CN116303624A - Agricultural data processing method and device, electronic equipment and storage medium - Google Patents
Agricultural data processing method and device, electronic equipment and storage medium Download PDFInfo
- Publication number
- CN116303624A CN116303624A CN202310552742.4A CN202310552742A CN116303624A CN 116303624 A CN116303624 A CN 116303624A CN 202310552742 A CN202310552742 A CN 202310552742A CN 116303624 A CN116303624 A CN 116303624A
- Authority
- CN
- China
- Prior art keywords
- key name
- matched
- similarity
- agricultural
- description text
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 238000003672 processing method Methods 0.000 title claims abstract description 27
- 238000000034 method Methods 0.000 claims abstract description 30
- 238000012545 processing Methods 0.000 claims abstract description 17
- 238000004519 manufacturing process Methods 0.000 claims description 12
- 238000012549 training Methods 0.000 claims description 12
- 238000004590 computer program Methods 0.000 claims description 10
- 230000010365 information processing Effects 0.000 abstract description 2
- 238000004891 communication Methods 0.000 description 7
- 238000000605 extraction Methods 0.000 description 6
- 240000008042 Zea mays Species 0.000 description 3
- 235000005824 Zea mays ssp. parviglumis Nutrition 0.000 description 3
- 235000002017 Zea mays subsp mays Nutrition 0.000 description 3
- 235000005822 corn Nutrition 0.000 description 3
- 241000894007 species Species 0.000 description 3
- 230000007547 defect Effects 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 238000007689 inspection Methods 0.000 description 2
- 230000003287 optical effect Effects 0.000 description 2
- 238000012935 Averaging Methods 0.000 description 1
- 230000005856 abnormality Effects 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 238000013500 data storage Methods 0.000 description 1
- 230000001419 dependent effect Effects 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000012423 maintenance Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000000750 progressive effect Effects 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
Images
Classifications
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A90/00—Technologies having an indirect contribution to adaptation to climate change
- Y02A90/10—Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation
Landscapes
- Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
Abstract
The invention provides an agricultural data processing method, an agricultural data processing device, electronic equipment and a storage medium, and relates to the technical field of information processing, wherein the method comprises the following steps: acquiring a first description text of a first key name to be matched in a first agricultural database, determining a first similarity between the first key name to be matched and a reference key name based on the first description text and the reference description text corresponding to the reference key name in a preset reference database, acquiring a second description text of a second key name to be matched in a second agricultural database, and determining a second similarity between the second key name to be matched and the reference key name based on the second description text and the reference description text; determining target similarity between the first key name to be matched and the second key name to be matched based on the first similarity and the second similarity; and when the target similarity reaches a preset threshold value, setting an intercommunication mark for the first key name to be matched and the second key name to be matched. The invention can realize the data intercommunication in the agricultural databases in different areas and improve the data utilization rate.
Description
Technical Field
The present invention relates to the field of information processing technologies, and in particular, to an agricultural data processing method, an agricultural data processing device, an electronic device, and a storage medium.
Background
Through years of development, the data volume related to agriculture is rapidly increased, the data storage and query volume requirements are also increasingly larger, and respective agriculture databases are established in all areas at present, but because the same agriculture concept is named differently in all area databases, information among the agriculture databases cannot be communicated, a data island exists, and high-efficiency utilization of data cannot be realized.
Disclosure of Invention
The invention provides an agricultural data processing method, an agricultural data processing device, electronic equipment and a storage medium, which are used for solving the defect that data among agricultural databases of all areas cannot be communicated in the prior art and realizing the data communication among the agricultural databases of all areas.
The invention provides an agricultural data processing method, which comprises the following steps:
acquiring a first description text of a first key name to be matched in a first agricultural database, determining a first similarity between the first key name to be matched and a reference key name in a preset reference database based on the first description text and the reference description text corresponding to the reference key name in the preset reference database, acquiring a second description text of a second key name to be matched in a second agricultural database, and determining a second similarity between the second key name to be matched and the reference key name based on the second description text and the reference description text, wherein the first description text reflects related information of the first key name to be matched, the second description text reflects related information of the second key name to be matched, and the reference description text is used for describing agricultural concepts corresponding to the reference key name;
Determining target similarity between the first key name to be matched and the second key name to be matched based on the first similarity and the second similarity;
when the target similarity reaches a preset threshold value, an intercommunication mark is set for the first key name to be matched and the second key name to be matched, wherein the intercommunication mark represents that the corresponding agricultural concepts of the first key name to be matched and the corresponding agricultural concepts of the second key name to be matched are the corresponding agricultural concepts of the reference key name.
According to the agricultural data processing method provided by the invention, the method for acquiring the first description text of the first key name to be matched in the first agricultural database comprises the following steps:
searching the first description text in a preset first content library based on the first key name to be matched;
the obtaining the second description text of the second key name to be matched in the second agricultural database comprises the following steps:
searching the second description text in a preset second content library based on the second key name to be matched;
the first content library is consistent with the geographic area corresponding to the first agricultural database, and the second content library is consistent with the geographic area corresponding to the second agricultural database.
