CN108132966A - Knowledge mapping generation method and device - Google Patents
Knowledge mapping generation method and device Download PDFInfo
- Publication number
- CN108132966A CN108132966A CN201711217693.XA CN201711217693A CN108132966A CN 108132966 A CN108132966 A CN 108132966A CN 201711217693 A CN201711217693 A CN 201711217693A CN 108132966 A CN108132966 A CN 108132966A
- Authority
- CN
- China
- Prior art keywords
- keyword
- word
- basic word
- association
- knowledge mapping
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/95—Retrieval from the web
- G06F16/953—Querying, e.g. by the use of web search engines
- G06F16/9535—Search customisation based on user profiles and personalisation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/21—Design, administration or maintenance of databases
- G06F16/215—Improving data quality; Data cleansing, e.g. de-duplication, removing invalid entries or correcting typographical errors
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/22—Indexing; Data structures therefor; Storage structures
- G06F16/221—Column-oriented storage; Management thereof
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/24—Querying
- G06F16/245—Query processing
- G06F16/2458—Special types of queries, e.g. statistical queries, fuzzy queries or distributed queries
- G06F16/2465—Query processing support for facilitating data mining operations in structured databases
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/27—Replication, distribution or synchronisation of data between databases or within a distributed database system; Distributed database system architectures therefor
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/28—Databases characterised by their database models, e.g. relational or object models
- G06F16/284—Relational databases
- G06F16/288—Entity relationship models
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
- G06F16/36—Creation of semantic tools, e.g. ontology or thesauri
- G06F16/374—Thesaurus
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/95—Retrieval from the web
- G06F16/951—Indexing; Web crawling techniques
Landscapes
- Engineering & Computer Science (AREA)
- Databases & Information Systems (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Data Mining & Analysis (AREA)
- Computational Linguistics (AREA)
- Software Systems (AREA)
- Quality & Reliability (AREA)
- Computing Systems (AREA)
- Fuzzy Systems (AREA)
- Mathematical Physics (AREA)
- Probability & Statistics with Applications (AREA)
- Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
Abstract
The invention discloses a kind of knowledge mapping generation method and devices.Wherein, this method includes：Basic word is captured in predetermined content platform；The keyword with basic word association is obtained on predetermined content platform；According to the frequency that basic word and keyword occur simultaneously, the degree of association between basis word and keyword is determined；Knowledge mapping is generated according to the determining degree of association, wherein, knowledge mapping includes multiple basic words and the keyword with multiple basic word associations, and knowledge mapping feeds back for the search of content information.By the present invention, solve in the related art, when being scanned for the content information of needs, the technical issues of existence time is long, and efficiency is low.
Description
Technical field
The present invention relates to data processing field, in particular to a kind of knowledge mapping generation method and device.
Background technology
With the continuous development of information technology, internet information is intricate.People are when carrying out information search, Zhi Nengjian
Frame retrieval singly is entered search terms into, system provides content relevant with the search term according to the search term of input and believes later
Breath.But many times, people are not aware that the Accurate Expression of the content oneself to be searched for, only know that some are general interior
Hold, and at this time, if it is desired to when getting the content information to be searched for, then can only user input possible search term one by one,
And possible search result is shown one by one.And when using such operation, when often having searched for repeatedly or having searched for very long
Between also search for less than really desired content information.Therefore, in the related art, when being scanned for the content information of needs,
The problem of existence time is long, and efficiency is low.
For it is above-mentioned the problem of, currently no effective solution has been proposed.
Invention content
An embodiment of the present invention provides a kind of knowledge mapping generation method and device, at least to solve in the related art,
When being scanned for the content information of needs, the technical issues of existence time is long, and efficiency is low.
One side according to embodiments of the present invention provides a kind of knowledge mapping generation method, including：In predetermined content
The basic word of platform crawl；The keyword with the basic word association is obtained on the predetermined content platform；According to the basis
The frequency that word occurs simultaneously with the keyword determines the degree of association between the basic word and the keyword；According to determining
The degree of association generation knowledge mapping, wherein, the knowledge mapping include it is multiple it is described basis words and with the multiple base
The keyword of plinth word association, the knowledge mapping feed back for the search of content information.
Optionally, it obtains on the predetermined content platform and includes with the keyword of the basic word association：It determines
With the correlation dimension of the keyword and the basic word of the basic word association；On the predetermined content platform obtain with it is described
All keywords of the basic word in the correlation dimension.
Optionally, the knowledge mapping is generated according to the determining degree of association to include：The basic word is obtained described
The frequency that the frequency and the keyword that predetermined content platform occurs occur in the predetermined content platform；According to the base
Plinth word determines the temperature of the basic word and according to the keyword described in the frequency that the predetermined content platform occurs
The frequency that predetermined content platform occurs determines the temperature of the keyword；The knowledge graph is generated according to the determining degree of association
Spectrum, wherein, include the degree of association of the basic word and the keyword in the knowledge mapping, the temperature of the basis word,
The temperature of the keyword.
Optionally, it after the knowledge mapping is generated according to the determining degree of association, further includes：Receive input
Search operation and/or clicking operation；According to the operation of the described search of reception and/or clicking operation, to the knowledge graph of generation
Spectrum is modified.
Optionally, it after the knowledge mapping is generated according to the determining degree of association, further includes：Receive input
For the search term of search；Judge in the knowledge mapping to whether there is and the matched basic word of described search word；Sentencing
Disconnected result in the case of being, obtain the basic word content information and in the keyword of the basic word association
Hold information；Show the basic content information of word and the content information of the keyword.
Optionally, show that the basic content information of word and the content information of the keyword include：With it is matched
The keyword of the basis word association is ranked up multiple keywords according to the size of the degree of association and obtains there are in the case of multiple
Obtain ranking results；While the basic word is shown, the content information of the keyword is shown according to ranking results.
