CN112286988B - Medical document ordering method, device, electronic equipment and storage medium - Google Patents
Medical document ordering method, device, electronic equipment and storage medium Download PDFInfo
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Abstract
The application relates to the technical field of medical science and technology, and particularly discloses a medical document ordering method, a device, electronic equipment and a storage medium. The method comprises the following steps: acquiring citation relations among a plurality of medical documents and publishing time of each medical document in the plurality of medical documents; determining a directed graph of the plurality of medical documents under a preset time node according to the quotation relation of the plurality of medical documents and the publishing time of each medical document; determining a first score for each of the plurality of medical documents from the corresponding directed graph of the plurality of medical documents; determining a target score of each medical document under the preset time node according to the directed graph corresponding to the medical documents and the first score of each medical document; and sorting the medical documents according to the target scores of the medical documents at the preset time nodes.
Description
Technical Field
The application relates to the technical field of information recommendation, in particular to a medical document ordering method, a medical document ordering device, electronic equipment and a storage medium.
Background
For a medical researcher, a huge amount of medical literature in a medical literature library provides huge research resources, and also brings screening trouble to the medical researcher. If one wants to grasp the most central research situation in one field or research direction, such as lung cancer field, it is the most efficient method to directly read the high quality medical literature of lung cancer field at different time points.
Currently, the quality of each medical document is determined mainly by a method of establishing a quotation network, namely, the quality of each medical document is determined by a method of establishing an adjacency matrix, for example, according to the cited condition of each medical document, the score of the medical document which cited the medical document to the medical document can be determined, and then the score of each medical document is obtained. For example, if the medical document B refers to the medical document a, the medical document B scores the medical document a with 1×γ, where γ is a preset hyper-parameter.
Therefore, the accuracy of the scoring of the determined medical document depends on preset super parameters, and the super parameters can be obtained by a large amount of experimental data and repeated adjustment, so that the scoring process of the medical document is complicated, and the accuracy is low.
Disclosure of Invention
The embodiment of the application provides a medical document ordering method, a medical document ordering device, electronic equipment and a storage medium. The target score of the medical document can be determined without presetting super parameters, the scoring process of the medical document is simplified, and the scoring precision of the medical document is improved.
In a first aspect, an embodiment of the present application provides a medical document ordering method, including:
acquiring citation relations among a plurality of medical documents and publishing time of each medical document in the plurality of medical documents;
determining a directed graph of the plurality of medical documents under a preset time node according to the quotation relation of the plurality of medical documents and the publishing time of each medical document;
determining a first score for each of the plurality of medical documents from the corresponding directed graph of the plurality of medical documents;
determining a target score of each medical document under the preset time node according to the directed graph corresponding to the medical documents and the first score of each medical document;
and sorting the medical documents according to the target scores of the medical documents at the preset time nodes.
In a second aspect, embodiments of the present application provide a medical document ordering apparatus, including:
the receiving and transmitting unit is used for acquiring the quotation relation among the plurality of medical documents and the publishing time of each medical document in the plurality of medical documents;
the processing unit is used for determining a directed graph of the plurality of medical documents under a preset time node according to the quotation relation of the plurality of medical documents and the publishing time of each medical document;
the processing unit is further used for determining a first score of each medical document in the plurality of medical documents according to the directed graph corresponding to the plurality of medical documents;
the processing unit is further configured to determine a target score of each medical document at the preset time node according to the directed graph corresponding to the plurality of medical documents and the first score of each medical document;
the processing unit is further configured to rank the plurality of medical documents according to the target score of each medical document at the preset time node.
In a third aspect, an embodiment of the present application provides an electronic device, including: and a processor connected to a memory for storing a computer program, the processor being configured to execute the computer program stored in the memory, to cause the electronic device to perform the method according to the first aspect.
In a fourth aspect, embodiments of the present application provide a computer-readable storage medium storing a computer program, the computer program causing a computer to perform the method according to the first aspect.
In a fifth aspect, embodiments of the present application provide a computer program product comprising a non-transitory computer readable storage medium storing a computer program, the computer being operable to cause a computer to perform the method according to the first aspect.
The implementation of the embodiment of the application has the following beneficial effects:
it can be seen that in the embodiment of the application, the quotation relation and the publishing time between the medical documents can be used for creating the directed graph, and the scoring of the medical documents can be determined according to the directed graph without setting the super-parameters in advance, so that the scoring process of the medical documents is simplified, and the scoring accuracy of each medical document is improved.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present application, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a schematic flow chart of a medical document sorting method according to an embodiment of the present application;
FIG. 2 is a schematic diagram of a directed graph according to an embodiment of the present application;
FIG. 3 is a flow chart of another method for sorting medical documents according to an embodiment of the present disclosure;
FIG. 4 is a functional block diagram of a medical document ordering apparatus according to an embodiment of the present disclosure;
fig. 5 is a schematic structural diagram of a medical document sorting apparatus according to an embodiment of the present application.