According to the agricultural data processing method provided by the invention, the determining the target similarity between the first key name to be matched and the second key name to be matched based on the first similarity and the second similarity comprises the following steps:
Acquiring corresponding production data in the first agricultural database based on the first key name to be matched, wherein the production data comprises yield data and climate data;
determining a third similarity between the first key name to be matched and the second key name to be matched based on the production data and the second key name to be matched;
the target similarity is determined based on the first, second, and third similarities.
According to the agricultural data processing method provided by the invention, the determining of the third similarity between the first key name to be matched and the second key name to be matched based on the production data and the second key name to be matched comprises the following steps:
determining a trained prediction model corresponding to the second key name to be matched in a model library corresponding to the second agricultural database based on the second key name to be matched;
inputting the climate data into the prediction model to obtain prediction data output by the prediction model;
acquiring the third similarity based on the prediction data and the yield data;
the prediction model is trained based on multiple sets of training data, each set of training data comprises sample climate data and a yield data label corresponding to the sample climate data, and the sample climate data corresponds to the second key name to be matched.
According to the agricultural data processing method provided by the invention, the determining the target similarity based on the first similarity, the second similarity and the third similarity comprises the following steps:
determining a fourth similarity based on the first and second similarities, the fourth similarity reflecting a degree of similarity of the first and second similarities;
the target similarity is determined based on the fourth similarity and the third similarity.
According to the agricultural data processing method provided by the invention, the reference database comprises a plurality of layers, and each layer comprises a plurality of key names; after determining the target similarity between the first key name to be matched and the second key name to be matched based on the first similarity and the second similarity, the method further includes:
when the target similarity does not reach the preset threshold, selecting a new key name to replace the reference key name in a target layer where the reference key name is located, and re-executing the step of obtaining a first description text of a first key name to be matched in a first agricultural database, determining the first similarity between the first key name to be matched and the reference key name based on the first description text and a reference description text corresponding to the reference key name in the preset reference database, obtaining a second description text of a second key name to be matched in a second agricultural database, and determining the second similarity between the second key name to be matched and the reference key name based on the second description text and the reference description text until the target similarity reaches the preset threshold; or,
And after traversing all key names in the target layer, when the target similarity does not reach the preset threshold value, selecting a new key name in the upper layer of the target layer as the reference key name.
According to the agricultural data processing method provided by the invention, after a new key name is selected as the reference key name in the previous layer of the target layer, the method further comprises:
if all key names in the three continuous layers are respectively used as the reference key names and the target similarity cannot reach the preset threshold value, prompt information is sent out to prompt the key names and the corresponding description texts in the reference database to be checked.
The invention also provides an agricultural data processing device, which comprises:
the first similarity determining module is used for obtaining a first description text of a first key name to be matched in a first agricultural database, determining first similarity between the first key name to be matched and a reference key name based on a reference description text corresponding to the first description text and the reference key name in a preset reference database, obtaining a second description text of a second key name to be matched in a second agricultural database, and determining second similarity between the second key name to be matched and the reference key name based on the second description text and the reference description text, wherein the first description text reflects related information of the first key name to be matched, the second description text reflects related information of the second key name to be matched, and the reference description text is used for describing agricultural concepts corresponding to the reference key name;
A second similarity determining module, configured to determine a target similarity between the first key name to be matched and the second key name to be matched based on the first similarity and the second similarity;
and the data marking module is used for setting an intercommunication mark for the first key name to be matched and the second key name to be matched when the target similarity reaches a preset threshold value, wherein the intercommunication mark represents that the first key name to be matched and the second key name to be matched correspond to the agricultural concepts corresponding to the reference key name.
The invention also provides an electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the agricultural data processing method as described above when executing the program.
The present invention also provides a non-transitory computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements a method of agricultural data processing as described in any of the above.
According to the technical scheme provided by the invention, the description texts of the first key name to be matched and the second key name to be matched in the reference database are respectively corresponding to the description texts of the reference key names in the reference database, the first similarity and the second similarity between the first key name to be matched and the second key name to be matched in the reference database are determined, the target similarity between the first key name to be matched and the second key name to be matched is determined based on the first similarity and the second similarity, and when the target similarity reaches a preset threshold value, an intercommunication mark is set for the first key name to be matched and the second key name to be matched, so that the first key name to be matched and the second key name to be matched are corresponding to the same agricultural concept.
Drawings
In order to more clearly illustrate the invention or the technical solutions of the prior art, the following description will briefly explain the drawings used in the embodiments or the description of the prior art, and it is obvious that the drawings in the following description are some embodiments of the invention, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic flow chart of an agricultural data processing method provided by the invention;
FIG. 2 is a schematic view of the structure of the agricultural data processing apparatus provided by the present invention;
fig. 3 is a schematic structural diagram of an electronic device provided by the present invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the present invention more apparent, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings, and it is apparent that the described embodiments are some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The inventor finds that the names of the agricultural concepts in each area can be different, for example, in the north, the common name of corn is called corn, and in the south is called corn, when each area builds an own agricultural database, in order to facilitate local personnel to input and call data, the local familiar name is often adopted as the key name of the agricultural concepts in the database, which leads to the fact that the data of the agricultural databases in each area cannot be communicated, forms an information island and is unfavorable for the utilization of the agricultural data.