Optionally, the basic content information of word and/or the content information of the keyword include：Domestic News,
Trend of investment, action message, industry patent, service information, technical documentation, industry Zone Information.
According to another aspect of the present invention, a kind of knowledge mapping generating means are provided, including：Handling module, for
The basic word of predetermined content platform crawl；First acquisition module, for being obtained on the predetermined content platform and the basic word
Associated keyword；Determining module for the frequency occurred simultaneously with the keyword according to the basic word, determines the base
The degree of association between plinth word and the keyword；Generation module, for generating knowledge mapping according to the determining degree of association,
In, the knowledge mapping includes multiple basic words and the keyword with the multiple basic word association, the knowledge graph
Spectrum is fed back for the search of content information.
Optionally, first acquisition module includes：First determination unit, for determining the pass with the basic word association
The correlation dimension of keyword and the basic word；First acquisition unit, for being obtained and the base on the predetermined content platform
All keywords of the plinth word in the correlation dimension.
Optionally, the generation module includes：Second acquisition unit, for obtaining the basic word in the predetermined content
The frequency that the frequency and the keyword that platform occurs occur in the predetermined content platform；Second determination unit, for root
According to the basic word temperature of the basic word is determined in the frequency that the predetermined content platform occurs and according to the key
Word determines the temperature of the keyword in the frequency that the predetermined content platform occurs；Generation unit, for according to determining institute
It states the degree of association and generates the knowledge mapping, wherein, the pass of the basic word and the keyword is included in the knowledge mapping
Connection degree, the temperature of the basis word, the temperature of the keyword.
Optionally, which further includes：First receiving module, for receiving the search operation of input and/or clicking behaviour
Make；Correcting module, for according to the operation of the described search of reception and/or clicking operation, being carried out to the knowledge mapping of generation
It corrects.
Optionally, which further includes：Second receiving module, for receiving the search term for search of input；Sentence
Disconnected module, for judging to whether there is in the knowledge mapping and the matched basic word of described search word；Second obtains mould
Block, in the case where the judgment result is yes, obtain the basic word content information and with the basic word association
The content information of keyword；Display module, for showing the basic content information of word and the content information of the keyword.
Optionally, the display module includes：Sequencing unit, in the keyword with the matched basic word association
In the case of multiple, acquisition ranking results are ranked up to size of multiple keywords according to the degree of association；Display unit is used
In while the basic word is shown, the content information of the keyword is shown according to ranking results.
In embodiments of the present invention, knowledge mapping is generated using according to the degree of association between basic word and the keyword,
And the mode for feeding back the knowledge mapping for the search of content information so that there are phases between basic word and keyword
The incidence relation answered when being scanned for basic word therein, can also readily obtain the key with the basis word association
The content information of word has achieved the purpose that show the content information that may be needed as much as possible, it is achieved thereby that search needs
Content information when, shorten duration, the technique effect of search efficiency is improved, and then solve in the related art, to needs
When content information scans for, the technical issues of existence time is long, and efficiency is low.
Description of the drawings
Attached drawing described herein is used to provide further understanding of the present invention, and forms the part of the application, this hair
Bright illustrative embodiments and their description do not constitute improper limitations of the present invention for explaining the present invention.In the accompanying drawings：
Fig. 1 is the flow chart of knowledge mapping generation method according to embodiments of the present invention；
Fig. 2 is the structure diagram of knowledge mapping generating means according to embodiments of the present invention；
Fig. 3 is the structure diagram of the first acquisition module 22 in knowledge mapping generating means according to embodiments of the present invention；
Fig. 4 is the structure diagram of generation module 28 in knowledge mapping generating means according to embodiments of the present invention；
Fig. 5 is the preferred structure block diagram one of knowledge mapping generating means according to embodiments of the present invention；
Fig. 6 is the preferred structure block diagram two of knowledge mapping generating means according to embodiments of the present invention；
Fig. 7 is the preferred structure block diagram of display module 68 in knowledge mapping generating means according to embodiments of the present invention；
Fig. 8 is showing for the database sharing of the knowledge mapping according to the preferred embodiment of the invention towards Intelligent hardware field
It is intended to；
Fig. 9 is that the user foreground of the knowledge mapping according to the preferred embodiment of the invention towards Intelligent hardware field was searched for
The schematic diagram of journey.
Specific embodiment
In order to which those skilled in the art is made to more fully understand the present invention program, below in conjunction in the embodiment of the present invention
The technical solution in the embodiment of the present invention is clearly and completely described in attached drawing, it is clear that described embodiment is only
The embodiment of a part of the invention, instead of all the embodiments.Based on the embodiments of the present invention, ordinary skill people
Member's all other embodiments obtained without making creative work should all belong to the model that the present invention protects
It encloses.
It should be noted that term " first " in description and claims of this specification and above-mentioned attached drawing, "
Two " etc. be the object for distinguishing similar, and specific sequence or precedence are described without being used for.It should be appreciated that it uses in this way
Data can be interchanged in the appropriate case, so as to the embodiment of the present invention described herein can in addition to illustrating herein or
Sequence other than those of description is implemented.In addition, term " comprising " and " having " and their any deformation, it is intended that cover
Cover it is non-exclusive include, be not necessarily limited to for example, containing the process of series of steps or unit, method, system, product or equipment
Those steps or unit clearly listed, but may include not listing clearly or for these processes, method, product
Or the intrinsic other steps of equipment or unit.
According to embodiments of the present invention, a kind of embodiment of the method for knowledge mapping generation method is provided, it should be noted that
Step shown in the flowchart of the accompanying drawings can perform in the computer system of such as a group of computer-executable instructions, and
And although showing logical order in flow charts, in some cases, can institute be performed with the sequence being different from herein
The step of showing or describing.
