CN114153716B - Real-time portrait generation method for people and nobody objects under semantic information exchange network - Google Patents
Real-time portrait generation method for people and nobody objects under semantic information exchange network Download PDFInfo
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Abstract
The invention discloses a real-time portrait generation method for an unmanned object under a semantic information exchange network, and relates to the fields of big data application technology and user portrait construction; the object image of the invention is composed of a spatio-temporal image of high frequency variation and a relatively solidified task image. Constructing a task portrait group by acquiring relevant data of people and by means of technologies such as entity identification, data mining and the like; when an unmanned object executes a task, the spatiotemporal portrait part updates the portrait content in real time according to the current spatiotemporal state of the unmanned object, analyzes the information received and sent by the unmanned object in real time to acquire key information of the task, and updates the task portrait part by matching the portrait of the task from the task portrait group according to the information. The method can generate object portraits with multiple dimensions, can update the content of the object portraits in real time according to the situation of change in a task execution site, meets the property requirement of complex and changeable situation of the task execution site, and can assist in the real-time accurate distribution of messages in a semantic information exchange network.
Description
Technical Field
The invention relates to the fields of big data application technology and user portrait construction, in particular to a real-time portrait generation method for an object with or without a human body under a semantic information exchange network.
Background
The user portrait is used as an effective tool for sketching a target user and connecting user appeal and design direction, and the target is to establish a label for describing user characteristics in multiple dimensions by analyzing user data, so that the characteristics of the user in multiple aspects are described by using label attributes, and the requirements of the user are further mined. User portrayal is applied in a plurality of fields at present, particularly the E-commerce field, a platform can abstract each concrete information of a user into labels, and the labels are utilized to embody the user image, so that targeted services are provided for the user.
However, in the field of semantic information exchange, the user portrait technology has not been well applied. Especially in the information distribution direction. With the development of modern technology, loads carried by people and nobody equipment are diversified and have more and more powerful functions, so that the types and formats of acquired information are continuously increased, under the scene of a semantic information exchange network, the demand of people and nobody objects on the information is different and large, and commanders are difficult to clearly determine the demand of people and nobody objects, so that the objects are difficult to obtain the information required by the objects. The traditional information distribution system can only distribute according to the customization and subscription behaviors of each object with or without people. The information distribution system is in mechanized distribution and cannot push information to the objects with or without people according to the current situation and the change situation of the objects. Thereby reducing the ability of the presence or absence of a human subject to obtain real-time and accurate information. Under such circumstances, it is an urgent need to solve the problems of understanding the environment of an object, bearing a role, executing a task, and the like, constructing a real-time representation of the presence or absence of a human object in a semantic information exchange network, clarifying the most urgent need for information assurance of the presence or absence of a human object, processing information as needed, and improving the real-time performance and accuracy of information exchange.
Disclosure of Invention
The invention aims to meet the requirement of intelligent information pushing under a semantic information exchange network, and provides a real-time portrait generation method for an unmanned object under the semantic information exchange network.
In order to achieve the technical purpose, the technical scheme of the invention is realized as follows:
a method for generating a real-time portrait of an object with or without a person under a semantic information exchange network comprises the following steps:
(1) acquiring relevant data of the object with or without the person, wherein the relevant data of the object with or without the person comprises attribute data of the object with or without the person, message content received by the object with or without the person, message content sent by the object with or without the person, behavior data of the object with or without the person and task relevant historical data;
(2) based on the relevant data of the object with or without people, constructing a task portrait group by means of named entity recognition, event extraction and data mining technologies and combining expert knowledge;
(3) designing an unmanned object portrait model which comprises a space-time portrait and a task portrait, and constructing an object initial portrait according to the relevant data of the unmanned object;
(4) after the task starts, updating a space-time portrait part in the object initial portrait in real time according to the current time and the position of the object with or without a person; and updating the task portrait part in the object initial portrait by analyzing the message content received or sent by the unmanned object in real time and matching the analysis result with the tasks in the task portrait group.