In order to solve the defect that data among the agricultural databases of all areas cannot be communicated in the prior art, the invention provides an agricultural data processing method, an agricultural data processing device, an agricultural data processing electronic device and a storage medium.
The method for processing agricultural data provided by the invention is described below with reference to fig. 1, and as shown in fig. 1, the method for processing agricultural data provided by the invention comprises the following steps:
s100, a first description text of a rated first key name to be matched in a first agricultural database is obtained, a first similarity between the first key name to be matched and a reference key name is determined based on the first description text and the reference description text corresponding to the reference key name in a preset reference database, a second description text of a second key name to be matched in a second agricultural database is obtained, and a second similarity between the second key name to be matched and the reference key name is determined based on the second description text and the reference description text.
The first description text reflects the related information of the first key name to be matched, the second description text reflects the related information of the second key name to be matched, and the reference description text is used for describing agricultural concepts corresponding to the reference key name.
The reference database comprises a plurality of key names and description texts corresponding to the key names, the key names in the reference database are academic names or common names of various agricultural concepts existing in various areas, the description texts corresponding to the key names in the reference database are used for describing the agricultural concepts corresponding to the key names, and the description texts in the reference database can be written by professionals or extracted from textbooks, academic articles and the like. In order to realize the intercommunication of the first agriculture database and the second agriculture database, it is required to determine which key name in the first agriculture database and which key name in the second agriculture database correspond to the same agriculture concept, so that key values corresponding to the key names of the same agriculture concept can be automatically mutually called or combined, and the utilization rate of data is improved.
The reference database includes a plurality of layers, each layer includes a plurality of key names, and the key names corresponding to sub-agricultural concepts (e.g., different subspecies and varieties under the same species) of the agricultural concepts included in the n-th layer are in the n+1-th layer. Layering the reference databases may further enable matching of a wider range of agricultural concepts when the key names to be matched from the two agricultural databases are not of the same range class of agricultural concepts.
Specifically, obtaining a first description text of a first key name to be matched in a first agricultural database includes:
searching a first description text in a preset first content library based on a first key name to be matched;
obtaining a second description text of a second key name to be matched in a second agricultural database, wherein the second description text comprises:
and searching a second description text in a preset second content library based on the second key name to be matched.
The first content library is consistent with a geographic area corresponding to the first agricultural database, and the second content library is consistent with a geographic area corresponding to the second agricultural database.
It can be understood that, because the agricultural concepts in each region have regional differences, the description text of each key name in the agricultural database written by a professional familiar with the agricultural concepts in the geographic region corresponding to the agricultural database can be added into the content library corresponding to the agricultural database, so that the description text corresponding to each key name in the agricultural database can reflect the agricultural concepts corresponding to the key names more accurately.
Determining a first similarity between the first key name to be matched and the reference key name based on the first description text and the reference description text corresponding to the reference key name in the preset reference database, wherein the method comprises the following steps:
the first description text and the reference description text are respectively input into a trained semantic extraction model, a first semantic vector corresponding to the first description text output by the semantic extraction model is obtained, a reference semantic vector corresponding to the reference description text output by the semantic extraction model is obtained, and the similarity score of the first semantic vector and the reference semantic vector is calculated to be used as a first similarity.
Determining a second similarity between the second key name to be matched and the reference key name based on the second descriptive text and the reference descriptive text, comprising:
inputting the second description text into the trained semantic extraction model, obtaining a second semantic vector corresponding to the second description text output by the semantic extraction model, and calculating the similarity score of the second semantic vector and the reference semantic vector as a second similarity.
The semantic extraction model can be obtained by adopting the existing architecture of a model for extracting the semantic and adopting agriculture related corpus training on the basis.
Referring again to fig. 1, the agricultural data processing method provided by the present invention further includes the steps of:
S200, determining target similarity between the first key name to be matched and the second key name to be matched based on the first similarity and the second similarity.
It can be seen that the first similarity reflects the degree of similarity between the first key name to be matched and the reference key name, and the second similarity reflects the degree of similarity between the second key name to be matched and the reference key name, and then, based on the first similarity and the second similarity, the target similarity between the first key name to be matched and the second key name to be matched can be determined later.