Detailed Description
The following description of the embodiments of the present application will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are some, but not all, of the embodiments of the present application. All other embodiments, which can be made by one of ordinary skill in the art based on the embodiments herein without making any inventive effort, are intended to be within the scope of the present application.
The terms "first," "second," "third," and "fourth" and the like in the description and in the claims of this application and in the drawings, are used for distinguishing between different objects and not for describing a particular sequential order. Furthermore, the terms "comprise" and "have," as well as any variations thereof, are intended to cover a non-exclusive inclusion. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those listed steps or elements but may include other steps or elements not listed or inherent to such process, method, article, or apparatus.
Reference herein to "an embodiment" means that a particular feature, result, or characteristic described in connection with the embodiment may be included in at least one embodiment of the application. The appearances of such phrases in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. Those of skill in the art will explicitly and implicitly appreciate that the embodiments described herein may be combined with other embodiments.
Referring to fig. 1, fig. 1 is a flow chart of a medical document sorting method according to an embodiment of the present application. The method is applied to a medical document ordering device. The method comprises the following steps:
101: a medical document ordering device obtains a citation relationship between a plurality of medical documents and a publication time for each of the plurality of medical documents.
The plurality of medical documents may be a plurality of medical documents related to a certain disease in the PUBMED database, for example, the plurality of medical documents may be medical documents related to lung cancer, stomach cancer, and tumor.
The reference relationships among the medical documents are marked in advance, and the reference relationships among the medical documents and the publishing time of each medical document can be acquired in the process of acquiring the medical documents from the PUBMED database. The publication time of each medical document is in the granularity of year, for example, the publication time of a certain medical document is No. 19 of 8 months in 2020, and the publication time of the medical document is 2020.
102: the medical document ordering device determines a directed graph of the plurality of medical documents under a preset time node according to the quotation relation of the plurality of medical documents and the publishing time of each medical document.
Wherein the preset time node is also granular by year.
For example, a target medical document of the plurality of medical documents, which refers to a medical document i among the plurality of medical documents, may be determined according to a reference relationship among the plurality of medical documents and a publication time of each medical document, wherein the medical document i is any one of the plurality of medical documents, i has a value of 1 to N, N is a number of the plurality of medical documents, i.e., a medical document i is referred to among the plurality of medical documents, and the publication time is not later than a preset time node is taken as the target medical document, and a directed path of a medical treatment from the medical document i to the target medical document is created for the medical document i and the target medical document, thereby obtaining the directed graph. It should be understood that, for the plurality of medical treatments, the medical document i is cited, but the posting time is later than the preset time node, and for the medical document not cited medical document i (whether or not the posting time is later than the preset time point), no directed path can be created between the medical documents and the medical document i, and the directed graph is obtained by creating the directed path of the medical document i by the isolated nodes.
For example, as shown in fig. 2, if medical document B and medical document D both refer to medical document a, medical document C refers to medical document B, and the publication times of medical document a, medical document B, medical document C, and medical document D are Ta, tb, tc, and Td, respectively, if Tb and Tc are not later than the preset time node T N A directed path from medical document a to medical document B and a directed path from medical document B to medical document C may be created. If Td is later than the preset time node T N Although medical document D also refers to medical document a, a directed path from medical document a to medical document B cannot be created, with medical document D as an isolated node.
103: a medical document ordering device determines a first score for each of the plurality of medical documents based on the corresponding directed graph of the plurality of medical documents.
Illustratively, a first score for each of the plurality of medical documents is determined based on the corresponding directed graph of the plurality of medical documents and the pagerank algorithm.
Illustratively, similar to the method for determining the importance of the web page, the transfer matrix corresponding to the plurality of medical documents is determined according to the directed graph (i.e., the reference relationship among the plurality of medical documents, the connection relationship similar to the web page); then, determining the initial probability of each medical document according to the number of the plurality of medical documents, namely, the initial probability of each medical document is 1/N, and N is the number of the plurality of medical documents; and carrying out multiple iterations according to the initial probability, the transition matrix and the preset super parameters to obtain a first score of each medical document, wherein the first score can reflect the importance degree of each medical document.
Illustratively, during the first iteration, the score for each medical document may be represented by equation (1):
Pr 1 ＝α*M*V 0 + (1- α) e formula (1);
wherein Pr is 1 For the vector of scores of each medical document after the first iteration, V 0 For the vector of initial probabilities of each document, M is the transition matrix and e can be V 0 Alpha is a preset super parameter.
104: the medical document sorting device determines a target score of each medical document under the preset time node according to the directed graph corresponding to the medical documents and the first score of each medical document, wherein the target score of each medical document is used for representing the quality of each medical document under the preset time node.
Illustratively, the first scores of the plurality of medical documents are normalized to obtain a second score corresponding to each medical document in the plurality of medical documents; and then, obtaining a target score corresponding to the medical document i according to the directed graph and the second score corresponding to each medical document. Illustratively, determining a third score for each of the plurality of medical documents other than the medical document i based on the directed graph and the second score for each medical document; and summing the third score of the medical document i and the second score of the medical document i by each medical document in the other medical documents to obtain a target score corresponding to the medical document i.