Further, the task portrait group constructed in the step (2) at least comprises attack, defense, guarantee, collaboration and interference tasks.
Further, in the step (3), the spatiotemporal image contains time and space attributes of high-frequency change, namely the geographic position of the existing and existing human objects and the current time; the task representation contains relatively solidified content that is of interest to accomplish the task.
Further, the step (4) of matching the analysis result with the task in the task portrait group to update the task portrait part in the object initial portrait includes the following steps:
and calculating the similarity of the analysis result and each task in the task image group, and selecting the task image with the maximum similarity to update the task image part in the object initial image.
Further, in the step (4), the task portrait part in the object initial portrait is updated by analyzing the content of the message received or sent by the unmanned object in real time and matching the analysis result with the task in the task portrait group, and the method specifically comprises the following steps:
key information related to the task name is analyzed from messages received or sent by the object with or without people in real time;
judging whether the analyzed task is completely the same as the task in the object initial image, if so, not updating the task image part; and if the task image is different from the original object image, performing semantic similarity calculation by using the analyzed key information related to the task name and each task in the task image group, selecting the task image content with the maximum similarity, and adding the task image content into the object initial image to complete the updating of the task image part in the object initial image.
Further, when the task image portion is updated, if a plurality of tasks are simultaneously present in the task image portion, the tasks are independent of each other, the life cycle of the task image portion is determined by the task execution state, and when the task execution state is "completed", the corresponding task image life cycle is completed.
According to the technical scheme, the invention has the following advantages:
in the technical scheme provided by the invention, the real-time portrait of the unmanned object under the semantic information exchange network is constructed by analyzing the attribute data of the unmanned object, the message content received and sent by the unmanned object and the behavior data of the unmanned object under the semantic information exchange network, and the portrait construction technology is applied to the scene of the semantic information exchange network; extracting multi-dimensional target characteristics from the data, wherein the constructed portrait system comprises multi-dimensional contents such as space-time attributes, task execution related requirements and the like; the scheme provided by the invention can update the object portrait content in real time according to the situation that the existence of the change in the task execution of the unmanned object under the scene of the semantic information exchange network, so as to improve the accuracy and the real-time performance of message distribution in the semantic information exchange network.
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FIG. 1 is an overall process framework layout diagram of the present invention.
FIG. 2 is a flow chart of task portrait update rules in the present invention.
Detailed Description
The following description of the embodiments of the present invention is provided in order to better understand the present invention for those skilled in the art with reference to the accompanying drawings. It is to be expressly noted that in the following description, a detailed description of known functions and designs will be omitted when it may obscure the subject matter of the present invention.
FIG. 1 is a schematic flow chart diagram of a method for generating a real-time portrait of an object with or without a human being under a semantic information exchange network according to an embodiment of the present invention.
In this embodiment, as shown in fig. 1, the method for generating a real-time portrait of an object with or without a human being under a semantic information exchange network specifically includes the following steps:
(1) acquiring relevant data of the object with or without a person, wherein the relevant data comprises attribute data of the object with or without a person, message content received by the object with or without a person, message content sent by the object with or without a person, behavior data of the object with or without a person and task-related historical data;
(2) based on the relevant data of the object with or without people, constructing a task portrait group by means of named entity recognition, event extraction and data mining technologies and combining expert knowledge; the task portrait group at least comprises attack, defense, guarantee, cooperation and interference tasks.
(3) Designing an unmanned object portrait model which comprises a space-time portrait and a task portrait, and constructing an object initial portrait according to the relevant data of the unmanned object; the space-time portrait comprises time and space attributes with high frequency change, namely the geographic position of the existing and the existing objects and the time of the current moment; the task representation contains relatively solidified content that is of interest to accomplish the task.
(4) After the task starts, updating a space-time portrait part in the object initial portrait in real time according to the current time and the position of the object with or without a person; and updating the task portrait part in the object initial portrait by analyzing the message content received or sent by the unmanned object in real time and matching the analysis result with the tasks in the task portrait group.