Fig. 1 is the flow chart of knowledge mapping generation method according to embodiments of the present invention, as shown in Figure 1, this method includes
Following steps：
Step S102 captures basic word in predetermined content platform, wherein, which can be scheduled net
Page, naturally it is also possible to be the page that some other includes content information；
Step S104 obtains the keyword with basic word association on predetermined content platform；
Step S106 according to the frequency that basic word and keyword occur simultaneously, determines the pass between basis word and keyword
Connection degree；
Step S108 generates knowledge mapping according to the determining degree of association, wherein, knowledge mapping include multiple basic words with
With the keyword of multiple basic word associations, knowledge mapping feeds back for the search of content information.
By above-mentioned steps, and, will know using according to the degree of association generation knowledge mapping between basic word and keyword
Know mode of the collection of illustrative plates for the search feedback of content information so that there are corresponding incidence relation between basic word and keyword,
When being scanned for basic word therein, the content information with the keyword of the basis word association can be also readily obtained,
Achieve the purpose that show the content information that may be needed as much as possible, it is achieved thereby that during the content information of search needs,
Shorten duration, improve the technique effect of search efficiency, and then solve in the related art, the content information of needs is searched
The technical issues of Suo Shi, existence time is long, and efficiency is low.
Optionally, when predetermined content platform captures basic word, the basic word to be captured can also be selected or
Screening, so that the knowledge mapping that will be generated is more universal or more practical.For example, according to scheduled screening conditions
(for example, for avoiding the screening conditions of uncommon word) screens basic word, by screening operation, it is possible to prevente effectively from looking for not
To keyword corresponding with basic word, the success rate of generation knowledge mapping is improved.
When obtaining the keyword with basic word association on predetermined content platform, can according to the basis word and keyword it
Between correlation dimension, to obtain all keywords with the basis word association.It should be noted that above-mentioned correlation dimension can be
For showing to be associated with rank between basic word and keyword, for example, when basic word and keyword are directly linked, it is believed that
The basis word is associated with keyword for level-one；When basic word and keyword need when being associated, to recognize by a word
With keyword it is that two level is associated with for the basis word；It, can be with when basic word and keyword are needed through two words come when being associated
Think that the basis word is associated with keyword for three-level；The rest may be inferred ....Therefore, by correlation dimension, to obtain and the basis
During all keywords of word association, the correlation dimension with the keyword of basic word association and basic word can be first determined；Predetermined
All keywords in correlation dimension with basic word are obtained on content platform.It, can be flexibly according to specific by above-mentioned processing
Needs control the quantity of the keyword got, can be for example, when relatively broad with the keyword of basic word association
Correlation dimension controls few, so that the quantity of the keyword obtained is unlikely to too many；When the pass with basic word association
When keyword is more rare, correlation dimension can be controlled more, so that the keyword obtained is comprehensive.
Optionally, when generating knowledge mapping according to the determining degree of association, can include in knowledge mapping to content information
Useful information is searched for, for example, it may be some necessary information, for example, the degree of association between basic word and keyword, certainly
Can also include some auxiliary informations, for example, the basic temperature of word and the temperature of keyword, including auxiliary information
For more fully being shown to the information to be searched for.For example, when being shown to the content information searched out, Ke Yixian
Show the temperature of the content information, so as to which user be facilitated preferably to know the attention rate of the content information.When being wrapped in knowledge mapping
The auxiliary information included includes the temperature of basic word, during the temperature of keyword, can first pass through in the following manner and obtain basic word
Temperature, the temperature of keyword：It first obtains frequency that basic word occurs in predetermined content platform and keyword is put down in predetermined content
The frequency that platform occurs；Later, according to basic word the frequency that predetermined content platform occurs determine basic word temperature and according to
Keyword determines the temperature of keyword in the frequency that predetermined content platform occurs.So as to generate knowledge graph according to the determining degree of association
Spectrum, wherein, the degree of association of basic word and keyword, the temperature of basic word, the temperature of keyword are included in knowledge mapping.
Knowledge mapping to search for for content information is more perfect, so that the content information of search is more smart
Really, the knowledge mapping of generation can timely be corrected after according to determining degree of association generation knowledge mapping, wherein
Modified mode can be a variety of, for example, can be realized according to the operation issued to predetermined content platform, for example, can first connect
Receive the search operation and/or clicking operation of input；According to the search operation and/or clicking operation of reception, to the knowledge of generation
Collection of illustrative plates is modified.For concrete example, after above-mentioned knowledge mapping is generated, input of the user to a certain basic word is received,
The number for inputting the basis word is counted, when the number of statistics reaches input pre-value, it may be determined that the basis word is works as
Under heat search word, therefore, directly by the temperature of the basis word be turned up.Equally receiving click behaviour of the user to a certain basic word
When making, the number for clicking the basis word is counted, reaches the pre- timing of click in the number of statistics, it may be determined that the basis word
For high concern word instantly, therefore, directly the temperature of the basis word is turned up.The temperature after adjustment is adapted to knowledge graph later
In spectrum, according to revised knowledge mapping, to realize the search feedback to content information, so that the content information of feedback is more
It is accurate.
It should be noted that after according to determining degree of association generation knowledge mapping, content information is scanned for instead
During feedback, following processing mode may be used：Receive the search term for search of input；It whether there is in judgemental knowledge collection of illustrative plates
With the matched basic word of search term；In the case where the judgment result is yes, obtain basic word content information and with basic word
The content information of associated keyword；The content information of display base word and the content information of keyword.Pass through matched mode
The content information of the not only content information of display base word, also display and the keyword of basic word association, realizes quick, high
Effect accurately feeds back content information.