Specifically, from the directed graph, a medical document to which the medical document i is cited and a medical document to which the medical document i is not cited (i.e., isolated nodes in the directed graph) are determined among the other medical documents, wherein the medical document to which the medical document i is cited includes directly referencing the medical document i and indirectly referencing the medical document i, for example, as shown in fig. 2, the medical document to which the medical document a is cited includes a medical document B to which the medical document a is cited directly and a medical document C to which the medical document a is cited indirectly; determining a third score of the medical document j on the medical document i according to the second score and the publishing time of the medical document j, the second score of the medical document i and the preset time node, wherein the medical document j refers to any one of the medical documents i, the value of j is 1 to M, and M is the number of the medical documents referring to the medical document i; a third score of 0 for a medical document i is determined for the medical document not referring to the medical document i.
For example, in the case where the medical document j directly references the medical document i, a first average value between the medical document j and a second score of the medical document i, and a first time difference between the publication time of the medical document j and the preset time node may be determined; a third score of the medical document j to the medical document i is determined based on the first mean and the first time difference.
For example, in the case where the medical document j indirectly refers to the medical document i, three medical documents are exemplified, for example, in the case where the medical document j directly refers to the medical document k (does not refer to the medical document i), and the medical document k directly refers to the medical document i, then the third score of the medical document j to the medical document k and the third score of the medical document k to the medical document i may be determined, and the product of the third score of the medical document j to the medical document k and the third score of the medical document k to the medical document i may be taken as the third score of the medical document j to the medical document i. Specifically, a second average value between the second scores of the medical document j and the medical document k and a second time difference between the publishing time of the medical document j and a preset time node can be determined, and a third score of the medical document j to the medical document k is determined according to the second average value and the second time difference; and determining a third average value between the second scores of the medical document k and the medical document i, and a third time difference between the publishing time of the medical document k and a preset time node, and determining a third score of the medical document k to the medical document i according to the third average value and the third time difference.
Illustratively, the third score for medical document j to medical document i may be represented by equation (2):
pr (i, j) is the third score of medical document j to medical document i, pr (i) is the second score of medical document i, pr (j) is the second score of medical document j, T N For a preset time node, T j Is the posting time of medical document j, wherein other cases include medical document j not referencing medical document i or medical document j posting time later than T N 。
Illustratively, the target score for medical document i can be represented by equation (3):
wherein Pr is i H Target score for medical document i, pr (i, j) is the third score of medical document j for medical document i, pr i 2 A second score for medical document i. The second score of each medical document is finally superimposed, mainly considering that some isolated medical documents have certain influence, and avoiding setting the target score of the medical document to 0, so that the target score of each medical document is more convincing.
105: and the medical document sorting device sorts the medical documents according to the target scores of each medical document at the preset time node.
For example, after obtaining the target score of each medical document at the preset time node, the plurality of medical documents may be ranked to mine the milestone medical documents at the preset time node from the plurality of medical documents, for example, the medical document with the largest target score may be taken as the milestone medical document at the preset time node, or a preset number of medical documents may be selected from the plurality of medical documents in order of the target score from the large to the small as the milestone medical document at the preset time node.
It can be seen that in the embodiment of the application, the scoring parameters between two medical documents with a citation relationship can be dynamically set according to the pagerank algorithm, and no super-parameters are required to be set in advance, so that the scoring process of the medical documents is simplified; and the pagerank algorithm is firstly applied to the adjacency matrix, and the two scoring results are combined, so that the score of each medical document finally obtained is more accurate, and the quality of the medical documents is ranked by using the score, so that the ranking result is more accurate.
In one embodiment of the present application, the medical document sorting method of the present application may also be applied to smart medical scenarios, for example, a doctor may sort medical documents before a certain year through the medical document sorting method of the present application, and may quickly find a milestone document, improve data reference for the doctor, improve diagnosis efficiency for the doctor, and further promote development of medical science and technology.
Referring to fig. 3, fig. 3 is a flow chart of another medical document sorting method according to an embodiment of the present application. The method is applied to a medical document ordering device and the repetition of the method with the embodiment shown in fig. 1 is not repeated here. The method of the embodiment comprises the following steps:
301: a medical document ordering device obtains a citation relationship between a plurality of medical documents and a publication time for each of the plurality of medical documents.
302: the medical document ordering device determines a directed graph of the plurality of medical documents under a preset time node according to the quotation relation of the plurality of medical documents and the publishing time of each medical document.
303: the medical document ordering means determines a first score for each of the plurality of medical documents based on the pagerank algorithm and the directed graph.
304: and the medical document sorting device normalizes the first scores of the plurality of medical documents to obtain a second score corresponding to each medical document.
305: the medical document ranking means determines a third score for each of the medical documents other than the medical document i from the directed graph and the second score for each of the medical documents.
