CN112579904B - Analysis method for realizing migration and propagation based on graph relationship and time - Google Patents
Analysis method for realizing migration and propagation based on graph relationship and time Download PDFInfo
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Abstract
The invention relates to an analysis method for realizing migration propagation based on a graph relation and time, which is characterized in that a heat curve from the initial time to the current time of an event is drawn, a time period with the maximum slope is found out based on the curve, the weight type influencing the heat development trend of the event in the time period is found out, the weight types influencing the heat of the event in the other two time periods are found out, the influence indexes of all weights on the heat are analyzed to respectively obtain the weights with the indexes ranked at the front, and the weight types with the weights ranked at the front are corrected or deleted according to the expected purpose.
Description
Technical Field
The invention relates to data analysis, in particular to an analysis method for realizing migration and propagation based on a graph relation and time.
Background
In data analysis, the heat of time, that is, the change of events over time, is generally measured according to two indexes, namely, time and heat index. Data analysis in the traditional mode generally can only be aimed at analysis of the trend of the heat of the event development along with the time, namely analysis of the hot event. For example, publication number CN109271639a discloses a method and device for discovering a hot event, which relate to the technical field of information processing and include: acquiring text content flowing through a network node to be monitored in a current time period; performing data processing on the text content to obtain candidate hot words contained in the text content, word frequencies corresponding to the candidate hot words and word frequencies corresponding to the target phrases; performing comprehensive hotness value calculation on the candidate hotwords based on the word frequency corresponding to the candidate hotwords and the word frequency corresponding to the target phrase to obtain a comprehensive hotness value of each candidate hotword; and determining a hot event on the network node to be monitored in the current time period according to the comprehensive heat value of each candidate hot word. According to the method, candidate hotwords with more information content can be obtained through data processing, comprehensive hotness value calculation is carried out on the candidate hotwords, the comprehensive hotness value is obtained, information considered in the calculation process is more comprehensive, and the technical problems that the hotword information amount is small and hotness calculation consideration is incomplete in the existing hotword discovery method are solved.
Disclosure of Invention
The invention aims to overcome the defects of the prior art, and provides an analysis method for realizing migration and propagation based on a graph relation and time, which can analyze the weight affecting time development or heat in an event.
The aim of the invention is realized by the following technical scheme:
an analysis method for realizing migration propagation based on a graph relation and time, the method comprises the following steps:
s100: drawing event start time t 1 To the current time t 2 Heat curve p of (2);
s200: finding a time period with the maximum slope k based on the graph, denoted as t 2 '-t 3 ' find t 2 '-t 3 Weight type Q affecting event heat development trend in' time period m Wherein m is the number of weight types;
s300: analysis time point t 2 ' previous time period t 1 '-t 2 ' in, time point t 3 ' last time period t 3 '-t 4 In' weight types affecting the trend of event heat development are respectively marked as P n And G j Wherein n, j represent the number of types of weights, respectively;
s400: analysis weight Q m 、P n 、G j The influence indexes of the middle on the heat degree are respectively obtained to obtain the weights with the indexes ranked at the front, and the weights are recorded as Q 1 、Q 2 、Q 3 ……，P 1 、P 2 、P 3 ……，G 1 、G 2 、G 3 ……；
S500: analysis Q 1 、Q 2 、Q 3 ，P 1 、P 2 、P 3 ，G 1 、G 2 、G 3 Whether the same weight is contained or not, combining the same weight, and sequencing according to the combined indexes to obtain an overall weight index ranking;
s600: the weight value is corrected or the corresponding weight type is deleted for the weight type with the weight index ranked forward based on the intended purpose.
Further, the time period t 2 '-t 3 ' employ traversal period t 1 -t 2 The time period during which the slope k is greatest.
Further, in the traversing process, the minimum time unit changed according to the slope k is sequentially traversed as a time node, and the part with the same slope is used as an integral time period.
Further, the time t 1 '-t 2 ' is the time point t 2 ' a period of constant pre-slope k, a period of time t 3 '-t 4 ' is the time point t 3 The' post slope k is a constant segment.
Further, the impact index on the heat refers to the positive benefit of the weight type on the event.
Further, the positive benefits comprise the reading quantity, the transfer quantity, the attention degree and the good score of the event.
The beneficial effects of the invention are as follows: the method is based on a graph technology, and the weight type in the event spreading process is analyzed to obtain the weight type with the greatest influence on the event.
Drawings
Fig. 1 is a schematic diagram of the present invention.
Detailed Description
The technical scheme of the present invention is described in further detail below with reference to specific embodiments, but the scope of the present invention is not limited to the following description.
An analysis method for realizing migration propagation based on a graph relation and time, the method comprises the following steps:
s100: drawing event start time t 1 To the current time t 2 Heat curve p of (2);
s200: finding a time period with the maximum slope k based on the graph, denoted as t 2 '-t 3 ' find t 2 '-t 3 Weight type Q affecting event heat development trend in' time period m Wherein m is the number of weight types;
s300: analysis time point t 2 ' previous time period t 1 '-t 2 ' in, time point t 3 ' last time period t 3 '-t 4 In' weight types affecting the trend of event heat development are respectively marked as P n And G j Wherein n, j represent the number of types of weights, respectively;
s400: analysis weight Q m 、P n 、G j The influence indexes of the middle on the heat degree are respectively obtained to obtain the weights with the indexes ranked at the front, and the weights are recorded as Q 1 、Q 2 、Q 3 ……，P 1 、P 2 、P 3 ……，G 1 、G 2 、G 3 ……；
S500: analysis Q 1 、Q 2 、Q 3 ，P 1 、P 2 、P 3 ，G 1 、G 2 、G 3 Whether the same weight is contained or not, combining the same weight, and sequencing according to the combined indexes to obtain an overall weight index ranking;
s600: the weight value is corrected or the corresponding weight type is deleted for the weight type with the weight index ranked forward based on the intended purpose.