Optionally, it in the content information of the content information of display base word and keyword, is closed with matched basic word
The keyword of connection may be used diversified forms and the content information of multiple keywords shown there are in the case of multiple, example
Such as, it may be used and acquisition ranking results first be ranked up to size of multiple keywords according to the degree of association；Showing basic word
While, the content information according to ranking results display keyword.It, can be aobvious according to needing flexibly to control when specifically being shown
The quantity shown for example, when the content information of keyword is more, can will show the quantity control of the keyword of content information
It obtains smaller；And when the content information of keyword is smaller, it can will show that the quantity of the keyword of content information controls
It is more.
It should be noted that it is above-mentioned basis the content information of word and/or the content information of keyword may each comprise it is a variety of,
For example, at least one of can be included：Domestic News, trend of investment, action message, industry patent, service information, technology text
Shelves, industry Zone Information.Classification annotation or right is carried out by the content information of the content information to basic word and/or keyword
Above-mentioned included type is finely divided, for example, Domestic News include：Sports news information, entertainment news information etc., investment are dynamic
State includes real estate investment dynamic, equity investment dynamic etc., and industry patent includes patent of invention information, utility model patent information
Include commerce services information, service for life etc. Deng, service information.By in the content information and/or keyword to basic word
Hold information and carry out classification annotation, it would be desirable to which user oneself sees the content for oneself being needed to be distinguished after the page, believes by content
Breath feeds back to user and has just carried out corresponding mark before, and having effectively achieved may need the content distinguished to carry out area user
Point so that it is more accurate to the information of user feedback by knowledge mapping.
In embodiments of the present invention, a kind of knowledge mapping generating means are additionally provided, Fig. 2 is according to embodiments of the present invention
The structure diagram of knowledge mapping generating means, as shown in Fig. 2, the device includes：Handling module 22, the first acquisition module 24, really
Cover half block 26 and generation module 28, below illustrate the device.
Handling module 22, for capturing basic word in predetermined content platform；First acquisition module 22, is connected to above-mentioned crawl
Module 22, for obtaining the keyword with basic word association on predetermined content platform；Determining module 26 is connected to above-mentioned first
Acquisition module 22 for the frequency occurred simultaneously according to basic word and keyword, determines being associated between basis word and keyword
Degree；Generation module 28 is connected to above-mentioned determining module 26, for generating knowledge mapping according to the determining degree of association, wherein, knowledge
Collection of illustrative plates includes multiple basic words and the keyword with multiple basic word associations, and knowledge mapping is anti-for the search of content information
Feedback.
Fig. 3 is the structure diagram of the first acquisition module 22 in knowledge mapping generating means according to embodiments of the present invention, such as
Shown in Fig. 3, which includes：First determination unit 32 and first acquisition unit 34 below carry out first acquisition module 22
Explanation.
First determination unit 32, for determining the correlation dimension with the keyword of basic word association and basic word；First obtains
Unit 34 is taken, is connected to above-mentioned first determination unit 32, for being obtained on predetermined content platform with basic word in correlation dimension
Interior all keywords.
Fig. 4 is the structure diagram of generation module 28 in knowledge mapping generating means according to embodiments of the present invention, such as Fig. 4 institutes
Show, which includes：Second acquisition unit 42, the second determination unit 44 and generation unit 46, below to the generation mould
Block 28 illustrates.
Second acquisition unit 42, the frequency occurred for obtaining basic word in predetermined content platform and keyword are pre-
Determine the frequency of content platform appearance；Second determination unit 44 is connected to above-mentioned second acquisition unit 42, for being existed according to basic word
The frequency that the frequency that predetermined content platform occurs determines the temperature of basic word and occurred according to keyword in predetermined content platform
Determine the temperature of keyword；Generation unit 46 is connected to above-mentioned second determination unit 44, for according to determining degree of association generation
Knowledge mapping, wherein, the degree of association of basic word and keyword, the temperature of basic word, the heat of keyword are included in knowledge mapping
Degree.
Fig. 5 is the preferred structure block diagram one of knowledge mapping generating means according to embodiments of the present invention, as shown in figure 5, should
Device further includes in addition to including all structures shown in Fig. 2：First receiving module 52 and correcting module 54, it is preferred to this below
Structure illustrates.
First receiving module 52 is connected to above-mentioned generation module 28, for receiving the search operation of input and/or click
Operation；Correcting module 54 is connected to above-mentioned first receiving module 52, for the search operation and/or clicking operation according to reception,
The knowledge mapping of generation is modified.
Fig. 6 is the preferred structure block diagram two of knowledge mapping generating means according to embodiments of the present invention, as shown in fig. 6, should
Device further includes in addition to including all structures shown in Fig. 2：Second receiving module 62, judgment module 64, the second acquisition module 66
With display module 68, the preferred structure is illustrated below.
Second receiving module 62 is connected to above-mentioned generation module 28, for receiving the search term for search of input；
Judgment module 64 is connected to above-mentioned second receiving module 62, matched with search term for whether there is in judgemental knowledge collection of illustrative plates
Basic word；Second acquisition module 66 is connected to above-mentioned judgment module 64, in the case where the judgment result is yes, obtaining base
The content information of plinth word and the content information with the keyword of basic word association；Display module 68 is connected to above-mentioned second and obtains
Modulus block 66, for the content information of display base word and the content information of keyword.
Fig. 7 is the preferred structure block diagram of display module 68 in knowledge mapping generating means according to embodiments of the present invention, such as
Shown in Fig. 7, which includes：Sequencing unit 72 and display unit 74 below illustrate the display module 68.
Sequencing unit 72, for the keyword of matched basic word association there are in the case of multiple, to multiple passes
Keyword is ranked up acquisition ranking results according to the size of the degree of association；Display unit 74 is connected to above-mentioned sequencing unit 72, is used for
While basic word is shown, the content information of keyword is shown according to ranking results.