Illustratively, from the directed graph, determining a medical document in which the medical document i is cited in the other medical documents and a medical document in which the medical document i is not cited (i.e., isolated nodes in the directed graph), wherein the medical document referencing the medical document i includes directly referencing the medical document i and indirectly referencing the medical document i; determining a third score of the medical document j on the medical document i according to the second score and the publishing time of the medical document j, the second score of the medical document i and the preset time node, wherein the medical document j refers to any one of the medical documents i, the value of j is 1 to M, the value of M is the number of the medical documents referring to the medical document i, and the third score of the medical document not referring to the medical document i is set to 0.
For example, in the case where the medical document j directly references the medical document i, a first average value between the medical document j and a second score of the medical document i, and a first time difference between the publication time of the medical document j and the preset time node may be determined; a third score of medical document j to medical document i is determined based on the first average, the first time difference, the number of medical documents spaced between medical document j and medical document i, and the second score of medical document j.
For example, in the case where the medical document j indirectly refers to the medical document i, three medical documents are exemplified, for example, in the case where the medical document j directly refers to the medical document k (does not refer to the medical document i), and the medical document k directly refers to the medical document i, then the third score of the medical document j to the medical document k and the third score of the medical document k to the medical document i may be determined, and the product of the third score of the medical document j to the medical document k and the third score of the medical document k to the medical document i may be taken as the third score of the medical document j to the medical document i. Specifically, a second average value between the second scores of the medical document j and the medical document k and a second time difference between the publishing time of the medical document j and a preset time node can be determined, and a third score of the medical document j to the medical document k is determined according to the second average value, the second time difference, the number of medical documents spaced between the medical document j and the medical document k and the second score of the medical document j; and determining a third average value between the second scores of the medical document k and the medical document i, and a third time difference between the publishing time of the medical document k and a preset time node, and determining a third score of the medical document k to the medical document i according to the third average value, the third time difference, the number of medical documents spaced between the medical document k and the medical document i, and the second score of the medical document k.
Illustratively, the third score for medical document j to medical document i may be represented by equation (3):
pr (i, j) is the third score of medical document j to medical document i, pr (i) is the second score of medical document i, pr (j) is the second score of medical document j, x is the number of medical documents spaced between medical document j and medical document i, T N For a preset time node, T j Is the posting time of medical document j, wherein other cases include medical document j not referencing medical document i or medical document j posting time later than T N 。
It can be seen that the second score of the medical document j is introduced in the formula (3), that is, the importance of the medical document j itself is considered in the process of calculating the score of the medical document j on the medical document i, which is equivalent to taking the second score of the medical document j as a weight coefficient and weighting the score, so that the obtained score of the medical document j on the medical document i is more accurate; in addition, the single-peak distribution function e-x is also introduced in the formula (3), so that as the distance between the medical document j and the medical document i becomes longer (namely, when the number of medical documents between the two medical documents is large), even if the medical document j is important, the medical document i is attenuated along with the increase of the distance, and the scoring is further more accurate.
306: and the medical document sorting device sums the third score of the medical document i and the second score of the medical document i by each medical document in the other medical documents to obtain a target score corresponding to the medical document i.
307: and the medical document sorting device sorts the medical documents according to the target scores of each medical document at the preset time node.
It can be seen that in the embodiment of the application, the scoring parameters between two medical documents with a citation relationship can be dynamically set according to the pagerank algorithm, and no super-parameters are required to be set in advance, so that the scoring process of the medical documents is simplified; moreover, the pagerank algorithm is firstly applied to the adjacency matrix, and two scoring results are combined, so that the score of each medical document finally obtained is more accurate, and the quality of the medical document is evaluated by using the score, so that the evaluation result is more accurate. In addition, in the process of determining the scores of the medical documents, the weight coefficient and the unimodal distribution function are introduced, so that the scores of the determined medical documents are more accurate, and the ranking of the medical documents is more accurate.
Referring to fig. 4, fig. 4 is a functional unit block diagram of a medical document sorting apparatus according to an embodiment of the present application. The medical document sorting apparatus 400 includes: a transceiver unit 401 and a processing unit 402, wherein:
a transceiver unit 401, configured to obtain a reference relationship between a plurality of medical documents and a publishing time of each medical document in the plurality of medical documents;
a processing unit 402, configured to determine a directed graph of the plurality of medical documents under a preset time node according to a reference relationship of the plurality of medical documents and a publication time of each medical document;
the processing unit 402 is further configured to determine a first score of each of the plurality of medical documents according to the directed graph corresponding to the plurality of medical documents;
the processing unit 402 is further configured to determine a target score of each medical document at the preset time node according to the directed graph corresponding to the plurality of medical documents and the first score of each medical document;
the processing unit 402 is further configured to rank the plurality of medical documents according to the target score of each medical document at the preset time node.
In some possible embodiments, the processing unit 402 is specifically configured to, in determining a directed graph of the plurality of medical documents at a preset time node according to the reference relationship of the plurality of medical documents and the publishing time of each medical document:
Determining a target medical document corresponding to the medical document in the plurality of medical documents according to the reference relation among the medical documents and the publishing time of the medical document i, wherein the medical document i is any medical document in the plurality of medical documents, and the target medical document is the medical document which refers to the medical document i in the plurality of medical documents;
creating a directed path from the medical document i to the target medical document, and taking medical documents other than the target medical document of the plurality of medical documents as isolated nodes to obtain a directed graph of the plurality of medical documents at a preset time node.
