, and certain steps can be omitted.
Step S300, obtains the fishery FIELD Data of a target area, and extracts from the fishery FIELD Data multiple
Fishery entity, the plurality of fishery entity include at least fisherman's entity and at least fishery's entity.
In one embodiment, multiple fishery entities can also include an at least fish class instance.
Step S302 establishes the association between multiple fishery entities by preset incidence relation method for building up and closes
System.
Step S304 is established according to the incidence relation between each fishery entity and each fishery entity
Fishery knowledge mapping.
Step S306 updates Rule according to presupposed information and updates the information of the fish class instance, the fisherman
The information of the information of entity and fishery's entity, and it is based on the other entity information of the updated fish, fisherman's entity
Information and fishery's entity information are updated the fishery knowledge mapping.
It is specified that building one may be implemented in above-mentioned fishery knowledge mapping construction device, method and computer readable storage medium
The fishery knowledge mapping in region promotes the convenience that the fishery FIELD Data efficiency of management and data use, facilitate fishery with
The transaction of fisherman both sides, and aid decision can be provided for fishery and fisherman.
It will be apparent to those skilled in the art that the reality of production can be combined with scheme of the invention according to the present invention and inventive concept
Border needs to make other and is altered or modified accordingly, and these change and adjustment all should belong to range disclosed in this invention.
Claims (10)
1. a kind of fishery knowledge mapping construction method, which is characterized in that the described method includes:
The fishery FIELD Data of a target area is obtained, and extracts multiple fishery entities from the fishery FIELD Data, wherein
Multiple fishery entities include at least fisherman's entity and at least fishery's entity；
The incidence relation between multiple fishery entities is established by preset incidence relation method for building up；And
According to the incidence relation between each fishery entity and each fishery entity, fishery knowledge mapping is established.
2. the method as described in claim 1, which is characterized in that the fishery entity further includes an at least fish class instance, institute
Stating the step of extracting multiple fishery entities from the fishery FIELD Data includes:
Fisherman's data are extracted from the fishery FIELD Data；And
An at least fish class instance is extracted from fisherman's data.
3. method according to claim 2, which is characterized in that the incidence relation established between multiple fishery entities
The step of include:
Obtain the fish classification information of each fisherman's entity fishing；
Fish classification information based on the fishing establishes the fishing relationship between fisherman's entity and the fish class instance.
4. method according to claim 2, which is characterized in that the method also includes:
Rule is updated according to presupposed information and updates the information of the fish class instance, the information of fisherman's entity and institute
State the information of fishery's entity；And
The fishery is known based on the other entity information of the updated fish, fisherman's entity information and fishery's entity information
Know map to be updated.
5. the method as described in claim 1, which is characterized in that the fishery entity further includes an at least fish class instance, more
Incidence relation between a fishery entity include incidence relation between fishery's entity and fisherman's entity,
Incidence relation and fisherman's entity and the fish class instance between fishery's entity and the fish class instance
Between incidence relation.
6. method as claimed in claim 5, which is characterized in that described according to each fishery entity and each fishing
Incidence relation between industry entity, the step of establishing fishery knowledge mapping include:
It obtains and fishery is constructed based on the name identification of fishery's entity, fisherman's entity and the fish class instance
Knowledge mapping frame；And
By incidence relation, fishery's entity and the fish between fishery's entity and fisherman's entity
The incidence relation between incidence relation and fisherman's entity and the fish class instance between other entity is filled to the fishing
Industry knowledge mapping frame obtains the fishery knowledge mapping.
7. method as claimed in claim 5, which is characterized in that between fishery's entity and the fish class instance
Incidence relation is established to obtain by following steps:
Obtain the other entity information of fish of fishery's entity sale and/or purchase；
Based on fishery's entity sell and/or buy the other entity information of fish, establish fishery's entity with
Incidence relation between the fish class instance.
8. the method as described in claim 1, which is characterized in that described according to each fishery entity and each fishing
Incidence relation between industry entity, the step of establishing fishery knowledge mapping include:
Incidence relation between the name identification of each fishery entity and each fishery entity is directed into default
Graphic data base, and carry out visualization and be converted to the fishery knowledge mapping.
9. a kind of fishery knowledge mapping construction device, described device includes processor and memory, is stored on the memory
Several computer programs, which is characterized in that realized such as when the processor is for executing the computer program stored in memory
The step of claim 1-8 described in any item fishery knowledge mapping construction methods.
10. a kind of computer readable storage medium, which is characterized in that the computer-readable recording medium storage has a plurality of finger
It enables, a plurality of described instruction can be executed by one or more processor, to realize such as the described in any item fishery of claim 1-8
The step of knowledge mapping construction method.
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