CN112861005A - Method, device and equipment for information push - Google Patents
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Abstract
The application relates to the technical field of information push, and discloses a method for information push, which comprises the following steps: acquiring user position information and extracting chat keywords; matching the user position information with a preset keyword to obtain a user position matching result; matching the chat keywords with preset keywords to obtain a chat keyword matching result; determining corresponding position scores according to the position matching results of the users, and determining corresponding chat keyword scores according to the chat keyword matching results; and carrying out information push according to the ranking scores of the preset keywords acquired according to the job scores and the chat keyword scores. According to the method, due to the fact that the position information and the chat keywords of the user are considered, the keywords which are interesting to the user can be screened out in a targeted mode, the keywords are used for obtaining corresponding push information to be pushed, and therefore the information push consideration is more comprehensive, and the experience of the user when obtaining the push information is better. The application also discloses a device and equipment for pushing the information.
Description
Technical Field
The present application relates to the field of information push technologies, and for example, to a method, an apparatus, and a device for information push.
Background
At present, with the rise and development of mobile internet technology, news information is often pushed to users by various news platforms. However, if news information is pushed blindly, the attention rate of users is often very low, the expected information delivery effect cannot be achieved, and how to push targeted information is desirable for many news platforms.
In the process of implementing the embodiments of the present disclosure, it is found that at least the following problems exist in the related art: in the prior art, information pushing is usually performed only according to single user data, and the consideration factor of information pushing is not comprehensive enough, so that the experience of a user in obtaining pushed information is poor.
Disclosure of Invention
The following presents a simplified summary in order to provide a basic understanding of some aspects of the disclosed embodiments. This summary is not an extensive overview nor is intended to identify key/critical elements or to delineate the scope of such embodiments but rather as a prelude to the more detailed description that is presented later.
The embodiment of the disclosure provides a method, a device and equipment for information push, which can improve the experience of a user in acquiring push information.
In some embodiments, the method for information push includes:
acquiring the position information of a user, and extracting chat keywords from the chat information of the user;
matching the user position information with a preset keyword to obtain a user position matching result; matching the chat keywords with the preset keywords to obtain a chat keyword matching result;
determining a position score corresponding to the position information of the user according to the position matching result of the user, and determining a chat keyword score corresponding to the chat keyword according to the chat keyword matching result;
obtaining the sorting score of the preset keyword according to the position score and the chat keyword score;
and pushing information according to the sorting scores.
In some embodiments, the apparatus for information push comprises: a processor and a memory storing program instructions, the processor being configured to execute the method for pushing information as described above when executing the program instructions.
In some embodiments, the apparatus comprises: the device for pushing information is as described above.
The method, the device and the equipment for pushing the information provided by the embodiment of the disclosure can realize the following technical effects: obtaining the role information of the user and the chat keywords in the chat information, and respectively matching the role information of the user and the chat keywords with preset keywords to obtain the matching combination of the role of the user and the matching result of the chat keywords; acquiring a position score and a chat keyword score according to a user position matching combination and a chat keyword matching result respectively, and acquiring a sorting score of a preset keyword according to the position score and the keyword score; and pushing the information according to the sorting scores. Because the job information and the chat keywords of the user are considered according to different preset keywords, keywords which are interesting to the user can be screened out in a targeted mode, and corresponding push information is obtained by utilizing the keywords to be pushed, so that the consideration factors of information pushing are more comprehensive, the attention degree of the user to the push information can be improved, and the experience of the user in obtaining the push information is better.
The foregoing general description and the following description are exemplary and explanatory only and are not restrictive of the application.
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One or more embodiments are illustrated by way of example in the accompanying drawings, which correspond to the accompanying drawings and not in limitation thereof, in which elements having the same reference numeral designations are shown as like elements and not in limitation thereof, and wherein:
fig. 1 is a schematic diagram of a method for pushing information provided by an embodiment of the present disclosure;
fig. 2 is a schematic diagram of an apparatus for pushing information according to an embodiment of the present disclosure.
Detailed Description
So that the manner in which the features and elements of the disclosed embodiments can be understood in detail, a more particular description of the disclosed embodiments, briefly summarized above, may be had by reference to the embodiments, some of which are illustrated in the appended drawings. In the following description of the technology, for purposes of explanation, numerous details are set forth in order to provide a thorough understanding of the disclosed embodiments. However, one or more embodiments may be practiced without these details. In other instances, well-known structures and devices may be shown in simplified form in order to simplify the drawing.