In some possible embodiments, the processing unit 402 is specifically configured to, in determining a first score of each of the plurality of medical documents according to the directed graph corresponding to the plurality of medical documents:
determining a transfer matrix corresponding to the plurality of medical documents according to the directed graphs corresponding to the plurality of medical documents;
a first score for each of the plurality of medical documents is determined based on the transfer matrix corresponding to the plurality of medical documents and the number of the plurality of medical documents.
In some possible embodiments, the processing unit 402 is specifically configured to determine, according to the directed graph corresponding to the plurality of medical documents and the first score of each medical document, a target score of each medical document at the preset time node:
normalizing the first scores of the plurality of medical documents to obtain second scores corresponding to the medical documents;
and obtaining a target score corresponding to the medical document i according to the directed graph and the second score corresponding to each medical document, wherein the medical document i is any medical document in the plurality of medical documents.
In some possible embodiments, the processing unit 402 is specifically configured to, in obtaining the target score corresponding to the medical document i according to the directed graph and the second score corresponding to each medical document:
determining a third score for each of the plurality of medical documents to the medical document i based on the directed graph and the second score for each medical document;
and summing the third score of the medical document i and the second score of the medical document i by each medical document in the other medical documents to obtain a target score corresponding to the medical document i.
In some possible embodiments, the processing unit 402 is specifically configured to, in determining, from the directed graph and the second score for each medical document, a third score for each medical document i among the plurality of medical documents other than the medical document i, for the medical document i:
determining, from the directed graph, a medical document in which the medical document i is cited and a medical document (i.e., isolated nodes in the directed graph) in which the medical document i is not cited among the other medical documents, wherein the medical document in which the medical document i is cited includes directly referencing the medical document i and indirectly referencing the medical document i;
determining a third score of the medical document j on the medical document i according to the second score and the publishing time of the medical document j, the second score of the medical document i and the preset time node, wherein the medical document j refers to any medical document in the medical document i, and the third score of the medical document i, which is not referred to the medical document i, is determined to be 0.
In some possible embodiments, the processing unit 402 is specifically configured to determine, according to the second score and the publishing time of the medical document j, the second score of the medical document i, and the preset time node, a third score of the medical document j on the medical document i:
In the case that the medical document j directly refers to the medical document i, determining a first average value between the medical document j and a second score of the medical document i and a first time difference between the publishing time of the medical document j and the preset time node, and determining a third score of the medical document j on the medical document i according to the first average value and the first time difference;
when the medical document j directly refers to the medical document k and the medical document i is not referred to, and the medical document k directly refers to the medical document i, determining a third score of the medical document j to the medical document k and a third score of the medical document k to the medical document i, and taking a product of the third score of the medical document j to the medical document k and the third score of the medical document k to the medical document i as the third score of the medical document j to the medical document i.
Referring to fig. 5, fig. 5 is a schematic structural diagram of an electronic device according to an embodiment of the present application. As shown in fig. 5, the electronic device 500 includes a transceiver 501, a processor 502, and a memory 503. Which are connected by a bus 504. The memory 503 is used to store computer programs and data and may be used to transfer the stored data to the processor 502.
The processor 502 is configured to read a computer program in the memory 503 to perform the following operations:
control transceiver 501 obtains a reference relationship between a plurality of medical documents and a publication time for each of the plurality of medical documents;
determining a directed graph of the plurality of medical documents under a preset time node according to the quotation relation of the plurality of medical documents and the publishing time of each medical document;
determining a first score for each of the plurality of medical documents from the corresponding directed graph of the plurality of medical documents;
determining a target score of each medical document under the preset time node according to the directed graph corresponding to the medical documents and the first score of each medical document;
and sorting the medical documents according to the target scores of the medical documents at the preset time nodes.
In some possible embodiments, the processor 502 is specifically configured to, in determining the directed graph of the plurality of medical documents at the preset time node according to the reference relationship of the plurality of medical documents and the publication time of each medical document, perform the following operations:
Determining a target medical document corresponding to the medical document in the plurality of medical documents according to the reference relation among the medical documents and the publishing time of the medical document i, wherein the medical document i is any medical document in the plurality of medical documents, and the target medical document is the medical document which refers to the medical document i in the plurality of medical documents;
creating a directed path from the medical document i to the target medical document, and taking medical documents other than the target medical document of the plurality of medical documents as isolated nodes to obtain a directed graph of the plurality of medical documents at a preset time node.
In some possible embodiments, the processor 502 is specifically configured to, in determining a first score for each of the plurality of medical documents from the corresponding directed graph of the plurality of medical documents:
determining a transfer matrix corresponding to the plurality of medical documents according to the directed graphs corresponding to the plurality of medical documents;
a first score for each of the plurality of medical documents is determined based on the transfer matrix corresponding to the plurality of medical documents and the number of the plurality of medical documents.