For the complicated internet information of solution, user is allowed to search more accurately information, in embodiments of the present invention,
Provide a kind of working knowledge interconnection carries out the method for information search.The purpose of knowledge interconnection is one people of structure and machine
The WWW being appreciated that so that network is more intelligent.Knowledge mapping is the semantic knowledge-base of structuring, for symbol
Number form describes concept and its correlation in physical world, and basic composition unit is " entity-relationship-entity " ternary
Group and entity and its association attributes-value pair are interconnected by relationship between entity, the webbed structure of knowledge of structure.In this hair
In bright embodiment, a kind of knowledge mapping structure (or to generate) method towards Intelligent hardware field is specifically provided, wherein,
The knowledge mapping be divided into database and user foreground two parts, in database part：Pass through the content platform in setting first
Keyword crawl is carried out, the knowledge dictionary of incidence relation is established, data is associated and classified by labeling, are carried out at the same time
Data cleansing forms the knowledge base in Intelligent hardware field with concluding.It should be noted that signified intelligence in embodiments of the present invention
Energy hardware is a scientific and technological concept, refers to be combined to traditional equipment progress intellectualized reconstruction by hardware and software.Transformation pair
As that can be electronic equipment, for example, wrist-watch, TV and other electric appliances；Can also be the equipment without electronization, for example, door lock,
Teacup, automobile etc..For example, Intelligent hardware can extend to smart television, smart home, intelligent automobile, doctor from wearable device
Treat health, intelligent toy, robot etc..
Fig. 8 is showing for the database sharing of the knowledge mapping according to the preferred embodiment of the invention towards Intelligent hardware field
It is intended to, as shown in figure 8, the flow is including as follows：Crawler capturing is carried out at the same time data cleansing；It is carried out according to crawler capturing result
Entry and score value are associated with, so as to generate hardware knowledge database.It is for example, specific as follows：It is carried out by the content platform in setting
Keyword captures, and establishes basic dictionary, is carried out at the same time data cleansing with concluding, it should be noted that data are carried out cleaning and
During conclusion, preset cleaning rule may be used or induction rule carries out, by preset cleaning rule to one
A little more miscellaneous or redundancy data are cleaned so that the data after cleaning can more targetedly serve user；
Inducing classification is carried out to data by induction rule so that the data after inducing classification can mutually understand, it will be apparent that distinguish, section
The discrimination time of user is saved, improves user experience；With these bases, dictionary is served as theme, and obtains basis respectively on the platform of setting
The same level-one keyword data of each word association in dictionary.Then to all keywords, how much sorted according to the frequency of appearance
So that it is determined that the absolute temperature of a word；According to the frequency of other words that using some word as core, statistics occurs simultaneously with the word
Rate, to determine the stiffness of coupling of a word and another word.The forward-backward correlation searched for and clicked according to user, carrys out dynamic corrections word
Temperature and word and word between the degree of association.Each keyword is associated with the corresponding Domestic News of setting content platform, throwing behind
Provide the content informations such as dynamic, correlated activation, related patents, relevant documentation.
Based on the method for above-mentioned knowledge mapping structure, can be accomplished in several ways, for example, can be following by including
The system of cluster or module is realized, for example, the system includes：Reptile cluster, Hadoop distributed storages cluster, natural language
Speech processing cluster, Mahout knowledge excavations module and knowledge data base；Wherein, which is used for according to seed address, grabs
Web data is taken, and web data is stored in webpage HBase table；Natural language processing cluster is used to be distributed from the Hadoop
It obtains the webpage HBase table in formula storage cluster, generates original knowledge information, and the original knowledge information is stored in and original is known
Know in HBase table；The Mahout knowledge excavations module is used to carry out the original knowledge information knowledge excavation, and generation is unstructured
Data, and the unstructured data is stored in unstructured data HBase table；The knowledge data base is used for according to through remarkable
The unstructured data structure knowledge mapping of work audit.
In user's foreground partition：When user foreground key in search term scan for, system can by corresponding keyword into
Row displaying, the classifying content that keyword is related to can include a variety of, it may for example comprise technical documentation, industry patent, industry Zone Information,
Related service, action message, trend of investment etc..In addition, after user logs in, user inputs a search term, not only provides this
The absolute temperature of a search term, moreover it is possible to provide the keyword distribution of different strengths and weaknesses of coupled degree, and combine the strong pass of the degree of coupling
Keyword recommends corresponding content.By the knowledge mapping towards Intelligent hardware field, solves Intelligent hardware domain knowledge figure
The blank of spectrum realizes the active demand to conformability and relevance of Intelligent hardware industry.Furthermore it is also possible to it provides to the user
The more industry data of precise specifications and abundant expression help user more easily to obtain Intelligent hardware domain knowledge.
Fig. 9 is that the user foreground of the knowledge mapping according to the preferred embodiment of the invention towards Intelligent hardware field was searched for
The schematic diagram of journey, as shown in figure 9, the user foreground search process is including as follows：Receive search term input by user；By knowing
Know database and filter information is carried out to the search term of input；Filter information is sent to displaying end later：It is number in the selection result
It is data presence and complete feelings in the selection result according to data of the database there is no search there is no in the case of, are prompted
Under condition, the sub-category complete information data of displaying.To further improve user experience, can further be closed in knowledge data base
Connection keyword (with basic word association) is associated with content information, for example, for example, user (corresponds to above-mentioned in input tennis
Signified search term), the corresponding content information of corresponding with tennis movement (keyword) is shown, to further improve user's body
It tests, can also be associated with and be associated with content information with motion association, for example, the other ball information (for example, football) of association, other
The action message (for example, information of football match) of movement, other sports equipment information are (for example, the brand that football needs
The information of football shirt) etc..
By including above-mentioned database and the two-part knowledge mapping in user foreground, solve in the relevant technologies, it is impossible to carry
For the knowledge mapping in Intelligent hardware field, it is impossible to provide the user with the knowledge in the Intelligent hardware field of the profession of system, it is impossible to full
The technical issues of user demand in sufficient Intelligent hardware field.By the structure of the above-mentioned knowledge mapping towards Intelligent hardware field,
Intelligent hardware field content multi-resources Heterogeneous is efficiently solved, the problem of institutional framework is loose, while realize intelligentized search
With personalized recommendation, meet the stratification in Intelligent hardware field, the user demand of structuring.By knowledge mapping technology, more
The answer that the feedback user of intelligence needs.