In one possible implementation, the target similarity between the first key name to be matched and the second key name to be matched may be determined directly based on the degree of similarity of the first similarity and the second similarity. However, this may lead to inaccuracy, because there may be two different agricultural concepts a and B, each having a similar degree to the agricultural concept C, and in order to avoid that the target similarity caused by this situation may not accurately reflect the similarity between the first key name to be matched and the second key name to be matched, the method provided by the present invention determines, based on the first similarity and the second similarity, the target similarity between the first key name to be matched and the second key name to be matched, including:
Acquiring corresponding production data in the first agricultural database based on the first key name to be matched, wherein the production data comprises yield data and climate data;
determining a third similarity between the first key name to be matched and the second key name to be matched based on the production data and the second key name to be matched;
the target similarity is determined based on the first, second, and third similarities.
Where for the same agricultural concept it may correspond to multiple types of data, for example for crops it may correspond to multiple types of data of yield, planting area, climate etc. And acquiring yield data and climate data corresponding to the first key name to be matched from a first agricultural database as production data.
In addition to the semantic differences between the corresponding descriptive text and the descriptive text corresponding to the reference key name, the corresponding yield data should have the same climate-dependent characteristics, i.e. the same crop should show a consistent yield under the same climate conditions. In the method provided by the invention, the similarity between the key name and the yield data is determined according to whether the characteristics of the yield data corresponding to the key name along with the climate change are consistent.
Determining a third similarity between the first key name to be matched and the second key name to be matched based on the first data and the second key name to be matched, including:
determining a trained prediction model corresponding to the second key name to be matched in a model library corresponding to the second agricultural database based on the second key name to be matched;
inputting the climate data into a prediction model to obtain prediction data output by the prediction model;
acquiring the third similarity based on the predicted data and the yield data;
the prediction model is trained based on a plurality of sets of training data, each set of training data comprises sample climate data and a yield data label corresponding to the sample climate data, and the sample climate data used for training the prediction model corresponds to a second key name to be matched.
In the invention, the third similarity reflects the similarity of the output data corresponding to the first key name to be matched and the second key name to be matched along with the climate change characteristics. Specifically, in the method provided by the invention, firstly, a corresponding trained prediction model is determined based on the second key name to be matched, the second key name to be matched corresponds to the trained prediction model, the training is completed based on a plurality of groups of training data, each group of training data comprises sample climate data and a yield data label corresponding to the sample climate data, the sample climate data and the yield data label corresponding to the sample climate data come from the data corresponding to the second key name to be matched, that is, after the prediction model is trained, the characteristics of the yield of crops corresponding to the second key name to be matched along with the climate change can be learned, if the first key name to be matched and the second key name to be matched correspond to the same agricultural concept, obviously, the model obtained by training the data corresponding to the second key name to be matched can predict the yield data corresponding to the first key name to be matched based on the climate data corresponding to the first key name to be matched, and a more correct result can be obtained. Therefore, the climate data corresponding to the first key name to be matched is input into the prediction model, and based on the similarity between the prediction data output by the prediction model and the yield data corresponding to the first key name to be matched, the third similarity reflecting the similarity of the yield characteristics of the first key name to be matched and the second key name to be matched along with the climate change can be obtained.
Determining the target similarity based on the first similarity, the second similarity, and the third similarity, comprising:
determining a fourth similarity based on the first similarity and the second similarity, the fourth similarity reflecting the degree of similarity of the first similarity and the second similarity;
the target similarity is determined based on the fourth similarity and the third similarity.
The fourth similarity reflects the semantic similarity of the description texts of the first key name to be matched and the second key name to be matched and the description texts of the reference key names respectively, the third similarity reflects the similarity of the output of the agricultural concepts corresponding to the first key name to be matched and the second key name to be matched along with the climate change characteristics, and the accuracy of the result of judging whether the agricultural concepts corresponding to the first key name to be matched and the second key name to be matched are the agricultural concepts corresponding to the reference key names can be greatly improved.
The target similarity is determined based on the fourth similarity and the third similarity, which may be obtained by averaging the fourth similarity and the third similarity, or may be obtained by weighting and summing the fourth similarity and the third similarity.
As shown in fig. 1, the method provided by the present invention further includes the steps of:
and S300, when the target similarity reaches a preset threshold value, setting intercommunication marks for the first key name to be matched and the second key name to be matched, wherein the intercommunication marks represent agricultural concepts corresponding to the reference key names and corresponding to the first key name to be matched and the second key name to be matched.
The preset threshold may be set to 90% after the corresponding objective similarity is calculated by using the existing interoperable agricultural concepts and the method provided by the present invention, for example, after a plurality of pairs of interoperable agricultural concepts are set according to the calculation result, the objective similarity calculated by using the method provided by the present invention is more than 90%, and of course, the preset threshold may be set to 90%, and those skilled in the art may set the preset threshold to other values, for example, 85%, 95% according to the actual situation. When the target similarity reaches a preset threshold value, the similarity between the first key name to be matched and the second key name to be matched reaches a certain degree, the similarity between the first key name to be matched and the reference key name, and the similarity between the second key name to be matched and the reference key name reach a certain program, and the agricultural concepts corresponding to the first key name to be matched and the second key name to be matched can be determined to be the agricultural concepts corresponding to the reference key name. In this way, even if data is stored in the first agriculture database and the second agriculture database, respectively, data of key names corresponding to the same agriculture concept can be communicated.