In some possible embodiments, the processor 502 is specifically configured to, in determining the target score of each medical document under the preset time node according to the directed graph corresponding to the medical documents and the first score of each medical document, perform the following operations:
normalizing the first scores of the plurality of medical documents to obtain second scores corresponding to the medical documents;
and obtaining a target score corresponding to the medical document i according to the directed graph and the second score corresponding to each medical document, wherein the medical document i is any medical document in the plurality of medical documents.
In some possible embodiments, the processor 502 is specifically configured to perform the following operations in obtaining the target score corresponding to the medical document i according to the directed graph and the second score corresponding to each medical document:
determining a third score for each of the plurality of medical documents to the medical document i based on the directed graph and the second score for each medical document;
and summing the third score of the medical document i and the second score of the medical document i by each medical document in the other medical documents to obtain a target score corresponding to the medical document i.
In some possible embodiments, the processor 502 is specifically configured to, in determining a third score for each of the plurality of medical documents other than the medical document i on the basis of the directed graph and the second score for each medical document, perform the following operations:
determining, from the directed graph, a medical document in which the medical document i is cited and a medical document (i.e., isolated nodes in the directed graph) in which the medical document i is not cited among the other medical documents, wherein the medical document in which the medical document i is cited includes directly referencing the medical document i and indirectly referencing the medical document i;
determining a third score of the medical document j on the medical document i according to the second score and the publishing time of the medical document j, the second score of the medical document i and the preset time node, wherein the medical document j refers to any medical document in the medical document i, and the third score of the medical document i, which is not referred to the medical document i, is determined to be 0.
In some possible embodiments, the processor 502 is specifically configured to, in determining the third score of the medical document j for the medical document i according to the second score and the publication time of the medical document j, the second score of the medical document i, and the preset time node, perform the following operations:
In the case that the medical document j directly refers to the medical document i, determining a first average value between the medical document j and a second score of the medical document i and a first time difference between the publishing time of the medical document j and the preset time node, and determining a third score of the medical document j on the medical document i according to the first average value and the first time difference;
when the medical document j directly refers to the medical document k and the medical document i is not referred to, and the medical document k directly refers to the medical document i, determining a third score of the medical document j to the medical document k and a third score of the medical document k to the medical document i, and taking a product of the third score of the medical document j to the medical document k and the third score of the medical document k to the medical document i as the third score of the medical document j to the medical document i.
Specifically, the transceiver 501 may be the transceiver unit 401 of the medical document sorting apparatus 400 of the embodiment illustrated in fig. 4, and the processor 502 may be the processing unit 402 of the medical document sorting apparatus 400 of the embodiment illustrated in fig. 4.
The medical document sorting device in the application can comprise a smart Phone (such as an Android mobile Phone, an iOS mobile Phone, a Windows Phone mobile Phone and the like), a tablet computer, a palm computer, a notebook computer, a mobile internet device MID (Mobile Internet Devices, abbreviated as MID) or a wearable device and the like. The above-described medical document ordering devices are merely examples and are not intended to be exhaustive, including but not limited to the above-described medical document ordering devices. In practical application, the medical document sorting apparatus may further include: intelligent vehicle terminals, computer equipment, etc.
The present application also provides a computer storage medium storing a computer program for execution by a processor to implement some or all of the steps of any one of the medical document ordering methods as set forth in the method embodiments above.
Embodiments of the present application also provide a computer program product comprising a non-transitory computer-readable storage medium storing a computer program operable to cause a computer to perform some or all of the steps of any of the medical document ordering methods as set forth in the method embodiments above.
It should be noted that, for simplicity of description, the foregoing method embodiments are all expressed as a series of action combinations, but it should be understood by those skilled in the art that the present application is not limited by the order of actions described, as some steps may be performed in other order or simultaneously in accordance with the present application. Further, those skilled in the art will also appreciate that the embodiments described in the specification are all alternative embodiments, and that the acts and modules referred to are not necessarily required in the present application.
In the foregoing embodiments, the descriptions of the embodiments are emphasized, and for parts of one embodiment that are not described in detail, reference may be made to related descriptions of other embodiments.
In the several embodiments provided in this application, it should be understood that the disclosed apparatus may be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative, such as the division of the units, merely a logical function division, and there may be additional manners of dividing the actual implementation, such as multiple units or components may be combined or integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be an indirect coupling or communication connection via some interfaces, devices or units, or may be in electrical or other forms.
The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in each embodiment of the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units described above may be implemented either in hardware or in software program modules.
The integrated units, if implemented in the form of software program modules, may be stored in a computer-readable memory for sale or use as a stand-alone product. Based on such understanding, the technical solution of the present application may be embodied in essence or a part contributing to the prior art or all or part of the technical solution in the form of a software product stored in a memory, including several instructions for causing a computer device (which may be a personal computer, a server or a network device, etc.) to perform all or part of the steps of the method described in the embodiments of the present application. And the aforementioned memory includes: a U-disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a removable hard disk, a magnetic disk, or an optical disk, or other various media capable of storing program codes.