The embodiments of the present invention are for illustration only, do not represent the quality of embodiment.
In the above embodiment of the present invention, all emphasize particularly on different fields to the description of each embodiment, do not have in some embodiment
The part of detailed description may refer to the associated description of other embodiment.
In several embodiments provided herein, it should be understood that disclosed technology contents can pass through others
Mode is realized.Wherein, the apparatus embodiments described above are merely exemplary, such as the division of the unit, Ke Yiwei
A kind of division of logic function, can there is an other dividing mode in actual implementation, for example, multiple units or component can combine or
Person is desirably integrated into another system or some features can be ignored or does not perform.Another point, shown or discussed is mutual
Between coupling, direct-coupling or communication connection can be INDIRECT COUPLING or communication link by some interfaces, unit or module
It connects, can be electrical or other forms.
The unit illustrated as separating component may or may not be physically separate, be shown as unit
The component shown may or may not be physical unit, you can be located at a place or can also be distributed to multiple
On unit.Some or all of unit therein can be selected according to the actual needs to realize the purpose of this embodiment scheme.
In addition, each functional unit in each embodiment of the present invention can be integrated in a processing unit, it can also
That each unit is individually physically present, can also two or more units integrate in a unit.Above-mentioned integrated list
The form that hardware had both may be used in member is realized, can also be realized in the form of SFU software functional unit.
If the integrated unit is realized in the form of SFU software functional unit and is independent product sale or uses
When, it can be stored in a computer read/write memory medium.Based on such understanding, technical scheme of the present invention is substantially
The part to contribute in other words to the prior art or all or part of the technical solution can be in the form of software products
It embodies, which is stored in a storage medium, is used including some instructions so that a computer
Equipment (can be personal computer, server or network equipment etc.) perform each embodiment the method for the present invention whole or
Part steps.And aforementioned storage medium includes：USB flash disk, read-only memory (ROM, Read-OnlyMemory), arbitrary access are deposited
Reservoir (RAM, Random Access Memory), mobile hard disk, magnetic disc or CD etc. are various can to store program code
Medium.
The above is only the preferred embodiment of the present invention, it is noted that for the ordinary skill people of the art
For member, various improvements and modifications may be made without departing from the principle of the present invention, these improvements and modifications also should
It is considered as protection scope of the present invention.
Claims (13)
1. a kind of knowledge mapping generation method, which is characterized in that including：
Basic word is captured in predetermined content platform；
The keyword with the basic word association is obtained on the predetermined content platform；
According to the frequency that the basic word occurs simultaneously with the keyword, determine between the basic word and the keyword
The degree of association；
Knowledge mapping is generated according to the determining degree of association, wherein, the knowledge mapping include multiple basic words with
With the keyword of the multiple basic word association, the knowledge mapping feeds back for the search of content information.
2. it according to the method described in claim 1, it is characterized in that, is obtained on the predetermined content platform and the basic word
The associated keyword includes：
Determine the correlation dimension with the keyword of the basic word association and the basic word；
All keywords in the correlation dimension with the basic word are obtained on the predetermined content platform.
3. according to the method described in claim 1, it is characterized in that, the knowledge mapping is generated according to the determining degree of association
Including：
It obtains frequency that the basic word occurs in the predetermined content platform and the keyword is put down in the predetermined content
The frequency that platform occurs；
The temperature of the basic word is determined and according to institute in the frequency that the predetermined content platform occurs according to the basic word
State the temperature that keyword determines the keyword in the frequency that the predetermined content platform occurs；
The knowledge mapping is generated according to the determining degree of association, wherein, the basic word is included in the knowledge mapping
With the degree of association of the keyword, the temperature of the basis word, the temperature of the keyword.
4. according to the method described in claim 1, it is characterized in that, generating the knowledge graph according to the determining degree of association
After spectrum, further include：
Receive the search operation and/or clicking operation of input；
According to the operation of the described search of reception and/or clicking operation, the knowledge mapping of generation is modified.
5. method according to any one of claim 1 to 4, which is characterized in that according to determining degree of association life
Into after the knowledge mapping, further include：
Receive the search term for search of input；
Judge in the knowledge mapping to whether there is and the matched basic word of described search word；
In the case where the judgment result is yes, the content information of the basic word and the pass with the basic word association are obtained
The content information of keyword；
Show the basic content information of word and the content information of the keyword.
6. according to the method described in claim 5, it is characterized in that, the content information and the keyword of the display basic word
Content information include：
With the keyword of the matched basic word association there are in the case of multiple, to multiple keywords according to the degree of association
Size is ranked up acquisition ranking results；
While the basic word is shown, the content information of the keyword is shown according to ranking results.
7. method according to claim 5 or 6, which is characterized in that the content information of the basis word and/or the key
The content information of word includes：Domestic News, trend of investment, action message, industry patent, service information, technical documentation, industry
Information.
8. a kind of knowledge mapping generating means, which is characterized in that including：
Handling module, for capturing basic word in predetermined content platform；
First acquisition module, for obtaining the keyword with the basic word association on the predetermined content platform；
Determining module for the frequency occurred simultaneously with the keyword according to the basic word, determines the basic word and institute
State the degree of association between keyword；
Generation module, for generating knowledge mapping according to the determining degree of association, wherein, the knowledge mapping includes multiple
The basis word and the keyword with the multiple basic word association, the knowledge mapping feed back for the search of content information.