The first key name to be matched and the second key name to be matched may be sub-divided concepts under the same large concept, for example, different subspecies or different varieties under the same species, or the first key name to be matched and the second key name to be matched belong to concepts with different granularity, for example, one is a species name and the other is a subspecies name. In practice, however, it makes sense to identify the generic concept common to both even though they are not agricultural concepts of the same granularity. Therefore, in the method provided by the invention, for efficiency, the selection of the reference key name is performed in a layer-by-layer progressive manner. Specifically, first, a reference key name is selected at the bottom layer of the reference database, and if a reference key name which cannot enable the target similarity to reach a preset threshold cannot be found at the layer, the reference key name is selected at the upper layer of the layer. That is, in the method provided by the invention, after determining the target similarity between the first key name to be matched and the second key name to be matched based on the first similarity and the second similarity, the method further comprises the steps of:
When the target similarity does not reach a preset threshold value, selecting a new key name to replace the reference key name in a target layer where the reference key name is located, and re-executing the steps of acquiring a first description text of a first key name to be matched in the first agricultural database, determining the first similarity between the first key name to be matched and the reference key name based on the first description text and a reference description text corresponding to the reference key name in the preset reference database, acquiring a second description text of a second key name to be matched in the second agricultural database, and determining the second similarity between the second key name to be matched and the reference key name based on the second description text and the reference description text until the target similarity reaches the preset threshold value; or after traversing all key names in the target layer, when the target similarity does not reach a preset threshold value, selecting a new key name in the upper layer of the target layer as a reference key name.
Further, after selecting a new key name as a reference key name in a layer above the target layer, the method further comprises the steps of:
if all key names in the three continuous layers are respectively used as reference key names and the target similarity cannot reach the preset threshold value, prompt information is sent out to prompt the checking of the key names and the corresponding description texts in the reference database.
If three continuous layers (taking the bottommost layer as an example, namely the bottommost layer, the upper layer of the bottommost layer and the upper layer of the bottommost layer) are respectively used as reference key names, but the generated target similarity does not reach a preset threshold value, the fact that the key names in the reference database are missing is indicated, or the description text of the key names is inaccurate can be sent out, and prompt information can be sent out to prompt maintenance personnel of the reference database to check the key names and the corresponding description text in the reference database.
Specifically, in order to improve the inspection efficiency, before sending out prompt information to prompt the inspection of the key names and the corresponding description text in the reference database, the method includes:
and determining a corresponding target key name of the existing intercommunication mark in the reference database, setting a first checking priority for the target key name, and setting a second checking priority for the key names except the target key name in the reference database, wherein the second checking priority is higher than the first checking priority.
If the key names in the reference database can enable the target similarity of the key names to be matched in the other two agricultural databases to reach a preset threshold, the key names are set to be higher in rationality, so that the checking priority of the target key names is set to be lower, the checking priorities of other key names are set to be higher, in this way, when checking, the key names with higher priorities can be checked firstly based on the checking priorities, and when no abnormality occurs, the target key names with lower priorities can be checked, and the checking efficiency can be effectively improved.
In summary, according to the method for processing agricultural data provided by the invention, through the description texts of the first key name to be matched and the second key name to be matched respectively from two agricultural databases and the description texts of the reference key names in the reference databases, the first similarity and the second similarity between the first key name to be matched and the second key name to be matched are determined, the target similarity between the first key name to be matched and the second key name to be matched is determined based on the first similarity and the second similarity, and when the target similarity reaches a preset threshold value, an intercommunication mark is set for the first key name to be matched and the second key name to be matched, so that the first key name to be matched and the second key name to be matched correspond to the same agricultural concept.
The agricultural data processing apparatus provided by the present invention will be described below, and the agricultural data processing apparatus described below and the agricultural data processing method described above may be referred to correspondingly to each other.
As shown in fig. 2, the agricultural data processing apparatus provided by the present invention includes a first similarity determining module 210, a second similarity determining module 220 and a data marking module 230.
The first similarity determining module 210 is configured to obtain a first description text of a first key name to be matched in the first agricultural database, determine a first similarity between the first key name to be matched and a reference key name based on a reference description text corresponding to the first description text and the reference key name in a preset reference database, obtain a second description text of a second key name to be matched in the second agricultural database, and determine a second similarity between the second key name to be matched and the reference key name based on the second description text and the reference description text, where the first description text reflects related information of the first key name to be matched, the second description text reflects related information of the second key name to be matched, and the reference description text is used for describing an agricultural concept corresponding to the reference key name;
the second similarity determining module 220 is configured to determine, based on the first similarity and the second similarity, a target similarity between the first key name to be matched and the second key name to be matched;
The data marking module 230 is configured to set an interworking mark for the first key name to be matched and the second key name to be matched when the target similarity reaches a preset threshold, where the interworking mark indicates that the first key name to be matched and the second key name to be matched are both agricultural concepts corresponding to the reference key name.