Those of ordinary skill in the art will appreciate that all or a portion of the steps in the various methods of the above embodiments may be implemented by a program that instructs associated hardware, and the program may be stored in a computer readable memory, which may include: flash disk, read-Only Memory (ROM), random access Memory (Random Access Memory, RAM), magnetic disk or optical disk.
The foregoing has outlined rather broadly the more detailed description of embodiments of the present application, wherein specific examples are provided herein to illustrate the principles and embodiments of the present application, the above examples being provided solely to assist in the understanding of the methods of the present application and the core ideas thereof; meanwhile, as those skilled in the art will have modifications in the specific embodiments and application scope in accordance with the ideas of the present application, the present description should not be construed as limiting the present application in view of the above.
Claims (7)
1. A method of medical document ordering comprising:
acquiring citation relations among a plurality of medical documents and publishing time of each medical document in the plurality of medical documents;
determining a directed graph of the plurality of medical documents under a preset time node according to the quotation relation of the plurality of medical documents and the publishing time of each medical document;
Determining a first score for each of the plurality of medical documents from the corresponding directed graph of the plurality of medical documents, comprising: determining a transfer matrix corresponding to the plurality of medical documents according to the directed graphs corresponding to the plurality of medical documents; determining a first score for each of the plurality of medical documents based on the transfer matrices corresponding to the plurality of medical documents and the number of the plurality of medical documents;
determining the target score of each medical document under the preset time node according to the directed graph corresponding to the medical documents and the first score of each medical document, wherein the target score comprises the following steps: normalizing the first scores of the plurality of medical documents to obtain second scores corresponding to the medical documents; obtaining a target score corresponding to a medical document i according to the directed graph and the second score corresponding to each medical document, wherein the medical document i is any medical document in the plurality of medical documents;
determining a third score of the medical document j on the medical document i according to the second score and the publishing time of the medical document j, the second score of the medical document i and the preset time node, wherein the third score comprises the following steps:
In the case that the medical document j directly refers to the medical document i, determining a first average value between the medical document j and a second score of the medical document i and a first time difference between the publishing time of the medical document j and the preset time node, and determining a third score of the medical document j on the medical document i according to the first average value and the first time difference;
determining a third score of the medical document j on the medical document k and a third score of the medical document k on the medical document i, and taking the product of the third score of the medical document j on the medical document k and the third score of the medical document k on the medical document i as the third score of the medical document j on the medical document i, when the medical document j directly references the medical document k and the medical document i is not referenced, and the medical document k directly references the medical document i;
and sorting the medical documents according to the target scores of the medical documents at the preset time nodes.
2. The method according to claim 1, wherein the determining the directed graph of the plurality of medical documents at the preset time node according to the reference relationship of the plurality of medical documents and the publication time of each medical document comprises:
Determining a target medical document corresponding to the medical document i in the plurality of medical documents according to the reference relation among the medical documents in the plurality of medical documents and the publishing time of the medical document i, wherein the medical document i is any medical document in the plurality of medical documents, and the target medical document is the medical document which refers to the medical document i in the plurality of medical documents;
creating a directed path from the medical document i to the target medical document, and taking medical documents except the target medical document in the plurality of medical documents as isolated nodes to obtain a directed graph of the plurality of medical documents at a preset time node.
3. The method according to claim 1, wherein the obtaining the target score corresponding to the medical document i according to the directed graph and the second score corresponding to each medical document comprises:
determining a third score for each of the plurality of medical documents to the medical document i based on the directed graph and the second score for each medical document;
and summing the third score of the medical document i and the second score of the medical document i by each medical document in the other medical documents to obtain a target score corresponding to the medical document i.
4. The method of claim 3, wherein determining a third score for each of the plurality of medical documents other than the medical document i based on the directed graph and the second score for each medical document comprises:
determining, from the directed graph, a medical document in which the medical document i is cited and a medical document in which the medical document i is not cited among the other medical documents, wherein the medical document in which the medical document i is cited includes directly referencing the medical document i and indirectly referencing the medical document i;
determining a third score of the medical document j on the medical document i according to the second score and the publishing time of the medical document j, the second score of the medical document i and the preset time node, wherein the medical document j refers to any medical document in the medical document i, and the third score of the medical document i not referring to the medical document i is determined to be 0.