The terms "first," "second," and the like in the description and in the claims, and the above-described drawings of embodiments of the present disclosure, are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It should be understood that the data so used may be interchanged under appropriate circumstances such that embodiments of the present disclosure described herein may be made. Furthermore, the terms "comprising" and "having," as well as any variations thereof, are intended to cover non-exclusive inclusions.
The term "plurality" means two or more unless otherwise specified.
In the embodiment of the present disclosure, the character "/" indicates that the preceding and following objects are in an or relationship. For example, A/B represents: a or B.
The term "and/or" is an associative relationship that describes objects, meaning that three relationships may exist. For example, a and/or B, represents: a or B, or A and B.
As shown in fig. 1, an embodiment of the present disclosure provides a method for pushing information, including:
step S101, obtaining user position information, and extracting chat keywords from the chat information of the user;
step S102, matching the user position information with preset keywords to obtain a user position matching result; matching the chat keywords with preset keywords to obtain a chat keyword matching result;
step S103, determining position scores corresponding to the position information of the user according to the position matching results of the user, and determining chat keyword scores corresponding to the chat keywords according to the chat keyword matching results;
step S104, obtaining the sorting score of the preset keyword according to the position score and the chat keyword score;
and step S105, carrying out information push according to the sorting scores.
By adopting the method for information pushing provided by the embodiment of the disclosure, the role information of the user and the chat keywords in the chat information are obtained and are respectively matched with the preset keywords, so that the role matching combination and the chat keyword matching result of the user are obtained; acquiring a position score and a chat keyword score according to a user position matching combination and a chat keyword matching result respectively, and acquiring a sorting score of a preset keyword according to the position score and the keyword score; and pushing the information according to the sorting scores. Because the job information and the chat keywords of the user are considered according to different preset keywords, keywords which are interesting to the user can be screened out in a targeted mode, and corresponding push information is obtained by utilizing the keywords to be pushed, so that the consideration factors of information pushing are more comprehensive, the attention degree of the user to the push information can be improved, and the experience of the user in obtaining the push information is better.
Optionally, the obtaining of the user position information includes: acquiring initial position information of a user, and matching reference position information corresponding to the initial position information in a preset position data sheet; and determining the reference position information corresponding to the initial position information as the user position information.
Optionally, the initial position information of the user includes: the position information stored or displayed in the enterprise WeChat platform by the user. In some embodiments, different companies may have different names, i.e., different job information, for the same job, by obtaining initial job information displayed by the user in the enterprise WeChat platform and determining reference job information corresponding to the initial job information in a preset job data table as the job information of the user. Thus, the job information of the user can be standardized.
Optionally, the job data table stores a plurality of reference job information, and the reference job information corresponding to the initial job information is matched in a preset job data table, including: acquiring first eigenvectors corresponding to the initial position information and acquiring second eigenvectors corresponding to the reference position information respectively; acquiring the similarity between the initial position information and each reference position information according to the first characteristic vector and each second characteristic vector; and determining the reference position information corresponding to the similarity meeting the preset conditions as the reference position information corresponding to the initial position information.
Optionally, the initial position information is converted into a first dense vector by using the pre-training word vector, and the first dense vector is used as the first feature vector. Optionally, the reference position information is converted into a second dense vector by using the pre-training word vector, and the second dense vector is used as a second feature vector. Optionally, cosine similarity calculation is performed by using the first feature vector and each second feature vector to obtain similarity between the initial position information and each reference position information. Optionally, the reference position information corresponding to the similarity meeting the preset condition includes: and reference position information corresponding to the maximum similarity.
Optionally, the initial position information is converted into a first feature vector by an AutoEncoder auto-encoder. Optionally, the reference position information is converted into a second feature vector by an AutoEncoder.
Optionally, determining a position score corresponding to the position information of the user according to the position matching result of the user includes: under the condition that a preset keyword which is the same as the position information of the user is matched, determining a first preset score as a position score corresponding to the position information of the user; and under the condition that the preset keywords which are the same as the position information of the user are not matched, determining the second preset score as the position score corresponding to the position information of the user.
Optionally, the first predetermined score is 1. In some embodiments, in the case that the preset keyword, such as the front-end development, which is the same as the user position information, is matched, the position score corresponding to the user position information, i.e., the front-end development, is 1. Optionally, the second predetermined score is 0. In some embodiments, in the case that the preset keyword identical to the position information of the user is not matched, the position score corresponding to the position information of the user is 0.