As shown in FIG. 2, the task portrait part update specifically includes the following processes:
key information related to the task name is analyzed from messages received or sent by the object with or without people in real time; judging whether the analyzed task is completely the same as the task in the object initial image, if so, not updating the task image part; and if the task image is different from the original object image, performing semantic similarity calculation by using the analyzed key information related to the task name and each task in the task image group, selecting the task image content with the maximum similarity, and adding the task image content into the object initial image to complete the updating of the task image part in the object initial image.
Further, when the task image portion is updated, if a plurality of tasks are simultaneously present in the task image portion, the tasks are independent of each other, the life cycle of the task image portion is determined by the task execution state, and when the task execution state is "complete", the corresponding task image life cycle is complete and will automatically disappear.
Although illustrative embodiments of the present invention have been described above to facilitate the understanding of the present invention by those skilled in the art, it should be understood that the present invention is not limited to the scope of the embodiments, and various changes may be made apparent to those skilled in the art as long as they are within the spirit and scope of the present invention as defined and defined by the appended claims, and all matters of the invention which utilize the inventive concepts are protected.
Claims (6)
1. A method for generating a real-time portrait of an object with or without a person under a semantic information exchange network is characterized by comprising the following steps:
(1) acquiring relevant data of the object with or without the person, wherein the relevant data comprises attribute data of the object with or without the person, message content received by the object with or without the person, message content sent by the object with or without the person, behavior data of the object with or without the person and task relevant historical data;
(2) based on the relevant data of the object with or without people, constructing a task portrait group by means of named entity recognition, event extraction and data mining technology and combining expert knowledge;
(3) designing an unmanned object portrait model which comprises a space-time portrait and a task portrait, and constructing an unmanned object initial portrait according to the relevant data of the unmanned object;
(4) after the task starts, updating a spatiotemporal image part in the initial image of the object with or without the person in real time according to the current time and the position of the object with or without the person; and updating the task portrait part in the initial portrait of the unmanned object by analyzing the content of the message received or sent by the unmanned object in real time and matching the analysis result with the task in the task portrait group.
2. The method for generating real-time portrait of an unmanned object under semantic information exchange network according to claim 1, wherein the task portrait group constructed in step (2) at least comprises attacking, defending, guaranteeing, coordinating and interfering tasks.
3. The method for generating a real-time portrait of an object with or without human beings under a semantic information exchange network according to claim 1, wherein in the step (3), the spatiotemporal portrait includes time and space attributes with high frequency changes, namely, the geographical position of the object with or without human beings at that time and the current time; the task representation contains relatively solidified content that is of interest to accomplish the task.
4. The method for generating real-time portrait of the unmanned object under semantic information exchange network according to claim 1, wherein the step (4) of matching the analysis result with the task in the task portrait group to update the task portrait part in the initial portrait of the unmanned object comprises the following steps:
and calculating the similarity of the analysis result and each task in the task image group, and selecting the task image with the maximum similarity to update the task image part in the initial image of the unmanned object.
5. The method for generating real-time portrait of the object with or without human beings under semantic information exchange network according to claim 4, wherein the step (4) of updating the task portrait part in the initial portrait of the object with or without human beings by analyzing the content of the message received or sent by the object with or without human beings in real time and matching the analysis result with the task in the task portrait group comprises the following steps:
key information related to the task name is analyzed from messages received or sent by the object with or without people in real time;
judging whether the analyzed task is completely the same as the task in the object initial image, if so, not updating the task image part; and if the task image is different from the original object image, performing semantic similarity calculation by using the analyzed key information related to the task name and each task in the task image group, selecting the task image content with the maximum similarity, and adding the task image content into the object initial image to complete the updating of the task image part in the object initial image.
6. The method for generating a real-time image of an unmanned object under a semantic information exchange network according to claim 5, wherein when the task image portion is updated, if a plurality of tasks are simultaneously present in the task image portion, the tasks are independent of each other, a life cycle of the task image portion is determined by a task execution state, and when the task execution state is "completed", the corresponding life cycle of the task image is completed.
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