9. device according to claim 8, which is characterized in that first acquisition module includes：
First determination unit, for determining the correlation dimension with the keyword of the basic word association and the basic word；
First acquisition unit, for obtaining the institute with the basic word in the correlation dimension on the predetermined content platform
There is keyword.
10. device according to claim 8, which is characterized in that the generation module includes：
Second acquisition unit, the frequency and the key occurred for obtaining the basic word in the predetermined content platform
The frequency that word occurs in the predetermined content platform；
Second determination unit, for determining the basic word in the frequency that the predetermined content platform occurs according to the basic word
Temperature and the temperature of the keyword is determined in the frequency that the predetermined content platform occurs according to the keyword；
Generation unit, for generating the knowledge mapping according to the determining degree of association, wherein, it is included in the knowledge mapping
There are the degree of association of the basic word and the keyword, the temperature of the basis word, the temperature of the keyword.
11. device according to claim 8, which is characterized in that further include：
First receiving module, for receiving the search operation of input and/or clicking operation；
Correcting module, for according to the operation of the described search of reception and/or clicking operation, being carried out to the knowledge mapping of generation
It corrects.
12. the device according to any one of claim 8 to 11, which is characterized in that further include：
Second receiving module, for receiving the search term for search of input；
Judgment module, for judging to whether there is in the knowledge mapping and the matched basic word of described search word；
Second acquisition module, in the case where the judgment result is yes, obtain the basic word content information and with institute
State the content information of the keyword of basic word association；
Display module, for showing the basic content information of word and the content information of the keyword.
13. device according to claim 12, which is characterized in that the display module includes：
Sequencing unit, for the keyword of the matched basic word association there are in the case of multiple, to multiple keys
Word is ranked up acquisition ranking results according to the size of the degree of association；
Display unit, for while the basic word is shown, the content letter of the keyword to be shown according to ranking results
Breath.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201711217693.XA CN108132966A (en) | 2017-11-28 | 2017-11-28 | Knowledge mapping generation method and device |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201711217693.XA CN108132966A (en) | 2017-11-28 | 2017-11-28 | Knowledge mapping generation method and device |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN108132966A true CN108132966A (en) | 2018-06-08 |
Family
ID=62389806
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201711217693.XA Pending CN108132966A (en) | 2017-11-28 | 2017-11-28 | Knowledge mapping generation method and device |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN108132966A (en) |
Cited By (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109829059A (en) * | 2019-01-18 | 2019-05-31 | 平安科技（深圳）有限公司 | Recommend method, apparatus, equipment and the storage medium of knowledge point |
| CN110188241A (en) * | 2019-06-04 | 2019-08-30 | 成都索贝数码科技股份有限公司 | A kind of race intelligence manufacturing system and production method |
| CN110442765A (en) * | 2019-07-04 | 2019-11-12 | 卓尔智联(武汉)研究院有限公司 | Information processing method, device, terminal and storage medium |
| CN110851610A (en) * | 2018-07-25 | 2020-02-28 | 百度在线网络技术（北京）有限公司 | Knowledge graph generation method and device, computer equipment and storage medium |
| CN110929019A (en) * | 2018-08-30 | 2020-03-27 | 深圳市蓝灯鱼智能科技有限公司 | Information display method and device, storage medium and electronic device |
| CN110990584A (en) * | 2019-11-26 | 2020-04-10 | 口口相传(北京)网络技术有限公司 | Knowledge graph generation method and device |
| CN111737477A (en) * | 2020-08-07 | 2020-10-02 | 杭州六棱镜知识产权科技有限公司 | Intellectual property big data-based intelligence investigation method, system and storage medium |
| CN112911073A (en) * | 2019-04-30 | 2021-06-04 | 五竹科技(北京)有限公司 | Intelligent knowledge graph construction method and device for outbound process conversation content |
| CN113987374A (en) * | 2021-10-27 | 2022-01-28 | 北京达佳互联信息技术有限公司 | Word cloud display method and device, electronic equipment, medium and product |
| CN115658929A (en) * | 2022-12-14 | 2023-01-31 | 天津理工大学 | Asset management knowledge graph generation method, device and system |
| CN117633253A (en) * | 2024-01-25 | 2024-03-01 | 南京大学 | Scientific-technical association detection method based on knowledge network multidimensional coupling |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20090327279A1 (en) * | 2008-06-25 | 2009-12-31 | International Business Machines Corporation | Apparatus and method for supporting document data search |
| CN102591862A (en) * | 2011-01-05 | 2012-07-18 | 华东师范大学 | Control method and device of Chinese entity relationship extraction based on word co-occurrence |
| CN104408102A (en) * | 2014-11-19 | 2015-03-11 | 北京国双科技有限公司 | Data processing method and device for association degree of network hot words and object |
| CN104462507A (en) * | 2014-12-19 | 2015-03-25 | 北京奇虎科技有限公司 | Method and device for establishing knowledge graph based on movie songs |
| CN104462501A (en) * | 2014-12-19 | 2015-03-25 | 北京奇虎科技有限公司 | Knowledge graph construction method and device based on structural data |
| CN105159912A (en) * | 2015-07-06 | 2015-12-16 | 无锡天脉聚源传媒科技有限公司 | Method and apparatus for processing degree of correlation among different words |
| CN106528616A (en) * | 2016-09-30 | 2017-03-22 | 厦门快商通科技股份有限公司 | Language error correcting method and system for use in human-computer interaction process |
-
2017
- 2017-11-28 CN CN201711217693.XA patent/CN108132966A/en active Pending