Fig. 3 illustrates a physical schematic diagram of an electronic device, as shown in fig. 3, where the electronic device may include: processor 310, communication interface (Communications Interface) 320, memory 330 and communication bus 340, wherein processor 310, communication interface 320, memory 330 accomplish communication with each other through communication bus 340. Processor 310 may invoke logic instructions in memory 330 to perform an agricultural data processing method comprising: acquiring a first description text of a first key name to be matched in a first agricultural database, determining a first similarity between the first key name to be matched and a reference key name based on the first description text and a reference description text corresponding to the reference key name in a preset reference database, acquiring a second description text of a second key name to be matched in a second agricultural database, and determining a second similarity between the second key name to be matched and the reference key name based on the second description text and the reference description text, wherein the first description text reflects related information of the first key name to be matched, the second description text reflects related information of the second key name to be matched, and the reference description text is used for describing agricultural concepts corresponding to the reference key name;
Determining target similarity between the first key name to be matched and the second key name to be matched based on the first similarity and the second similarity;
when the target similarity reaches a preset threshold value, an intercommunication mark is set for the first key name to be matched and the second key name to be matched, wherein the intercommunication mark represents agricultural concepts corresponding to the reference key names and corresponding to the first key name to be matched and the second key name to be matched.
Further, the logic instructions in the memory 330 described above may be implemented in the form of software functional units and may be stored in a computer-readable storage medium when sold or used as a stand-alone product. Based on this understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution, in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server, a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
In another aspect, the present invention also provides a computer program product comprising a computer program, the computer program being storable on a non-transitory computer readable storage medium, the computer program, when executed by a processor, being capable of performing the agricultural data processing method provided by the methods described above, the method comprising: acquiring a first description text of a first key name to be matched in a first agricultural database, determining a first similarity between the first key name to be matched and a reference key name based on the first description text and a reference description text corresponding to the reference key name in a preset reference database, acquiring a second description text of a second key name to be matched in a second agricultural database, and determining a second similarity between the second key name to be matched and the reference key name based on the second description text and the reference description text, wherein the first description text reflects related information of the first key name to be matched, the second description text reflects related information of the second key name to be matched, and the reference description text is used for describing agricultural concepts corresponding to the reference key name;
determining target similarity between the first key name to be matched and the second key name to be matched based on the first similarity and the second similarity;
When the target similarity reaches a preset threshold value, an intercommunication mark is set for the first key name to be matched and the second key name to be matched, wherein the intercommunication mark represents agricultural concepts corresponding to the reference key names and corresponding to the first key name to be matched and the second key name to be matched.
In yet another aspect, the present invention also provides a non-transitory computer readable storage medium having stored thereon a computer program which, when executed by a processor, is implemented to perform the agricultural data processing method provided by the above methods, the method comprising: acquiring a first description text of a first key name to be matched in a first agricultural database, determining a first similarity between the first key name to be matched and a reference key name based on the first description text and a reference description text corresponding to the reference key name in a preset reference database, acquiring a second description text of a second key name to be matched in a second agricultural database, and determining a second similarity between the second key name to be matched and the reference key name based on the second description text and the reference description text, wherein the first description text reflects related information of the first key name to be matched, the second description text reflects related information of the second key name to be matched, and the reference description text is used for describing agricultural concepts corresponding to the reference key name;
Determining target similarity between the first key name to be matched and the second key name to be matched based on the first similarity and the second similarity;
when the target similarity reaches a preset threshold value, an intercommunication mark is set for the first key name to be matched and the second key name to be matched, wherein the intercommunication mark represents agricultural concepts corresponding to the reference key names and corresponding to the first key name to be matched and the second key name to be matched.
The apparatus embodiments described above are merely illustrative, wherein the elements illustrated as separate elements may or may not be physically separate, and the elements shown as elements may or may not be physical elements, may be located in one place, or may be distributed over a plurality of network elements. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art will understand and implement the present invention without undue burden.
From the above description of the embodiments, it will be apparent to those skilled in the art that the embodiments may be implemented by means of software plus necessary general hardware platforms, or of course may be implemented by means of hardware. Based on this understanding, the foregoing technical solution may be embodied essentially or in a part contributing to the prior art in the form of a software product, which may be stored in a computer readable storage medium, such as ROM/RAM, a magnetic disk, an optical disk, etc., including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the method described in the respective embodiments or some parts of the embodiments.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present invention, and are not limiting; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims (10)
1. A method of agricultural data processing, comprising:
acquiring a first description text of a first key name to be matched in a first agricultural database, determining a first similarity between the first key name to be matched and a reference key name in a preset reference database based on the first description text and the reference description text corresponding to the reference key name in the preset reference database, acquiring a second description text of a second key name to be matched in a second agricultural database, and determining a second similarity between the second key name to be matched and the reference key name based on the second description text and the reference description text, wherein the first description text reflects related information of the first key name to be matched, the second description text reflects related information of the second key name to be matched, and the reference description text is used for describing agricultural concepts corresponding to the reference key name;
Determining target similarity between the first key name to be matched and the second key name to be matched based on the first similarity and the second similarity;
when the target similarity reaches a preset threshold value, an intercommunication mark is set for the first key name to be matched and the second key name to be matched, wherein the intercommunication mark represents that the corresponding agricultural concepts of the first key name to be matched and the corresponding agricultural concepts of the second key name to be matched are the corresponding agricultural concepts of the reference key name.