5. A medical document ordering apparatus, comprising:
the receiving and transmitting unit is used for acquiring the quotation relation among the plurality of medical documents and the publishing time of each medical document in the plurality of medical documents;
The processing unit is used for determining a directed graph of the plurality of medical documents under a preset time node according to the quotation relation of the plurality of medical documents and the publishing time of each medical document;
the processing unit is further configured to determine, according to the directed graphs corresponding to the plurality of medical documents, a first score of each medical document in the plurality of medical documents, including: determining a transfer matrix corresponding to the plurality of medical documents according to the directed graphs corresponding to the plurality of medical documents; determining a first score for each of the plurality of medical documents based on the transfer matrices corresponding to the plurality of medical documents and the number of the plurality of medical documents;
the processing unit is further configured to determine, according to the directed graphs corresponding to the multiple medical documents and the first score of each medical document, a target score of each medical document at the preset time node, where the target score includes: normalizing the first scores of the plurality of medical documents to obtain second scores corresponding to the medical documents; obtaining a target score corresponding to a medical document i according to the directed graph and the second score corresponding to each medical document, wherein the medical document i is any medical document in the plurality of medical documents;
Determining a third score of the medical document j on the medical document i according to the second score and the publishing time of the medical document j, the second score of the medical document i and the preset time node, wherein the third score comprises the following steps:
in the case that the medical document j directly refers to the medical document i, determining a first average value between the medical document j and a second score of the medical document i and a first time difference between the publishing time of the medical document j and the preset time node, and determining a third score of the medical document j on the medical document i according to the first average value and the first time difference;
determining a third score of the medical document j on the medical document k and a third score of the medical document k on the medical document i, and taking the product of the third score of the medical document j on the medical document k and the third score of the medical document k on the medical document i as the third score of the medical document j on the medical document i, when the medical document j directly references the medical document k and the medical document i is not referenced, and the medical document k directly references the medical document i;
The processing unit is further configured to rank the plurality of medical documents according to the target score of each medical document at the preset time node.
6. An electronic device, comprising: a processor connected to a memory for storing a computer program, the processor being configured to execute the computer program stored in the memory to cause the electronic device to perform the method of any one of claims 1-4.
7. A computer readable storage medium, characterized in that the computer readable storage medium stores a computer program, which is executed by a processor to implement the method of any of claims 1-4.
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| CN202011153172.4A CN112286988B (en) | 2020-10-23 | 2020-10-23 | Medical document ordering method, device, electronic equipment and storage medium |
| PCT/CN2020/131808 WO2021179687A1 (en) | 2020-10-23 | 2020-11-26 | Medical literature sorting method and apparatus, electronic device and storage medium |
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| CN202011153172.4A CN112286988B (en) | 2020-10-23 | 2020-10-23 | Medical document ordering method, device, electronic equipment and storage medium |
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Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101887460A (en) * | 2010-07-14 | 2010-11-17 | 北京大学 | Document quality assessment method and application |
| WO2011159646A1 (en) * | 2010-06-14 | 2011-12-22 | Topsy Labs, Inc. | A system and method for determining quality of cited objects in search results based on the influence of citing subjects |
| CN105740452A (en) * | 2016-02-03 | 2016-07-06 | 北京工业大学 | Scientific and technical literature importance degree evaluation method based on PageRank and time decay |
| CN109118029A (en) * | 2017-06-22 | 2019-01-01 | 腾讯科技（深圳）有限公司 | Object order processing method, device, computer equipment and storage medium |
| CN109376218A (en) * | 2018-09-14 | 2019-02-22 | 大连理工大学 | One kind being based on cascade paper impact factor appraisal procedure |
| CN111198897A (en) * | 2018-11-19 | 2020-05-26 | 中国农业大学 | Scientific research hotspot topic analysis method and device and electronic equipment |
Family Cites Families (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105589948B (en) * | 2015-12-18 | 2018-10-12 | 重庆邮电大学 | A kind of reference citation network visualization and literature recommendation method and system |
| CN105740386B (en) * | 2016-01-27 | 2020-07-21 | 北京航空航天大学 | Thesis searching method and device based on sorting integration |
| US11100422B2 (en) * | 2017-01-24 | 2021-08-24 | International Business Machines Corporation | System for evaluating journal articles |
| CN107391659B (en) * | 2017-07-18 | 2020-05-22 | 北京工业大学 | Citation network academic influence evaluation ranking method based on credibility |
| US10540410B2 (en) * | 2017-11-15 | 2020-01-21 | Sap Se | Internet of things structured query language query formation |
-
2020
- 2020-10-23 CN CN202011153172.4A patent/CN112286988B/en active Active
- 2020-11-26 WO PCT/CN2020/131808 patent/WO2021179687A1/en active Application Filing
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2011159646A1 (en) * | 2010-06-14 | 2011-12-22 | Topsy Labs, Inc. | A system and method for determining quality of cited objects in search results based on the influence of citing subjects |
| CN101887460A (en) * | 2010-07-14 | 2010-11-17 | 北京大学 | Document quality assessment method and application |
| CN105740452A (en) * | 2016-02-03 | 2016-07-06 | 北京工业大学 | Scientific and technical literature importance degree evaluation method based on PageRank and time decay |
| CN109118029A (en) * | 2017-06-22 | 2019-01-01 | 腾讯科技（深圳）有限公司 | Object order processing method, device, computer equipment and storage medium |
| CN109376218A (en) * | 2018-09-14 | 2019-02-22 | 大连理工大学 | One kind being based on cascade paper impact factor appraisal procedure |
| CN111198897A (en) * | 2018-11-19 | 2020-05-26 | 中国农业大学 | Scientific research hotspot topic analysis method and device and electronic equipment |
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