Optionally, an analysis method for implementing migration propagation based on a graph relationship and time includes:
s100: drawing event start time t 1 To the current time t 2 Heat curve p of (2);
s200: based on graph traversal time period t 1 -t 2 The time period in which the slope k is greatest is determined by means of (a), denoted t 2 '-t 3 The traversing process is to sequentially traverse the minimum time unit according to the change of the slope k as a time node, and the part with the same slope is used as an integral time period. Find t 2 '-t 3 Weight type Q affecting event heat development trend in' time period m Wherein m is the number of weight types;
s300: analysis time point t 2 ' previous time period t 1 '-t 2 ' in, time point t 3 ' last time period t 3 '-t 4 In' weight types affecting the trend of event heat development are respectively marked as P n And G j Wherein n, j represent the number of types of weights, respectively;
s400: analysis weight Q m 、P n 、G j The influence indexes of the middle on the heat degree are respectively obtained to obtain the weights with the indexes ranked at the front, and the weights are recorded as Q 1 、Q 2 、Q 3 ……，P 1 、P 2 、P 3 ……，G 1 、G 2 、G 3 ……；
S500: analysis Q 1 、Q 2 、Q 3 ，P 1 、P 2 、P 3 ，G 1 、G 2 、G 3 Whether the same weight is contained or not, combining the same weight, and sequencing according to the combined indexes to obtain an overall weight index ranking;
s600: the weight value is corrected or the corresponding weight type is deleted for the weight type with the weight index ranked forward based on the intended purpose.
Optionally, an analysis method for realizing migration propagation based on graph relationship and time, and time t 1 '-t 2 ' is the time point t 2 ' a period of constant pre-slope k, a period of time t 3 '-t 4 ' is the time point t 3 The' post slope k is a constant segment.
Optionally, an analysis method for implementing migration propagation based on a graph relationship and time, and an impact index on heat refers to positive benefits brought by the weight type on an event. The positive benefits include the reading amount, transfer amount, attention, and good score of the event.
Optionally, the invention also provides an analysis method for realizing migration propagation based on the graph relationship and time, and besides the weight with the greatest influence on the event by the analysis recorded by the method, the invention also provides an influence on adverse factors of the event, and the same is true in the weight Q m 、P n 、G j Extracting the weight type with the lowest influence index on heat degree, even the weight type with negative influence, and eliminating or adjusting the corresponding weight type in the intervention process of the eventTo enable positive guidance of events.
The foregoing is merely a preferred embodiment of the invention, and it is to be understood that the invention is not limited to the form disclosed herein but is not to be construed as excluding other embodiments, but is capable of numerous other combinations, modifications and environments and is capable of modifications within the scope of the inventive concept, either as taught or as a matter of routine skill or knowledge in the relevant art. And that modifications and variations which do not depart from the spirit and scope of the invention are intended to be within the scope of the appended claims.
Claims (6)
1. An analysis method for realizing migration and propagation based on a graph relation and time is characterized by comprising the following steps:
s100: drawing event start time t 1 To the current time t 2 Heat curve p of (2);
s200: finding a time period with the maximum slope k based on the graph, denoted as t 2 '-t 3 ' find t 2 '-t 3 Weight type Q affecting event heat development trend in' time period m Wherein m is the number of weight types;
s300: analysis time point t 2 ' previous time period t 1 '-t 2 ' in, time point t 3 ' last time period t 3 '-t 4 In' weight types affecting the trend of event heat development are respectively marked as P n And G j Wherein n and j respectively represent the number of corresponding weight types;
s400: analysis weight Q m 、P n 、G j The influence indexes of the middle on the heat degree are respectively obtained to obtain the weights with the indexes ranked at the front, and the weights are recorded as Q 1 、Q 2 、Q 3 ……，P 1 、P 2 、P 3 ……，G 1 、G 2 、G 3 ……；
S500: analysis Q 1 、Q 2 、Q 3 ，P 1 、P 2 、P 3 ，G 1 、G 2 、G 3 Whether or not the same weight is contained and the same weight is enteredMerging the rows, and sorting according to the merged indexes to obtain the overall weight index ranking;
s600: the weight value is corrected or the corresponding weight type is deleted for the weight type with the weight index ranked forward based on the intended purpose.
2. The analysis method for realizing migration propagation based on graph relationship and time according to claim 1, wherein the time period t 2 '-t 3 ' employ traversal period t 1 -t 2 The time period during which the slope k is greatest.
3. The analysis method for realizing migration propagation based on graph relationship and time according to claim 2, wherein the traversing process is sequentially traversed by taking a minimum time unit changed according to the slope k as a time node, and taking a part with the same slope as an integral time period.
4. The analysis method for realizing migration propagation based on graph relationship and time according to claim 3, wherein the time t 1 '-t 2 ' is the time point t 2 ' a period of constant pre-slope k, a period of time t 3 '-t 4 ' is the time point t 3 The' post slope k is a constant segment.
5. The analysis method for realizing migration propagation based on graph relationship and time according to claim 4, wherein the impact index on heat is positive benefit of the weight type on the event.
6. The analysis method for realizing migration propagation based on graph relationship and time according to claim 5, wherein the positive benefit comprises reading quantity, transfer amount, attention degree and praise rate of the event.
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| CN111680209A (en) * | 2020-04-24 | 2020-09-18 | 江苏安全技术职业学院 | Network security situation prediction system based on artificial intelligence |
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| CN109508416A (en) * | 2018-11-09 | 2019-03-22 | 四川大学 | Microblogging public sentiment event temperature and prediction of the development trend method based on number of reviews |
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