2. The method for processing agricultural data according to claim 1, wherein the obtaining the first descriptive text of the first key name to be matched in the first agricultural database includes:
searching the first description text in a preset first content library based on the first key name to be matched;
the obtaining the second description text of the second key name to be matched in the second agricultural database comprises the following steps:
searching the second description text in a preset second content library based on the second key name to be matched;
the first content library is consistent with the geographic area corresponding to the first agricultural database, and the second content library is consistent with the geographic area corresponding to the second agricultural database.
3. The agricultural data processing method according to claim 1, wherein the determining the target similarity between the first key name to be matched and the second key name to be matched based on the first similarity and the second similarity includes:
acquiring corresponding production data in the first agricultural database based on the first key name to be matched, wherein the production data comprises yield data and climate data;
determining a third similarity between the first key name to be matched and the second key name to be matched based on the production data and the second key name to be matched;
the target similarity is determined based on the first, second, and third similarities.
4. The agricultural data processing method according to claim 3, wherein the determining a third similarity between the first key name to be matched and the second key name to be matched based on the production data and the second key name to be matched includes:
determining a trained prediction model corresponding to the second key name to be matched in a model library corresponding to the second agricultural database based on the second key name to be matched;
inputting the climate data into the prediction model to obtain prediction data output by the prediction model;
Acquiring the third similarity based on the prediction data and the yield data;
the prediction model is trained based on multiple sets of training data, each set of training data comprises sample climate data and a yield data label corresponding to the sample climate data, and the sample climate data corresponds to the second key name to be matched.
5. The agricultural data processing method of claim 3, wherein the determining the target similarity based on the first similarity, the second similarity, and the third similarity includes:
determining a fourth similarity based on the first and second similarities, the fourth similarity reflecting a degree of similarity of the first and second similarities;
the target similarity is determined based on the fourth similarity and the third similarity.
6. The agricultural data processing method of claim 1, wherein the reference database includes a plurality of layers, each layer including a plurality of key names therein; after determining the target similarity between the first key name to be matched and the second key name to be matched based on the first similarity and the second similarity, the method further includes:
When the target similarity does not reach the preset threshold, selecting a new key name to replace the reference key name in a target layer where the reference key name is located, and re-executing the step of obtaining a first description text of a first key name to be matched in a first agricultural database, determining the first similarity between the first key name to be matched and the reference key name based on the first description text and a reference description text corresponding to the reference key name in the preset reference database, obtaining a second description text of a second key name to be matched in a second agricultural database, and determining the second similarity between the second key name to be matched and the reference key name based on the second description text and the reference description text until the target similarity reaches the preset threshold; or,
and after traversing all key names in the target layer, when the target similarity does not reach the preset threshold value, selecting a new key name in the upper layer of the target layer as the reference key name.
7. The agricultural data processing method of claim 6, wherein after the new key name is selected as the reference key name in a layer above the target layer, the method further comprises:
If all key names in the three continuous layers are respectively used as the reference key names and the target similarity cannot reach the preset threshold value, prompt information is sent out to prompt the key names and the corresponding description texts in the reference database to be checked.
8. An agricultural data processing apparatus, comprising:
the first similarity determining module is used for obtaining a first description text of a first key name to be matched in a first agricultural database, determining first similarity between the first key name to be matched and a reference key name based on a reference description text corresponding to the first description text and the reference key name in a preset reference database, obtaining a second description text of a second key name to be matched in a second agricultural database, and determining second similarity between the second key name to be matched and the reference key name based on the second description text and the reference description text, wherein the first description text reflects related information of the first key name to be matched, the second description text reflects related information of the second key name to be matched, and the reference description text is used for describing agricultural concepts corresponding to the reference key name;
A second similarity determining module, configured to determine a target similarity between the first key name to be matched and the second key name to be matched based on the first similarity and the second similarity;
and the data marking module is used for setting an intercommunication mark for the first key name to be matched and the second key name to be matched when the target similarity reaches a preset threshold value, wherein the intercommunication mark represents that the first key name to be matched and the second key name to be matched correspond to the agricultural concepts corresponding to the reference key name.
9. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the agricultural data processing method of any one of claims 1 to 7 when the program is executed by the processor.