Optionally, extracting a chat keyword from the chat information of the user includes: the method comprises the steps of obtaining the chat information of a user in a set time window, carrying out word segmentation processing on the chat information of the user, and obtaining chat keywords. Optionally, the time window is set to 1 month. Optionally, the chat message is a text message of the chat log. Optionally, performing word segmentation processing on the chat information of the user includes: the method comprises the step of carrying out word segmentation processing on chat information of a user through a Jieba word segmentation tool.
Optionally, determining a chat keyword score corresponding to the chat keyword according to the chat keyword matching result includes: under the condition that a preset keyword which is the same as the chat keyword is matched, determining the word frequency of the chat keyword in the chat information, namely the occurrence frequency of the chat keyword in the chat information as a chat keyword score corresponding to the chat keyword; and under the condition that the preset keywords which are the same as the chat keywords are not matched, determining the third preset score as the chat keyword score corresponding to the chat keywords.
Optionally, the word frequency of the chat keyword is the number of times that the chat keyword appears in the chat information in the set time window. In some embodiments, in the case that a preset keyword, such as a front-end development, which is the same as the chat keyword, is matched, the number of occurrences of the front-end development in the chat message is determined as a score of the chat keyword corresponding to the front-end development. Optionally, the third predetermined score is 0.
Optionally, obtaining a ranking score of the preset keyword according to the job score and the chat keyword score includes: acquiring behavior information of a user corresponding to a preset keyword; and calculating according to a preset first algorithm by using the position score, the chat keyword score and the behavior information to obtain the sequencing score of the preset keyword. Therefore, due to the fact that the position information, the chat keywords and the behavior information of the user are considered for different preset keywords, the keywords which are interested by the user can be screened out in a targeted mode, the corresponding push information is obtained through the keywords to be pushed, the information pushing consideration factor is comprehensive, the attention degree of the user to the push information can be improved, and the experience of the user when the user obtains the push information is better.
Optionally, the behavior information of the user corresponding to the preset keyword includes the number of times of operation of the user on the information with the preset keyword. Optionally, the number of operations on the information with the preset keyword includes: the number of clicks on information with a preset keyword, the number of collections of information with a preset keyword, the number of downloads of information with a preset keyword, and the like. In some embodiments, within a set time period, if the user clicks 5 times on news information with a preset keyword, for example, the behavior information developed by the user and the front-end is 5.
Optionally, by calculating y ═ wa*xa+wb*xb+wc*xcObtaining a ranking score of a preset keyword; wherein y is the ranking score of the preset keywords, waScore a weight, x, for the jobaIs the position score, wbScoring a value of a weight, x, for a chat keywordbScore for chat keywords, wcAs a weight of behavior information, xcIs a behavior information score. Optionally, the position score weight, the chat keyword score weight, and the behavior information weight are all preset. In some embodiments, if it is required to highlight the behavior information of the user corresponding to the preset keyword, w is increasedc(ii) a If the chat information of the user needs to be highlighted, increasing wb。
Optionally, obtaining a ranking score of the preset keyword according to the job score and the chat keyword score includes: acquiring behavior information of a user corresponding to a preset keyword, and acquiring label selection information of the user; matching the tag selection information with a preset keyword to obtain a tag selection matching result; acquiring a label selection score corresponding to the label selection information according to the label selection matching result; and calculating according to a preset second algorithm by using the position score, the chat keyword score, the label selection score and the behavior information to obtain the sorting score of the preset keyword. Therefore, due to the fact that the position information, the chat keywords, the behavior information corresponding to the preset keywords and the label selection information of the user are considered for different preset keywords, the keywords which the user is interested in can be screened out in a targeted mode, the corresponding push information is obtained by the keywords to be pushed, the information pushing consideration is comprehensive, the attention degree of the user to the push information can be improved, and the experience of the user when the user obtains the push information is better.
Optionally, the tag selection information includes: a user selected tag. In some embodiments, each piece of information corresponds to a tag, and the user selects the tag to obtain the corresponding information.
Optionally, determining a tag selection score corresponding to the tag selection information according to the tag selection matching result includes: under the condition that the preset keywords which are the same as the label selection information are matched, determining a fourth preset score as a label selection score corresponding to the label selection information; and under the condition that the preset keywords which are the same as the label selection information are not matched, determining the fifth preset score as the label selection score corresponding to the label selection information.
Optionally, the fourth predetermined score is 1. In some embodiments, in the case that the preset keyword identical to the tag selection information is matched, for example, in the front-end and back-end development, the tag selection score corresponding to the tag selection information, that is, the front-end and back-end development, is 1. Optionally, the fifth predetermined score is 0. In some embodiments, in the case that the preset keyword identical to the tag selection information is not matched, the tag selection score corresponding to the tag selection information is 0.
Optionally, by calculating y ═ wa*xa+wb*xb+wc*xc+wd*xdObtaining a ranking score of a preset keyword; wherein y is the ranking score of the preset keywords, waScore a weight, x, for the jobaIs the position score, wbScoring a value of a weight, x, for a chat keywordbScore for chat keywords, wcAs a weight of behavior information, xcAs a score of the behavioral information, wdSelecting a scoring weight, x, for a tagdThe label selects a score.
Optionally, the information pushing according to the ranking score includes: pushing information corresponding to the target keyword to a user; the target keywords are preset keywords corresponding to the sorting scores meeting preset conditions.
Optionally, the target keyword is a preset keyword corresponding to the ranking score meeting a preset condition, and the preset keyword includes: the target keywords are preset keywords corresponding to the sorting scores which are larger than or equal to the set threshold value.
Optionally, the preset keywords corresponding to the ranking scores meeting the preset condition include: and sequencing the preset keywords from large to small according to the sequencing scores, wherein the target keywords are the preset keywords corresponding to the sequencing scores of the set ranks before the ranking.
Optionally, the information pushing according to the ranking score includes: and acquiring the pushing quantity of the information corresponding to the preset keywords according to the sorting scores of the preset keywords, and pushing the information according to the pushing quantity of the information corresponding to each preset keyword. For example, the user a corresponds to a preset keyword, for example: and if the sorting score of the artificial intelligence is 0.6 and the sorting score of the front-end development and the sorting score of the back-end development are 0.4, pushing 6 pieces of information corresponding to the artificial intelligence to the user A and pushing 4 pieces of information corresponding to the front-end development and the back-end development.
In some embodiments, in the enterprise WeChat-based news distribution platform, the preset keywords include company position information, such as: technical managers, front-end and back-end development, UI design, artificial intelligence, automatic driving and the like; the preset keywords include company product information, such as: company product name A; the preset keyword includes competitive company information, such as a competitive company name, and competitive product information, such as a competitive product name, etc. Optionally, the job information of the company is extracted through the recruitment website.
Acquiring initial position information, such as front and back ends, stored in an enterprise WeChat platform by a user; matching reference position information corresponding to the front end and the back end in a preset position data table to develop the front end and the back end, wherein the user position information of the user is developed for the front end and the back end; under the condition that the user position information is the same as the preset keywords, namely front-end and back-end development, the position score corresponding to the front-end and back-end development is 1.
Obtaining chat text information of a user in the latest 1 month through a chat archiving function in the enterprise WeChat platform, and performing word segmentation processing on the chat text information to obtain chat keywords; under the condition that preset keywords with the same chat keywords, such as front-end and back-end development, a company product name A and the like, are matched, the frequency of the front-end and back-end development appearing in the chat text information is used as the score of the chat keywords corresponding to the front-end and back-end development, for example, 10; the number of times the company product name a appears in the chat text message, for example, 8, is taken as the chat keyword score corresponding to the company product name a.
Acquiring behavior information corresponding to a user and a preset keyword in the latest 1 month in a news distribution platform of enterprise WeChat; for example, if the user clicks the news information with front-end and back-end development 5 times, the behavior information corresponding to the front-end and back-end development is 5; if the user clicks the news information with the company product name a 3 times, the behavior information corresponding to the company product name a by the user is 3.
In a news distribution platform of enterprise WeChat, if the label selected by the user is front-end development, the selection score of the label corresponding to the front-end development is 1, and if the user does not select the label of the company product name A, the selection score of the label corresponding to the company product name A is 0.
By calculating y as wa*xa+wb*xb+wc*xc+wd*xdRespectively obtaining the ranking score of a user on preset keywords, such as 0.8 score of the front-end and back-end development and 0.2 score of the discharge score of a company product name A; and pushing 8 pieces of news information corresponding to front-end and back-end development to the user and pushing news information corresponding to 2 company product names A through a news release platform of the enterprise WeChat. Therefore, due to the fact that the position information, the chat keywords, the behavior information corresponding to the preset keywords and the label selection information of the user are considered for different preset keywords, the keywords which the user is interested in can be screened out in a targeted mode, the corresponding push information is obtained by the keywords to be pushed, the information pushing consideration is comprehensive, the attention degree of the user to the push information can be improved, and the experience of the user when the user obtains the push information is better.
As shown in fig. 2, an apparatus for pushing information according to an embodiment of the present disclosure includes a processor (processor)100 and a memory (memory)101 storing program instructions. Optionally, the apparatus may also include a Communication Interface (Communication Interface)102 and a bus 103. The processor 100, the communication interface 102, and the memory 101 may communicate with each other via a bus 103. The communication interface 102 may be used for information transfer. The processor 100 may call program instructions in the memory 101 to perform the method for information pushing of the above-described embodiments.
Further, the program instructions in the memory 101 may be implemented in the form of software functional units and stored in a computer readable storage medium when sold or used as a stand-alone product.
The memory 101, which is a computer-readable storage medium, may be used for storing software programs, computer-executable programs, such as program instructions/modules corresponding to the methods in the embodiments of the present disclosure. The processor 100 executes functional applications and data processing by executing program instructions/modules stored in the memory 101, that is, implements the method for pushing information in the above embodiments.
The memory 101 may include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function; the storage data area may store data created according to the use of the terminal device, and the like. In addition, the memory 101 may include a high-speed random access memory, and may also include a nonvolatile memory.
By adopting the device for information pushing provided by the embodiment of the disclosure, the role information of the user and the chat keywords in the chat information are obtained and are respectively matched with the preset keywords, so that the role matching combination and the chat keyword matching result of the user are obtained; acquiring a position score and a chat keyword score according to a user position matching combination and a chat keyword matching result respectively, and acquiring a sorting score of a preset keyword according to the position score and the keyword score; and pushing the information according to the sorting scores. Because the job information and the chat keywords of the user are considered according to different preset keywords, keywords which are interesting to the user can be screened out in a targeted mode, and corresponding push information is obtained by utilizing the keywords to be pushed, so that the consideration factors of information pushing are more comprehensive, the attention degree of the user to the push information can be improved, and the experience of the user in obtaining the push information is better.
The embodiment of the present disclosure provides an apparatus, which includes the above apparatus for pushing information. The social network site matching method comprises the steps that chat keywords in user position information and chat information are obtained and are respectively matched with preset keywords, and user position matching combination and chat keyword matching results are obtained; acquiring a position score and a chat keyword score according to a user position matching combination and a chat keyword matching result respectively, and acquiring a sorting score of a preset keyword according to the position score and the keyword score; and pushing the information according to the sorting scores. Because the job information and the chat keywords of the user are considered according to different preset keywords, keywords which are interesting to the user can be screened out in a targeted mode, and corresponding push information is obtained by utilizing the keywords to be pushed, so that the consideration factors of information pushing are more comprehensive, the attention degree of the user to the push information can be improved, and the experience of the user in obtaining the push information is better.
Optionally, the device includes a computer, a smart phone, a tablet, and other smart terminals.
The embodiment of the disclosure provides a computer-readable storage medium, which stores computer-executable instructions configured to execute the above method for information push.
The present disclosure provides a computer program product, which includes a computer program stored on a computer-readable storage medium, where the computer program includes program instructions, and when the program instructions are executed by a computer, the computer executes the above method for pushing information.
The computer-readable storage medium described above may be a transitory computer-readable storage medium or a non-transitory computer-readable storage medium.
The technical solution of the embodiments of the present disclosure may be embodied in the form of a software product, where the computer software product is stored in a storage medium and includes one or more instructions to enable a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method of the embodiments of the present disclosure. And the aforementioned storage medium may be a non-transitory storage medium comprising: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes, and may also be a transient storage medium.
The above description and drawings sufficiently illustrate embodiments of the disclosure to enable those skilled in the art to practice them. Other embodiments may incorporate structural, logical, electrical, process, and other changes. The examples merely typify possible variations. Individual components and functions are optional unless explicitly required, and the sequence of operations may vary. Portions and features of some embodiments may be included in or substituted for those of others. Furthermore, the words used in the specification are words of description only and are not intended to limit the claims. As used in the description of the embodiments and the claims, the singular forms "a", "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. Similarly, the term "and/or" as used in this application is meant to encompass any and all possible combinations of one or more of the associated listed. Furthermore, the terms "comprises" and/or "comprising," when used in this application, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof. Without further limitation, an element defined by the phrase "comprising an …" does not exclude the presence of other like elements in a process, method or apparatus that comprises the element. In this document, each embodiment may be described with emphasis on differences from other embodiments, and the same and similar parts between the respective embodiments may be referred to each other. For methods, products, etc. of the embodiment disclosures, reference may be made to the description of the method section for relevance if it corresponds to the method section of the embodiment disclosure.
Those of skill in the art would appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software may depend upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the disclosed embodiments. It can be clearly understood by the skilled person that, for convenience and brevity of description, the specific working processes of the system, the apparatus and the unit described above may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the embodiments disclosed herein, the disclosed methods, products (including but not limited to devices, apparatuses, etc.) may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units may be merely a logical division, and in actual implementation, there may be another division, for example, multiple units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form. The units described as separate parts may or may not be physically separate, and parts displayed 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 can be selected according to actual needs to implement the present embodiment. In addition, functional units in the embodiments of the present disclosure may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit.
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). In some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. In the description corresponding to the flowcharts and block diagrams in the figures, operations or steps corresponding to different blocks may also occur in different orders than disclosed in the description, and sometimes there is no specific order between the different operations or steps. For example, two sequential operations or steps may in fact be executed substantially concurrently, or they may sometimes be executed in the reverse order, depending upon the functionality involved. Each block of the block diagrams and/or flowchart illustrations, and combinations of blocks in the block diagrams and/or flowchart illustrations, can be implemented by special purpose hardware-based systems that perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
Claims (10)
1. A method for information push, comprising:
acquiring the position information of a user, and extracting chat keywords from the chat information of the user;
matching the user position information with a preset keyword to obtain a user position matching result; matching the chat keywords with the preset keywords to obtain a chat keyword matching result;
determining a position score corresponding to the position information of the user according to the position matching result of the user, and determining a chat keyword score corresponding to the chat keyword according to the chat keyword matching result;
obtaining the sorting score of the preset keyword according to the position score and the chat keyword score;
and pushing information according to the sorting scores.
2. The method of claim 1, wherein obtaining user position information comprises:
acquiring initial position information of the user, and matching reference position information corresponding to the initial position information in a preset position data sheet;
and determining the reference position information as the position information of the user.
3. The method according to claim 2, wherein the job data table stores a plurality of reference job information, and the matching of the reference job information corresponding to the initial job information in the preset job data table comprises:
acquiring first eigenvectors corresponding to the initial position information and acquiring second eigenvectors corresponding to the reference position information respectively;
acquiring the similarity between the initial position information and each piece of reference position information according to the first feature vector and the second feature vector;
and determining the reference position information corresponding to the similarity meeting the preset conditions as the reference position information corresponding to the initial position information.
4. The method of claim 1, wherein determining the position score corresponding to the position information of the user according to the position matching result of the user comprises:
determining a first preset score as a position score corresponding to the position information of the user under the condition that a preset keyword identical to the position information of the user is matched; and under the condition that the preset keywords which are the same as the position information of the user are not matched, determining a second preset score as the position score corresponding to the position information of the user.
5. The method of claim 1, wherein determining the chat keyword score corresponding to the chat keyword according to the chat keyword matching result comprises:
under the condition that a preset keyword which is the same as the chat keyword is matched, determining the word frequency of the chat keyword in the chat information as a chat keyword score corresponding to the chat keyword; and under the condition that the preset keywords which are the same as the chat keywords are not matched, determining a third preset score as the score of the chat keywords corresponding to the chat keywords.
6. The method of claim 1, wherein obtaining the ranking score of the predetermined keyword according to the position score and the chat keyword score comprises:
acquiring behavior information of the user corresponding to the preset keyword;
and calculating according to a preset first algorithm by using the position score, the chat keyword score and the behavior information to obtain the sequencing score of the preset keyword.
7. The method of claim 1, wherein obtaining the ranking score of the predetermined keyword according to the position score and the chat keyword score comprises:
acquiring behavior information of the user corresponding to the preset keyword, and acquiring label selection information of the user;
matching the tag selection information with the preset keywords to obtain a tag selection matching result;
acquiring a label selection score corresponding to the label selection information according to the label selection matching result;
and calculating by using the position score, the chat keyword score, the label selection score and the behavior information according to a preset second algorithm to obtain the sorting score of the preset keyword.
8. The method according to any one of claims 1 to 7, wherein pushing information according to the ranking score comprises:
pushing information corresponding to the target keyword to the user; the target keywords are preset keywords corresponding to the sorting scores meeting preset conditions.
9. An apparatus for information push, comprising a processor and a memory storing program instructions, characterized in that the processor is configured to execute the method for information push according to any one of claims 1 to 8 when executing the program instructions.
10. An arrangement, characterized in that it comprises the means for information push of claim 9.
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