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20090327279A1 (en) * | 2008-06-25 | 2009-12-31 | International Business Machines Corporation | Apparatus and method for supporting document data search |
| CN102591862A (en) * | 2011-01-05 | 2012-07-18 | 华东师范大学 | Control method and device of Chinese entity relationship extraction based on word co-occurrence |
| CN104408102A (en) * | 2014-11-19 | 2015-03-11 | 北京国双科技有限公司 | Data processing method and device for association degree of network hot words and object |
| CN104462507A (en) * | 2014-12-19 | 2015-03-25 | 北京奇虎科技有限公司 | Method and device for establishing knowledge graph based on movie songs |
| CN104462501A (en) * | 2014-12-19 | 2015-03-25 | 北京奇虎科技有限公司 | Knowledge graph construction method and device based on structural data |
| CN105159912A (en) * | 2015-07-06 | 2015-12-16 | 无锡天脉聚源传媒科技有限公司 | Method and apparatus for processing degree of correlation among different words |
| CN106528616A (en) * | 2016-09-30 | 2017-03-22 | 厦门快商通科技股份有限公司 | Language error correcting method and system for use in human-computer interaction process |
Cited By (18)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110851610A (en) * | 2018-07-25 | 2020-02-28 | 百度在线网络技术（北京）有限公司 | Knowledge graph generation method and device, computer equipment and storage medium |
| CN110851610B (en) * | 2018-07-25 | 2022-09-27 | 百度在线网络技术（北京）有限公司 | Knowledge graph generation method and device, computer equipment and storage medium |
| CN110929019A (en) * | 2018-08-30 | 2020-03-27 | 深圳市蓝灯鱼智能科技有限公司 | Information display method and device, storage medium and electronic device |
| CN110929019B (en) * | 2018-08-30 | 2022-06-10 | 北京蓝灯鱼智能科技有限公司 | Information display method and device, storage medium and electronic device |
| CN109829059A (en) * | 2019-01-18 | 2019-05-31 | 平安科技（深圳）有限公司 | Recommend method, apparatus, equipment and the storage medium of knowledge point |
| CN112911073A (en) * | 2019-04-30 | 2021-06-04 | 五竹科技(北京)有限公司 | Intelligent knowledge graph construction method and device for outbound process conversation content |
| CN110188241A (en) * | 2019-06-04 | 2019-08-30 | 成都索贝数码科技股份有限公司 | A kind of race intelligence manufacturing system and production method |
| CN110188241B (en) * | 2019-06-04 | 2023-07-25 | 成都索贝数码科技股份有限公司 | Intelligent manufacturing system and manufacturing method for events |
| CN110442765A (en) * | 2019-07-04 | 2019-11-12 | 卓尔智联(武汉)研究院有限公司 | Information processing method, device, terminal and storage medium |
| CN110442765B (en) * | 2019-07-04 | 2022-03-11 | 卓尔智联(武汉)研究院有限公司 | Information processing method, device, terminal and storage medium |
| CN110990584A (en) * | 2019-11-26 | 2020-04-10 | 口口相传(北京)网络技术有限公司 | Knowledge graph generation method and device |
| CN110990584B (en) * | 2019-11-26 | 2021-02-09 | 口口相传(北京)网络技术有限公司 | Knowledge graph generation method and device |
| CN111737477A (en) * | 2020-08-07 | 2020-10-02 | 杭州六棱镜知识产权科技有限公司 | Intellectual property big data-based intelligence investigation method, system and storage medium |
| CN113987374A (en) * | 2021-10-27 | 2022-01-28 | 北京达佳互联信息技术有限公司 | Word cloud display method and device, electronic equipment, medium and product |
| CN115658929A (en) * | 2022-12-14 | 2023-01-31 | 天津理工大学 | Asset management knowledge graph generation method, device and system |
| CN115658929B (en) * | 2022-12-14 | 2023-03-28 | 天津理工大学 | Asset management knowledge graph generation method, device and system |
| CN117633253A (en) * | 2024-01-25 | 2024-03-01 | 南京大学 | Scientific-technical association detection method based on knowledge network multidimensional coupling |
| CN117633253B (en) * | 2024-01-25 | 2024-04-30 | 南京大学 | Scientific-technical association detection method based on knowledge network multidimensional coupling |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN108132966A (en) | Knowledge mapping generation method and device | |
| CN106446195A (en) | News recommending method and device based on artificial intelligence | |
| US9135370B2 (en) | Method and apparatus of generating update parameters and displaying correlated keywords | |
| CN104809243B (en) | It is a kind of that method is recommended based on the mixing excavated to user behavior composite factor | |
| CN103744928B (en) | A kind of network video classification method based on history access record | |
| CN105095219B (en) | Micro-blog recommendation method and terminal | |
| CN103699700B (en) | A kind of generation method of search index, system and associated server | |
| CN107918616A (en) | Search system, page display method and client | |
| CN103984740B (en) | Based on the method and system that the retrieved page of combination tag shows | |
| CN102163228B (en) | Method, apparatus and device for determining sorting result of resource candidates | |
| CN110380954A (en) | Data sharing method and device, storage medium and electronic device | |
| CN107633021A (en) | A kind of dispensing of graph text information, generation method and device | |
| CN105243087A (en) | IT (Information Technology) information aggregation reading personalized recommendation method | |
| CN106682145A (en) | Enterprise information processing method, server and client | |
| CN107563867A (en) | A kind of commending system cold start-up method based on multi-arm fruit machine confidence upper limit | |
| CN109711867A (en) | Shopper based on rating big data, which draws a portrait, constructs marketing method and system | |
| CN106777282B (en) | The sort method and device of relevant search | |
| CN103577405A (en) | Interest analysis based micro-blogger community classification method | |
| CN108733791A (en) | network event detection method | |
| CN103365904A (en) | Advertising information searching method and system | |
| CN113590928A (en) | Content recommendation method and device and computer-readable storage medium | |
| CN107369058A (en) | A kind of correlation recommendation method and server | |
| CN107220745A (en) | A kind of recognition methods, system and equipment for being intended to behavioral data | |
| CN104077337A (en) | Searching method and device | |
| CN102214227B (en) | Automatic public opinion monitoring method based on internet hierarchical structure storage |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20180608 |