CN111104583B - Live broadcast room recommendation method, storage medium, electronic equipment and system - Google Patents
Live broadcast room recommendation method, storage medium, electronic equipment and system Download PDFInfo
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Abstract
The invention discloses a live broadcasting room recommending method, a storage medium, electronic equipment and a system, and relates to the field of Internet live broadcasting. And inputting the text information into a distributed search engine for word segmentation to obtain a plurality of phrases and weights of the corresponding phrases. And establishing an inverted index for the live broadcasting room ID and the phrase corresponding to the live broadcasting room ID and storing the inverted index into a database. The search content is monitored in real time, input sentences are obtained, the input sentences are split to obtain search words, and the search words are stored in the kafka message queue. And acquiring the search words from the kafka queue by using a real-time stream processing framework storm, searching an inverted sequence index in a database, sequencing the live broadcasting rooms according to the weight of the search words in the inverted sequence index, and recommending a preset number of live broadcasting rooms with optimal sequencing. The method and the system can recommend the live broadcast room which is interested by the current client to the client according to the real-time search content of the user.
Description
Technical Field
The invention relates to the field of internet live broadcasting, in particular to a live broadcasting room recommendation method, a storage medium, electronic equipment and a system.
Background
Live broadcasting is a broadcasting mode for simultaneously producing and broadcasting television programs on site along with the occurrence and development processes of time, and attracts more and more attention. The live broadcast platform is used as an aggregation platform with a plurality of live broadcast rooms, and besides a live broadcast room with a plurality of man-air flame explosions, a plurality of new man and live broadcast rooms with man-air needs to be lifted. In order to promote the number of viewers in the live broadcast rooms which are required to be promoted by the new people and the popularity of the new people and assist the users to find favorite live broadcast rooms, the live broadcast platform generally recommends the users.
However, in the recommendation process of live rooms, it is common practice to calculate and infer favorite live rooms of the user based on offline behavior data (historical behavior data cached in a platform) of the user, and then recommend the live rooms to the user. Such offline behavior data typically includes past behavior of the user, such as attention, viewing, gift, bullet screen, etc., i.e., aggregate statistics based on all of the user's previous behaviors. The common recommendation scheme can effectively calculate the historical interest of each user by using a big data technology and conduct personalized recommendation of thousands of people and thousands of faces.
However, this recommended method has obvious drawbacks: the first recommended live room is calculated based on the user's historic (today's past) behavior, and cannot reflect the user's real-time interests. For example, after a user pays attention to a new anchor or has new ideas and interests, the user needs to receive recommendations about the new anchor or new ideas and interests, and the recommendation system of the live platform recommends the user based on the historical interests of the user, so that the user feels difficult to find a currently favorite live broadcast room in the platform.
Second, since the live room is real-time, many users watch according to the current popular elements, such as from one popular game to another, the users watch along with the popularity, and the user behavior only contains historical data, which is a popular live room without current popular information, and is difficult to recommend to the users, so that the users feel that the platform cannot provide the most popular live content; again, the account number for login and not the same person being used: it may be another potential user that attempts to use, but the live platform recommends based on historical information of the account, so that the potential user believes that the live platform can recommend to a single-aspect interest, resulting in the loss of the potential user from the live platform. Finally, the live platform has a large number of users, and storing the historical data of each user occupies a large amount of storage space.
Therefore, there is a need for a live room recommendation method that overcomes the above drawbacks.
Disclosure of Invention
Aiming at the defects in the prior art, the invention aims to provide a live broadcast room recommending method, a storage medium, electronic equipment and a system, which can recommend live broadcast rooms which are interested by current clients to the clients according to real-time search content of the users.
To achieve the above object, in a first aspect, an embodiment of the present invention provides a live broadcast room recommendation method, configured to recommend, to a user, a live broadcast room currently interested by the user in real time, the method including:
acquiring text information of each live broadcasting room;
inputting the text information into a distributed search engine for word segmentation to obtain a plurality of phrases and weights of the corresponding phrases;
establishing an inverted index for the live broadcasting room ID and the phrase corresponding to the live broadcasting room ID and storing the inverted index into a database;
monitoring search content in real time and acquiring an input sentence, splitting the input sentence to obtain a search word, and storing the search word into a kafka message queue;
and acquiring the search words from the kafka queue by using a real-time stream processing framework storm, searching an inverted sequence index in a database, sequencing the live broadcasting rooms according to the weight of the search words in the inverted sequence index, and recommending a preset number of live broadcasting rooms with optimal sequencing.
As a preferred embodiment, the inputting the text information into the distributed search engine for word segmentation to obtain a plurality of phrases and weights of the corresponding phrases includes:
differentiating the text information into a plurality of language elements and a phrase formed by combining the language elements;
and scoring the language elements and the phrases combined by the language elements through a distributed search engine to obtain weights of the corresponding language elements and the phrases combined by the language elements, wherein the weights are scores of the relevancy of the language elements or the phrases corresponding to the word information in the live broadcasting room.
As a preferred embodiment, the real-time detection of search behavior and the acquisition of input sentences specifically comprises: and storing the sentences input each time in order, and acquiring the latest input sentences for a plurality of times.
As a preferred embodiment, the index word storage structure is a dissolved set structure of a Redis database, and a double type score of the dissolved set structure is used for storing a search time stamp.
As a preferred embodiment, the text information includes a live room title, a live room ID, a anchor ID, an anchor nickname.
As a preferred embodiment, the text information is split using an elastic search word segmentation tool, and the inverted index is stored in an elastic search cluster.
As a preferred implementation scheme, according to the historical behavior characteristics of the user, a plurality of historical behavior recommendation live rooms are selected, and the historical behavior recommendation live rooms and the live rooms with the optimal recommendation sequence and the preset number are transmitted to the client together.
In a second aspect, an embodiment of the present invention further provides a live room recommendation system, including:
the splitting module is used for acquiring the text information of all live broadcasting rooms, splitting the text information from complex to simple according to the text information composition, and establishing an inverted sequence index step by step according to the complexity and storing the inverted sequence index into a database;
the search module is used for detecting search behaviors of a user in real time, acquiring input sentences of the user, splitting the input sentences of the user to obtain search words, and storing the search words into the kafka message queue;
and the recommending module is used for acquiring the search words from the kafka queue by using a real-time stream processing framework storm, searching the reverse ordering index in the database, ordering the searched live broadcasting rooms according to the number of the search words from more to less, and recommending the preset number of the live broadcasting rooms with the forefront ordering.
In a third aspect, embodiments of the present invention further provide a storage medium having stored thereon a computer program which, when executed by a processor, implements the method in the embodiments of the first aspect.
In a fourth aspect, an embodiment of the present invention further provides an electronic device, including a memory and a processor, where the memory stores a computer program running on the processor, and the processor implements the method in the embodiment of the first aspect when executing the computer program.
Compared with the prior art, the invention has the advantages that:
(1) According to the live broadcasting room recommendation method, the storage medium, the electronic equipment and the system, the latest search words are searched for, the left data of the historical behaviors of the user are not considered any more, the recommendation can be carried out according to the real-time interest and hobbies used for the user, and the live broadcasting room recommended to the user can be ensured to be more fit with the current needs of the user; and meanwhile, word segmentation is carried out on the text information of the live broadcasting room, and the word is stored in an inverted index mode, so that the live broadcasting room can be found more quickly and definitely when the live broadcasting room is searched according to the search words. In addition, since the real-time searching behavior of the user is aimed at, the user is required to be fast, stable and not crashed, the user experience can be well ensured by using the kafka queue and the real-time stream processing framework storm.
(2) According to the live broadcasting room recommendation method, the storage medium, the electronic equipment and the system, word segmentation is carried out according to the word elements during word segmentation, and the word information of the live broadcasting room can be better split, so that the live broadcasting room which is more suitable for the requirements of users can be found during retrieval in the inverted index.
(3) According to the live broadcasting room recommendation method, the storage medium, the electronic equipment and the system, sentences input by a user each time are stored one by one according to times, meanwhile, the latest input sentences are acquired, sampling according to the latest interest and preference of the user is guaranteed, meanwhile, the live broadcasting room recommendation method is stored through the redis database, the set sorted structure is double type score, search time stamps can be stored better, the platform is guaranteed to cope with a large number of clients, and the live broadcasting room of current interest is recommended in real time.
(4) According to the live broadcasting room recommendation method, the storage medium, the electronic equipment and the system, which are disclosed by the invention, the live broadcasting room title, the live broadcasting room ID, the anchor nickname and the like of each live broadcasting room are taken as the text information to be split, so that the word group which can be searched in the inverted index is ensured to be necessary and sufficient, and the probability of recommending and attaching to the live broadcasting room experienced by a user is improved.
(5) According to the live broadcasting room recommendation method, the storage medium, the electronic equipment and the system, the electronic Search word segmentation tool is used for splitting the text information, the word segmentation tool can be used for directly distributing weights to the text information while splitting the text information, so that the subsequent recommendation is more convenient for a platform, meanwhile, the electronic Search cluster is arranged to store the inverted index, and the requirements of establishing the inverted index and storing after word segmentation are met, so that the recommendation is smoother, and the user experience is improved.
(6) According to the live broadcasting room recommendation method, the storage medium, the electronic equipment and the system, the live broadcasting room which is obtained by deduction according to the real-time retrieval behaviors of the user is recommended to the user, and the live broadcasting room which is recommended according to other data, such as historical behavior data, is recommended to the user. Because the interests of the user are not suddenly and completely changed, the interests of the user on the other hand can be temporarily increased, but the old interests still exist, and the live broadcast room inferred by completely recommending the real-time retrieval behaviors of the user can still cause discomfort to the user, so that the user experience can be better improved by reasonably integrating the recommendation of the live broadcast rooms of the two recommendation types to the user.
Drawings
For a clearer description of the technical solutions of the embodiments of the present invention, the following description will be given for a brief description of the drawings corresponding to the embodiments, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flowchart showing steps of a recommendation method for a live broadcast room according to the present invention;
fig. 2 is a schematic structural diagram of a recommendation system in a live broadcasting room according to the present invention.
In the figure: 1-split module, 2-search module, 3-recommendation module.
Detailed Description
Embodiments of the present invention are described in further detail below with reference to the accompanying drawings.
Referring to fig. 1, an embodiment of the present invention provides a live broadcast room recommendation method, a storage medium, an electronic device, and a system, which are capable of recommending live broadcast rooms to users in real time according to the current interests of the users by establishing an inverted index for each live broadcast room, splitting a phrase according to the location information of each live broadcast room, and searching in the inverted index in real time according to the input sentences of the searches of the users on a platform.
In order to achieve the technical effects, the general idea of the application is as follows:
the embodiment of the invention provides a live broadcast room recommendation method, which is used for recommending a live broadcast room of current interest of a user to the user in real time and comprises the following steps:
acquiring text information of each live broadcasting room;
inputting the text information into a distributed search engine for word segmentation to obtain a plurality of phrases and weights of the corresponding phrases;
establishing an inverted index for the live broadcasting room ID and the phrase corresponding to the live broadcasting room ID and storing the inverted index into a database;
monitoring search content in real time and acquiring an input sentence, splitting the input sentence to obtain a search word, and storing the search word into a kafka message queue;
and acquiring the search words from the kafka queue by using a real-time stream processing framework storm, searching an inverted sequence index in a database, sequencing the live broadcasting rooms according to the weight of the search words in the inverted sequence index, and recommending a preset number of live broadcasting rooms with optimal sequencing.
In summary, for the platform, it needs to better arouse the interests of the user, and attract the user to watch the live broadcast. Thus, when making recommendations to users, historical behavior data for each user is typically recorded and then inferred from the user's historical behavior. However, the recommendation is not performed according to the current interests of the user, and after the user generates new interests, the platform can only recommend the live broadcasting room recommended according to the historical behavior data to the client when searching, and the recommendation effect is greatly reduced because the live broadcasting room does not meet the requirements of the user.
The invention monitors the search content of the user in real time, acquires the sentences input by the user for searching, and ensures that the current interest information of the user can be acquired in real time.
In order to analyze the interest information of the user, input sentences of the user are obtained, wherein the input sentences are visual representations of the interest of the user, and are the information which can be obtained most directly by the live broadcast platform.
Further, in order to be able to reasonably retrieve the input sentences of the user, a set of retrieval databases is required. It is therefore first necessary to create from live room information on the platform.
The word sentence and the live broadcasting room ID which are obtained by splitting the text information of the live broadcasting room are used for establishing the inverted index, and when the index is searched, the search after the user input sentence is split can be carried out according to the index, so that the relevance is good, and the synchronous rate is higher: the inverted index is derived from the fact that it is necessary to find records according to the values of the attributes. Each entry in such an index table includes an attribute value and the address of each record having the attribute value. The position of a record is determined not by the record but by the attribute value, and is thus referred to as an inverted index.
Furthermore, the invention uses the kafka queue to store the search words, and uses the real-time stream processing framework storm to acquire the search words from the kafka queue, thereby meeting the requirements of the live platform on big data, massive users and real-time processing: because of the real-time requirement of the live platform, the live platform needs to record and analyze the current behavior of the user, namely almost every time, needs to analyze and recommend the current interest of the user in real time, and brings more strict requirements to the performance and architecture of the platform: for a large number of users and a large amount of data, the data can be transmitted and analyzed in real time.
Whereas Kafka is a high throughput distributed publish-subscribe messaging system that can handle all action stream data in consumer-scale websites, has high throughput, supports cluster differentiation, etc., and can meet the requirements for retrieval word storage and processing.
The real-time stream processing framework storm is a distributed real-time computing system capable of trustingly processing large amounts of stream data. The method can perform corresponding calculation in real time, is stable and does not collapse, and ensures that mass users facing live broadcast peak periods can still be processed without blocking.
In order to better understand the above technical solution, the following detailed description is provided in connection with specific embodiments.
Example 1
The embodiment of the invention provides a live broadcasting room recommendation method, which comprises the following steps:
s1: and acquiring the text information of each live broadcasting room.
The invention uses input sentences which are related to characters and are used for searching by users. Therefore, the database/index of each live broadcasting room on the live broadcasting platform is established corresponding to the text related information, and the text information of each live broadcasting room is required.
As a preferred embodiment, the text information includes, but is not limited to: inter-cast title, live room ID, anchor nickname. The title, ID, anchor ID and nickname of the live broadcasting room can reflect the content of the live broadcasting room in a wider range, so that the database/index established by the characters can reflect the attribute of the live broadcasting room more objectively and reasonably, and the subsequent retrieval and judgment are convenient.
S2: and inputting the text information into a distributed search engine for word segmentation to obtain a plurality of phrases and weights of the corresponding phrases.
After the text information in the live broadcasting room is obtained, if the text information is only associated with the live broadcasting room, the input sentence searched by the user cannot be completely matched with the text information, so that the text information needs to be processed to form a plurality of phrases. Thus, the phrase can be completely or incompletely matched during searching.
Meanwhile, if the input sentences are matched with a plurality of live broadcasting rooms, the platform needs to judge which one is more fit with the interests of the user, so that the phrases need to be scored, the weights of the phrases are obtained, and the phrases can be more easily compared under different weights, so that the fit live broadcasting rooms are recommended for the user.
It should be noted that, the weights obtained in the splitting in the step S2 are obtained by calculating the relevance of the words with respect to the corresponding text information according to a preset calculation formula, and the preset calculation formula is a common technical means for those skilled in the art during searching and retrieving, and will not be described in detail herein.
As a preferred embodiment, the inputting the text information into the distributed search engine for word segmentation to obtain a plurality of phrases and weights of the corresponding phrases includes:
differentiating the text information into a plurality of language elements and a phrase formed by combining the language elements;
and scoring the language elements and the phrases combined by the language elements through a distributed search engine to obtain weights of the corresponding language elements and the phrases combined by the language elements, wherein the weights are scores of the relevancy of the language elements or the phrases corresponding to the word information in the live broadcasting room.
Further, the text information is split by using an elastiscearch word segmentation tool, and elastiscearch is a Lucene-based search server. It provides a distributed multi-user capable full text search engine based on RESTful web interface. The elastomer search was developed in Java and released as open source under Apache license terms, is a currently popular enterprise-class search engine. The cloud computing system is designed to be used in cloud computing, can achieve real-time searching, is stable, reliable and quick, and is convenient to install and use.
For example, the literal information of the live room ID96291 is: the live broadcasting room is titled as 'the sound artist of the northeast quail', and the main broadcasting nick is called 'the northeast quail'. Inputting the text information into an elastic search word segmentation tool to obtain a phrase and corresponding weight (the weight is a numerical value in brackets): 96291 (1.0), northeast quail (0.95), sound artist (0.5), northeast (0.4), quail (0.3), sound (0.2), artist (0.1). Also, a direct broadcasting room ID is 96200, and the direct broadcasting room title is "northeast phase sound", and inputting this direct broadcasting room text information into the elastic search word segmentation tool will obtain a phrase and a weight (the weight is a value in brackets): 96200 (1.0), northeast (0.95), northeast (0.6), and phase (0.4).
S3: and establishing an inverted index for the live broadcasting room ID and the phrase corresponding to the live broadcasting room ID and storing the inverted index into a database.
The inverted index is derived from the fact that it is necessary to find records according to the values of the attributes. Each entry in such an index table includes an attribute value and the address of each record having the attribute value. The position of a record is determined not by the record but by the attribute value, and is thus referred to as an inverted index. During retrieval, the corresponding live broadcasting room can be retrieved directly according to the retrieval words obtained by splitting the input sentences, and the method is more efficient and quick.
Further, the inverted index is stored into an elastic search cluster.
Each field of the Elastic Search is indexed so that it can be retrieved, while each tile may have zero or more copies of the word in the inverted index as a tile. Each data node in a cluster may carry one or more slices and coordinate and process various operations. This ensures that load rebalancing and routing is done automatically in most cases when large volumes of data are processed. Second, the Elastic Search cluster can be extended to hundreds of servers, handling PB-level structured or unstructured data. And finally supporting a plug-in mechanism, a word segmentation plug-in, a synchronous plug-in, a Hadoop plug-in, a visual plug-in and the like.
S4: monitoring search content in real time and acquiring an input sentence, splitting the input sentence to obtain a search word, and storing the search word into a kafka message queue;
when a user owns a new interest and wants to watch a live broadcast room about the new interest, the user generally searches through a search function of the platform, so that the platform monitors search contents in real time and acquires input sentences corresponding to the search behavior. In this way, the input sentence can be captured entirely by the platform as a direct reaction of the user's current interests.
The live broadcast platform needs to meet the watching requirements of a large number of users, and the live broadcast platform carries out real-time recommendation according to the current interests of the users, and needs a large amount of data, real-time processing and stability of data processing. The invention uses the kafka queue to ensure quick access of the search words, uses the storm real-time stream processing framework to perform real-time and stable search, and ensures the data processing requirements of a large number of users in real-time processing of the platform.
Further, the real-time detection of the search behavior and the acquisition of the input sentence specifically includes: and storing the sentences input each time in order, and acquiring the latest input sentences for a plurality of times. The input sentences of the user in the current interest searching process are related to time, so that the sentences input each time are stored in sequence, and the latest input sentences for a plurality of times are acquired, so that the current user interest can be better captured.
Specifically, the index word storage structure is a dissolved set structure of the Redis database, and the double type score of the dissolved set structure is used for storing the search time stamp. The redis database is used for storing, the set sorted structure is double type score, so that the search time stamp can be stored better, the platform is ensured to be capable of coping with a large number of clients, and the current interested live broadcasting room is recommended for the clients in real time.
S5: and acquiring the search words from the kafka queue by using a real-time stream processing framework storm, searching an inverted sequence index in a database, sequencing the live broadcasting rooms according to the weight of the search words in the inverted sequence index, and recommending a preset number of live broadcasting rooms with optimal sequencing.
In order to obtain a live broadcasting room recommended by the current user, further searching in the inverted index is needed, so that a relevant live broadcasting room is obtained, after a plurality of live broadcasting rooms are obtained, the weight of the phrases is obtained according to the word disassembly information correspondingly obtained by the searching words, the phrases are ordered, and the preset number of live broadcasting rooms with the optimal ordering are recommended to the user.
It should be noted that, the ranking is the living broadcast room with larger weight after being ranked according to the weight, whether from big to small or from small to big. When the live broadcasting room which is most fit with the current interests is recommended to the user in real time, the matching degree of the live broadcasting room recommended to the user and the interests of the user can be improved by using the live broadcasting room with larger weight.
For example, the live broadcasting room with corresponding ID96291, its word group and corresponding weight (weight is the value in brackets) are: phrase and corresponding weight (weights in brackets): 96291 (1.0), northeast quail (0.95), audio artist (0.5), northeast (0.4), quail (0.3), audio (0.2), artist (0.1); and a live broadcast room with ID 96200, wherein word groups and corresponding weights are as follows: 96200 (1.0), northeast (0.95), northeast (0.6), and phase (0.4).
When searching for "northeast phase sound", the northeast phase sound (0.95) of the live broadcast room with the ID of 96200 is directly retrieved. While searching for "northeast", a live broadcast room with ID96291 and a live broadcast room with ID 96200 are retrieved, wherein northeast (0.4) and northeast (0.6) have better ordering than the live broadcast room with ID96291 due to the weight of 0.6 being greater than 0.4.
As an alternative embodiment, the part of the recommended fields on the user interface display the optimally ordered preset number of live rooms.
The live broadcasting room recommended to the user on the user interface is only recommended according to the input sentences searched by the user in real time, and other recommendation columns can display other recommended live broadcasting rooms, such as: and selecting a plurality of historical behavior recommendation live rooms according to the historical behavior characteristics of the user, and then sending the historical behavior recommendation live rooms and the live rooms with the preset number with the optimal recommendation sequence to the client.
In addition to recommending a live broadcast room which is inferred according to the user real-time retrieval behavior to the user, the live broadcast room which is recommended according to the user history behavior is recommended to the user, because the interest of the user is not suddenly and completely converted, the interest of the user on the other hand is possibly temporarily increased, but the old interest still exists, and the live broadcast room which is inferred by completely recommending the user real-time retrieval behavior can still cause discomfort to the user, so that the recommendation to the user by reasonably integrating the live broadcast rooms of the two recommendation types can better promote the user experience.
Based on the same inventive concept, the present application provides a second embodiment, and the specific implementation manner thereof is as follows.
Example two
As shown in fig. 2, an embodiment of the present invention provides a live broadcast room recommendation method system, which is characterized in that the method includes:
the splitting module (1) is used for acquiring the text information of all live broadcasting rooms, splitting the text information from complex to simple according to the text information composition, and establishing an inverted sequence index step by step according to the complexity and storing the inverted sequence index into a database;
the retrieval module (2) is used for detecting the search behavior of the user in real time, acquiring the input sentences of the user, splitting the input sentences of the user to obtain retrieval words, and storing the retrieval words into the kafka message queue;
and the recommending module (3) is used for acquiring the search words from the kafka queue by using a real-time stream processing framework storm, searching the reverse ordering indexes in the database, ordering the searched live broadcasting rooms according to the number of the search words from more to less, and recommending the preset number of the live broadcasting rooms with the forefront ordering.
The various modifications and specific examples of the foregoing method embodiments are equally applicable to the system of this embodiment, and those skilled in the art will be aware of the implementation methods and benefits of the system of this embodiment through the foregoing detailed description of the method, so they will not be described in detail herein for brevity.
Based on the same inventive concept, the present application provides embodiment three.
Example III
A third embodiment of the present invention provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements a live room recommendation method as provided by any embodiment of the present invention, the method comprising:
acquiring text information of each live broadcasting room;
inputting the text information into a distributed search engine for word segmentation to obtain a plurality of phrases and weights of the corresponding phrases;
establishing an inverted index for the live broadcasting room ID and the phrase corresponding to the live broadcasting room ID and storing the inverted index into a database;
monitoring search content in real time and acquiring an input sentence, splitting the input sentence to obtain a search word, and storing the search word into a kafka message queue;
and acquiring the search words from the kafka queue by using a real-time stream processing framework storm, searching an inverted sequence index in a database, sequencing the live broadcasting rooms according to the weight of the search words in the inverted sequence index, and recommending a preset number of live broadcasting rooms with optimal sequencing.
The computer storage media of embodiments of the invention may take the form of any combination of one or more computer-readable media. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. The computer readable storage medium may be, for example, but not limited to: an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples (a non-exhaustive list) of the computer-readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
The computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, either in baseband or as part of a carrier wave. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination of the foregoing. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.
Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, fiber optic cable, RF, etc., or any suitable combination of the foregoing.
Computer program code for carrying out operations of the present invention may be written in one or more programming languages, including an object oriented programming language such as Java, smalltalk, C ++ and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computer (for example, through the Internet using an Internet service provider).
Note that the above is only a preferred embodiment of the present invention and the technical principle applied. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, while the invention has been described in connection with the above embodiments, the invention is not limited to the embodiments, but may be embodied in many other equivalent forms without departing from the spirit or scope of the invention, which is set forth in the following claims.
Based on the same inventive concept, the present application provides an embodiment four.
Example IV
The fourth embodiment of the present invention also provides an electronic device, including a memory and a processor, where the memory stores a computer program running on the processor, and where the processor implements all or part of the method steps in the first embodiment when executing the computer program.
The processor may be a central processing unit (Central Processing Unit, CPU), other general purpose processors, digital signal processors (Digital Signal Processor, DSP), application specific integrated circuits (Application Specific Integrated Circuit, ASIC), off-the-shelf programmable gate arrays (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like that is a control center of the computer device, connecting various parts of the overall computer device using various interfaces and lines.
The memory may be used to store the computer program and/or modules, and the processor may implement various functions of the computer device by running or executing the computer program and/or modules stored in the memory, and invoking data stored in the memory. The memory may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program (such as a sound playing function, an image playing function, etc.) required for at least one function, and the like; the storage data area may store data (such as audio data, video data, etc.) created according to the use of the cellular phone, etc. In addition, the memory may include high-speed random access memory, and may also include non-volatile memory, such as a hard disk, memory, plug-in hard disk, smart Media Card (SMC), secure Digital (SD) Card, flash Card (Flash Card), at least one disk storage device, flash memory device, or other volatile solid-state storage device.
In general, according to the live broadcasting room recommendation method, the storage medium, the electronic equipment and the system provided by the embodiment of the invention, the current interests of the user are captured by acquiring the input words searched by the user in real time, and the inverted index of each live broadcasting room is established for searching, so that the live broadcasting room which is attached with the current interests is recommended to the user.
It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, magnetic disk storage, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
It will be apparent to those skilled in the art that various modifications and variations can be made to the present invention without departing from the spirit or scope of the invention. Thus, it is intended that the present invention also include such modifications and alterations insofar as they come within the scope of the appended claims or the equivalents thereof.
Claims (5)
1. A live broadcast room recommendation method for recommending a live broadcast room of current interest to a user in real time, comprising:
acquiring text information of each live broadcasting room; the text information comprises a live broadcasting room title, a live broadcasting room ID, a host broadcasting ID and a host broadcasting nickname;
inputting the text information into a distributed search engine for word segmentation to obtain a plurality of phrases and weights of the corresponding phrases; splitting the text information by using an elastic search word segmentation tool;
establishing an inverted index for the live broadcasting room ID and the phrase corresponding to the live broadcasting room ID and storing the inverted index into a database;
monitoring search content in real time and acquiring an input sentence, splitting the input sentence to obtain a search word, and storing the search word into a kafka message queue;
acquiring the search words from the kafka queue by using a real-time stream processing framework storm, searching an inverted sequence index in a database, sequencing live broadcasting rooms according to the weight of the search words in the inverted sequence index, and recommending a preset number of live broadcasting rooms with optimal sequencing; the index word storage structure is a dissolved set structure of a Redis database, and double type scores of the dissolved set structure are used for storing search time stamps;
inputting the text information into a distributed search engine for word segmentation, and obtaining a plurality of phrases and weights of the corresponding phrases comprises the following steps:
differentiating the text information into a plurality of language elements and a phrase formed by combining the language elements;
scoring the language elements and the phrases combined by the language elements through a distributed search engine to obtain weights of the corresponding language elements and the phrases combined by the language elements, wherein the weights are scores of the relevancy of the language elements or the phrases corresponding to the word information in the live broadcasting room;
the real-time monitoring of search content and the acquisition of input sentences are specifically as follows: and storing the sentences input each time in order, and acquiring the latest input sentences for a plurality of times.
2. The method of claim 1, wherein: and displaying the optimally ordered preset number of live rooms in a part of recommendation fields on the user interface.
3. A storage medium having a computer program stored thereon, characterized by: the computer program implementing the method of claim 1 or 2 when executed by a processor.
4. An electronic device comprising a memory and a processor, the memory having stored thereon a computer program that runs on the processor, characterized in that: the processor, when executing the computer program, implements the method of claim 1 or 2.
5. A live room recommendation system for making live room recommendations using the live room recommendation method of claim 1, comprising:
the splitting module is used for acquiring the text information of all live broadcasting rooms, splitting the text information from complex to simple according to the text information composition, and establishing an inverted sequence index step by step according to the complexity and storing the inverted sequence index into a database;
the search module is used for detecting search behaviors of a user in real time, acquiring input sentences of the user, splitting the input sentences of the user to obtain search words, and storing the search words into the kafka message queue;
and the recommending module is used for acquiring the search words from the kafka queue by using a real-time stream processing framework storm, searching the reverse ordering index in the database, ordering the searched live broadcasting rooms according to the number of the search words from more to less, and recommending the preset number of the live broadcasting rooms with the forefront ordering.
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| CN111954017B (en) * | 2020-08-14 | 2022-03-25 | 北京达佳互联信息技术有限公司 | Live broadcast room searching method and device, server and storage medium |
| CN112579899A (en) * | 2020-12-21 | 2021-03-30 | 杭州米络星科技(集团)有限公司 | Searching method and device for anchor |
| CN113329233B (en) * | 2021-04-30 | 2022-09-09 | 北京达佳互联信息技术有限公司 | Live broadcast data processing method and device, electronic equipment and storage medium |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102968465A (en) * | 2012-11-09 | 2013-03-13 | 同济大学 | Network information service platform and search service method based on network information service platform |
| CN102982153A (en) * | 2012-11-29 | 2013-03-20 | 北京亿赞普网络技术有限公司 | Information retrieval method and device |
| CN103198079A (en) * | 2012-01-06 | 2013-07-10 | 北大方正集团有限公司 | Related search implementation method and device |
| CN104317945A (en) * | 2014-10-31 | 2015-01-28 | 亚信科技（南京）有限公司 | E-commerce website commodity recommending method on basis of search behaviors |
| CN104978314A (en) * | 2014-04-01 | 2015-10-14 | 深圳市腾讯计算机系统有限公司 | Media content recommendation method and device |
| CN106557483A (en) * | 2015-09-25 | 2017-04-05 | 阿里巴巴集团控股有限公司 | A kind of data processing, data query method and apparatus |
| CN108256044A (en) * | 2018-01-12 | 2018-07-06 | 武汉斗鱼网络科技有限公司 | Direct broadcasting room recommends method, apparatus and electronic equipment |
-
2018
- 2018-10-10 CN CN201811178341.2A patent/CN111104583B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103198079A (en) * | 2012-01-06 | 2013-07-10 | 北大方正集团有限公司 | Related search implementation method and device |
| CN102968465A (en) * | 2012-11-09 | 2013-03-13 | 同济大学 | Network information service platform and search service method based on network information service platform |
| CN102982153A (en) * | 2012-11-29 | 2013-03-20 | 北京亿赞普网络技术有限公司 | Information retrieval method and device |
| CN104978314A (en) * | 2014-04-01 | 2015-10-14 | 深圳市腾讯计算机系统有限公司 | Media content recommendation method and device |
| CN104317945A (en) * | 2014-10-31 | 2015-01-28 | 亚信科技（南京）有限公司 | E-commerce website commodity recommending method on basis of search behaviors |
| CN106557483A (en) * | 2015-09-25 | 2017-04-05 | 阿里巴巴集团控股有限公司 | A kind of data processing, data query method and apparatus |
| CN108256044A (en) * | 2018-01-12 | 2018-07-06 | 武汉斗鱼网络科技有限公司 | Direct broadcasting room recommends method, apparatus and electronic equipment |
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