10. A non-transitory computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when executed by a processor, implements the agricultural data processing method according to any one of claims 1 to 7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310552742.4A CN116303624B (en) | 2023-05-17 | 2023-05-17 | Agricultural data processing method and device, electronic equipment and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310552742.4A CN116303624B (en) | 2023-05-17 | 2023-05-17 | Agricultural data processing method and device, electronic equipment and storage medium |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN116303624A true CN116303624A (en) | 2023-06-23 |
| CN116303624B CN116303624B (en) | 2023-09-19 |
Family
ID=86813501
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310552742.4A Active CN116303624B (en) | 2023-05-17 | 2023-05-17 | Agricultural data processing method and device, electronic equipment and storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116303624B (en) |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR20190053825A (en) * | 2019-05-10 | 2019-05-20 | 주식회사 공감랩 | System and method of building big data for estimating house price using space information |
| CN112287657A (en) * | 2020-11-19 | 2021-01-29 | 每日互动股份有限公司 | Information matching system based on text similarity |
| CN112434188A (en) * | 2020-10-23 | 2021-03-02 | 杭州未名信科科技有限公司 | Data integration method and device for heterogeneous database and storage medium |
| CN113255370A (en) * | 2021-06-22 | 2021-08-13 | 中国平安财产保险股份有限公司 | Industry type recommendation method, device, equipment and medium based on semantic similarity |
| CN115495309A (en) * | 2022-09-14 | 2022-12-20 | 中国建设银行股份有限公司 | Database server IO processing method and device sharing storage server |
-
2023
- 2023-05-17 CN CN202310552742.4A patent/CN116303624B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR20190053825A (en) * | 2019-05-10 | 2019-05-20 | 주식회사 공감랩 | System and method of building big data for estimating house price using space information |
| CN112434188A (en) * | 2020-10-23 | 2021-03-02 | 杭州未名信科科技有限公司 | Data integration method and device for heterogeneous database and storage medium |
| CN112287657A (en) * | 2020-11-19 | 2021-01-29 | 每日互动股份有限公司 | Information matching system based on text similarity |
| CN113255370A (en) * | 2021-06-22 | 2021-08-13 | 中国平安财产保险股份有限公司 | Industry type recommendation method, device, equipment and medium based on semantic similarity |
| CN115495309A (en) * | 2022-09-14 | 2022-12-20 | 中国建设银行股份有限公司 | Database server IO processing method and device sharing storage server |
Non-Patent Citations (2)
| Title |
|---|
| NUR AINI RAKHMAWATI: "Discovering Entity Profiles Candidate for Entity Resolution on Linked Open Data Halal Food Products", 2020 IEEE INTERNATIONAL CONFERENCE ON BIG DATA (BIG DATA) * |
| 谭永滨: "语义支持的地理要素属性相似性计算模型", 遥感信息 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN116303624B (en) | 2023-09-19 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN111309912B (en) | Text classification method, apparatus, computer device and storage medium | |
| CN110532397B (en) | Question-answering method and device based on artificial intelligence, computer equipment and storage medium | |
| CN110750649A (en) | Knowledge graph construction and intelligent response method, device, equipment and storage medium | |
| US20210365803A1 (en) | Machine-learning system and method for identifying same person in genealogical databases | |
| CN111898739B (en) | Data screening model construction method, data screening method, device, computer equipment and storage medium based on meta learning | |
| CN108496190B (en) | Annotation system for extracting attributes from electronic data structures | |
| CN110263326B (en) | User behavior prediction method, prediction device, storage medium and terminal equipment | |
| US20220044809A1 (en) | Systems and methods for using deep learning to generate acuity scores for critically ill or injured patients | |
| CN111242793B (en) | Medical insurance data abnormality detection method and device | |
| US20200364216A1 (en) | Method, apparatus and storage medium for updating model parameter | |
| WO2019223104A1 (en) | Method and apparatus for determining event influencing factors, terminal device, and readable storage medium | |
| WO2021240707A1 (en) | Data classification system, data classification method, and recording medium | |
| CN110135681A (en) | Risk subscribers recognition methods, device, readable storage medium storing program for executing and terminal device | |
| JP5682448B2 (en) | Causal word pair extraction device, causal word pair extraction method, and causal word pair extraction program | |
| CN110782996A (en) | Construction method and device of medical database, computer equipment and storage medium | |
| CN112597124A (en) | Data field mapping method and device and storage medium | |
| CN110704668B (en) | Grid-based collaborative attention VQA method and device | |
| Firneno Jr et al. | Delimitation despite discordance: Evaluating the species limits of a confounding species complex in the face of mitonuclear discordance | |
| WO2020087971A1 (en) | Prediction model-based hospitalization rationality prediction method and related products | |
| CN116303624B (en) | Agricultural data processing method and device, electronic equipment and storage medium | |
| CN110796178B (en) | Decision model training method, sample feature selection method, device and electronic equipment | |
| CN116756176A (en) | Structured query language problem prediction method, device, equipment and storage medium | |
| CN109324963A (en) | The method and terminal device of automatic test profitable result | |
| CN115238653A (en) | Report generation method, device, equipment and medium | |
| CN110543634B (en) | Corpus data set processing method and device, electronic equipment and storage medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |