CN109543188A - Object association method, device, server and readable storage medium - Google Patents
Object association method, device, server and readable storage medium Download PDFInfo
- Publication number
- CN109543188A CN109543188A CN201811409565.XA CN201811409565A CN109543188A CN 109543188 A CN109543188 A CN 109543188A CN 201811409565 A CN201811409565 A CN 201811409565A CN 109543188 A CN109543188 A CN 109543188A
- Authority
- CN
- China
- Prior art keywords
- words
- feature
- objects
- word
- providing
- 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
- 238000000034 method Methods 0.000 title claims abstract description 65
- 238000003860 storage Methods 0.000 title claims abstract description 18
- 230000006870 function Effects 0.000 claims abstract description 101
- 239000000284 extract Substances 0.000 claims abstract description 20
- 238000004422 calculation algorithm Methods 0.000 claims description 27
- 238000003058 natural language processing Methods 0.000 claims description 23
- 238000004891 communication Methods 0.000 claims description 19
- 238000000605 extraction Methods 0.000 claims description 16
- 238000004590 computer program Methods 0.000 claims description 14
- 238000012545 processing Methods 0.000 claims description 9
- 238000013507 mapping Methods 0.000 claims description 7
- 241000406668 Loxodonta cyclotis Species 0.000 claims description 3
- 230000008569 process Effects 0.000 abstract description 22
- 238000007726 management method Methods 0.000 description 19
- 238000010586 diagram Methods 0.000 description 12
- 238000012986 modification Methods 0.000 description 5
- 230000004048 modification Effects 0.000 description 5
- 238000005516 engineering process Methods 0.000 description 4
- 238000004378 air conditioning Methods 0.000 description 2
- 238000004364 calculation method Methods 0.000 description 2
- 238000005304 joining Methods 0.000 description 2
- 230000003287 optical effect Effects 0.000 description 2
- 230000002093 peripheral effect Effects 0.000 description 2
- 238000006467 substitution reaction Methods 0.000 description 2
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 2
- 230000008859 change Effects 0.000 description 1
- 238000013500 data storage Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000005108 dry cleaning Methods 0.000 description 1
- 235000013399 edible fruits Nutrition 0.000 description 1
- 230000005611 electricity Effects 0.000 description 1
- 238000000802 evaporation-induced self-assembly Methods 0.000 description 1
- 238000001027 hydrothermal synthesis Methods 0.000 description 1
- 238000012423 maintenance Methods 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 230000009467 reduction Effects 0.000 description 1
- 238000005057 refrigeration Methods 0.000 description 1
- 238000012216 screening Methods 0.000 description 1
- 239000004065 semiconductor Substances 0.000 description 1
- 239000007787 solid Substances 0.000 description 1
- 238000012546 transfer Methods 0.000 description 1
- 238000005406 washing Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F40/00—Handling natural language data
- G06F40/30—Semantic analysis
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Health & Medical Sciences (AREA)
- Artificial Intelligence (AREA)
- Audiology, Speech & Language Pathology (AREA)
- Computational Linguistics (AREA)
- General Health & Medical Sciences (AREA)
- Physics & Mathematics (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Machine Translation (AREA)
Abstract
The invention discloses an object association method, an object association device, a server and a readable storage medium, wherein the method comprises the following steps: for each object to be associated, extracting a feature word set of the object to be associated from pre-stored content description information of the object to be associated, wherein the feature word set is used for representing a set of feature words of service functions which can be provided by the object to be associated; for every two objects to be associated, judging whether the service functions which can be provided by the two objects to be associated are matched or not according to the feature word sets of the two objects to be associated; and if so, associating the two objects to be associated. According to the invention, the server can extract the feature word set representing the service function which can be provided by the object to be associated, and then associates the two objects to be associated when the two objects to be associated are matched according to the extracted feature word set of the object to be associated, so that the whole object association process is not artificially participated, and the accuracy and efficiency of the associated object are greatly improved.
Description
Technical field
The present invention relates to field of computer technology more particularly to a kind of method of mapping, device, server and readable deposit
Storage media.
Background technique
With the development of cloud computing technology, each cloud application requires the background management system being managed to it,
User can be managed the related object in cloud application by background management system, and to associated with the object after management
Object selected.Such as user such as can be created or be modified by object of the background management system to cloud application at the management
Operation, and object associated with the creation or modified object is selected, associated two objects are usually answered in same cloud
The same or similar function services are played in.
In the prior art when carrying out the association between object, user needs to transfer out two objects pre-saved manually
Information determines whether the two objects match by checking the information of two objects, and upon determining a match, user also needs
The two objects are associated manually.
When cloud application scale becomes larger, and the function services provided become more, the object in cloud application can also increase significantly even
There are mass data objects will lead to the accurate of affiliated partner since the associated process of object is manually completed by user
Property and efficiency substantially reduce.
Summary of the invention
The present invention provides a kind of method of mapping, device, server and readable storage medium storing program for executing, to solve existing skill
The low problem of the accuracy and efficiency of manual association object in art.
The present invention provides a kind of method of mapping, are applied to server, this method comprises:
For each object to be associated, in the content description information of the object to be associated pre-saved, extracting should be to
The feature set of words of affiliated partner, wherein the Feature Words set is for characterizing the service function that the object to be associated is capable of providing
Feature Words set；
For every two object to be associated, according to the feature set of words of two objects to be associated, judge this two wait close
Whether the service function that connection object is capable of providing matches；If so, being associated with two objects to be associated.
Further, each object to be associated belongs to same cloud application.
Further, the Feature Words for characterizing the service function that the object to be associated is capable of providing include following at least one
: name feature word, type feature word, attributive character word, functional character word and performance characteristic word.
Further, if the Feature Words for characterizing the service function that the object to be associated is capable of providing include title spy
At least one in word, type feature word and attributive character word is levied, the content in the object to be associated pre-saved is retouched
It states in information, the feature set of words for extracting the object to be associated includes:
Using natural language processing algorithm, the noun in the content description information is extracted；
According to the noun extracted, the name feature for characterizing the service function that the object to be associated is capable of providing is determined
At least one of in word, type feature word and attributive character word.
Further, if the Feature Words for characterizing the service function that the object to be associated is capable of providing include function spy
Word is levied, it is described in the content description information of the object to be associated pre-saved, extract the feature word set of the object to be associated
Conjunction includes:
Using natural language processing algorithm, the verb in the content description information is extracted；
According to the verb extracted, the functional character for characterizing the service function that the object to be associated is capable of providing is determined
Word.
Further, if the Feature Words for characterizing the service function that the object to be associated is capable of providing include performance spy
Word is levied, it is described in the content description information of the object to be associated pre-saved, extract the feature word set of the object to be associated
Conjunction includes:
Using natural language processing algorithm, the adjective in the content description information is extracted；
According to the adjective extracted, determine that the performance for characterizing the service function that the object to be associated is capable of providing is special
Levy word.
Further, the feature set of words according to two objects to be associated judges this two object energy to be associated
Whether the service function enough provided matches
According to the Feature Words in the feature set of words of two objects to be associated, the matching of two objects to be associated is determined
Degree；
Judge whether the matching degree of two objects to be associated is greater than the matching degree threshold value of setting.
Further, the feature set of words according to two objects to be associated, determines two objects to be associated
Matching degree includes:
Feature Words in the feature set of words of two objects to be associated are subjected to string matching and/or semantic scene
Match, determines the matching degree of two objects to be associated.
Further, the Feature Words by the feature set of words of two objects to be associated carry out string matching,
The matching degree for determining two objects to be associated includes:
Feature Words in the feature set of words of two objects to be associated are subjected to string matching；
According to the quantity of matched Feature Words, the matching degree of two objects to be associated is determined.
Further, the Feature Words by the feature set of words of two objects to be associated carry out semantic scene
Match, determines that the matching degree of two objects to be associated includes:
To in the feature set of words of two objects to be associated Feature Words carry out semantic scene division, determine this two to
The semantic scene set of affiliated partner；
By in the semantic scene set of two objects to be associated Feature Words and the semantic scene dictionary that pre-saves into
Row matching, determines the semantic scene feature set of words of two objects to be associated；
Semantic scene Feature Words in the semantic scene feature set of words of two objects to be associated are subjected to character string
Match, according to the quantity of matched semantic scene Feature Words, determines the matching degree of two objects to be associated.
The present invention provides a kind of object association means, are applied to server, which includes:
Extraction module describes letter in the content of the object to be associated pre-saved for being directed to each object to be associated
In breath, the feature set of words of the object to be associated is extracted, wherein the Feature Words set can for characterizing the object to be associated
The set of the Feature Words of the service function of offer；
Relating module, for being sentenced for every two object to be associated according to the feature set of words of two objects to be associated
Whether the service function that two objects to be associated are capable of providing of breaking matches；If so, being associated with two objects to be associated.
Further, each object to be associated belongs to same cloud application.
Further, the Feature Words for characterizing the service function that the object to be associated is capable of providing include following at least one
: name feature word, type feature word, attributive character word, functional character word and performance characteristic word.
Further, if the Feature Words for characterizing the service function that the object to be associated is capable of providing include title spy
At least one in word, type feature word and attributive character word is levied, the extraction module is specifically used for using natural language processing
Algorithm extracts the noun in the content description information；According to the noun extracted, determine for characterizing the object energy to be associated
At least one of in the name feature word of the service function enough provided, type feature word and attributive character word.
Further, if the Feature Words for characterizing the service function that the object to be associated is capable of providing include function spy
Word is levied, the extraction module is specifically used for using natural language processing algorithm, extracts the verb in the content description information；
According to the verb extracted, the functional character word for characterizing the service function that the object to be associated is capable of providing is determined.
Further, if the Feature Words for characterizing the service function that the object to be associated is capable of providing include performance spy
Word is levied, the extraction module is specifically used for using natural language processing algorithm, extracts describing in the content description information
Word；According to the adjective extracted, the performance characteristic word for characterizing the service function that the object to be associated is capable of providing is determined.
Further, the relating module, specifically for the spy in the feature set of words according to two objects to be associated
Word is levied, determines the matching degree of two objects to be associated；Judge whether the matching degree of two objects to be associated is greater than setting
Matching degree threshold value.
Further, the relating module, specifically for by the feature in the feature set of words of two objects to be associated
Word carries out string matching and/or semantic scene matching, determines the matching degree of two objects to be associated.
Further, the relating module, specifically for by the feature in the feature set of words of two objects to be associated
Word carries out string matching；According to the quantity of matched Feature Words, the matching degree of two objects to be associated is determined.
Further, the relating module, specifically for the feature in the feature set of words to two objects to be associated
Word carries out semantic scene division, determines the semantic scene set of two objects to be associated；By the language of two objects to be associated
Feature Words in adopted scene set are matched with the semantic scene dictionary pre-saved, determine the language of two objects to be associated
Adopted scene characteristic set of words；Semantic scene Feature Words in the semantic scene feature set of words of two objects to be associated are carried out
String matching determines the matching degree of two objects to be associated according to the quantity of matched semantic scene Feature Words.
The present invention provides a kind of servers, comprising: processor, communication interface, memory and communication bus, wherein place
Device, communication interface are managed, memory completes mutual communication by communication bus；
It is stored with computer program in the memory, when described program is executed by the processor, so that the place
Manage the step of device executes any of the above-described the method.
The present invention provides a kind of computer readable storage medium, it is stored with the computer journey that can be executed by server
Sequence, when described program is run on the server, so that the step of server executes any of the above-described the method.
The present invention provides a kind of method of mapping, device, server and readable storage medium storing program for executing, this method comprises: needle
To each object to be associated, in the content description information of the object to be associated pre-saved, the object to be associated is extracted
Feature set of words, wherein the Feature Words set is used to characterize the Feature Words for the service function that the object to be associated is capable of providing
Set；For every two object to be associated, according to the feature set of words of two objects to be associated, judge this two it is to be associated right
As whether the service function being capable of providing matches；If so, being associated with two objects to be associated.Server can mention in the present invention
The set for characterizing the Feature Words for the service function that object to be associated is capable of providing is got, then according to the object to be associated extracted
Feature set of words, whether the service function for judging that certain two object to be associated is capable of providing match, when determine this two wait close
When joining object matching, two objects to be associated are associated with, entire object association process does not artificially participate in, and substantially increases association
Accuracy and efficiency in Object Process.
Detailed description of the invention
In order to more clearly explain the embodiment of the invention or the technical proposal in the existing technology, to embodiment or will show below
There is attached drawing needed in technical description to be briefly described, it should be apparent that, the accompanying drawings in the following description is only this
Some embodiments of invention for those of ordinary skill in the art without creative efforts, can be with
It obtains other drawings based on these drawings.
Fig. 1 is a kind of schematic diagram for affiliated partner process that the embodiment of the present invention 1 provides；
Fig. 2 is a kind of flow diagram for affiliated partner that the embodiment of the present invention 3 provides；
Fig. 3 is a kind of flow diagram for affiliated partner that the embodiment of the present invention 4 provides；
Fig. 4 is the structural schematic diagram for a kind of electronic equipment that the embodiment of the present invention 5 provides；
Fig. 5 is a kind of affiliated partner schematic device provided in an embodiment of the present invention.
Specific embodiment
Low in order to improve accuracy and efficiency during affiliated partner, the embodiment of the invention provides a kind of associations of object
Method, apparatus, server and readable storage medium storing program for executing.
To make the objectives, technical solutions, and advantages of the present invention clearer, make below in conjunction with the attached drawing present invention into one
Step ground detailed description, it is clear that described embodiment is only a part of the embodiments of the present invention, rather than whole implementation
Example.Based on the embodiments of the present invention, obtained by those of ordinary skill in the art without making creative efforts
Every other embodiment, shall fall within the protection scope of the present invention.
Embodiment 1:
Fig. 1 be a kind of schematic diagram of object association process provided in an embodiment of the present invention, the process the following steps are included:
S101: being directed to each object to be associated, in the content description information of the object to be associated pre-saved, extracts
The feature set of words of the object to be associated, wherein the Feature Words set is for characterizing the service that the object to be associated is capable of providing
The set of the Feature Words of function.
Method of mapping provided in an embodiment of the present invention is applied to server, which can get at least two
Object to be associated, each object to be associated belong to same cloud application, i.e. server is for same when carrying out object association
Object to be associated in cloud application is associated.
Object in cloud application is capable of providing its corresponding server capability, which can be product and be that product mentions
For the subsystem etc. of management function, the object in cloud background management system can be not limited to product and subsystem object, can also be with
For other objects in cloud background management system.
Can pre-save the content description information of each object to be associated in the server, the object to be associated it is interior
Appearance description information can be user and save in the server when creating or modifying object.
Server can extract the pass in the content description information of the object to be associated for each object to be associated
Join the feature set of words of object, specifically, server can extract in the content description information of the object to be associated should be wait close
Join the Feature Words of object, then according to the Feature Words extracted, determines that the set of the Feature Words of the object to be associated i.e. should be wait close
Join the feature set of words of object.
The Feature Words of object to be associated are the Feature Words for characterizing the service function that object to be associated is capable of providing, and are used for
The Feature Words for characterizing the service function that the object to be associated is capable of providing include at least one of the following: that name feature word, type are special
Levy word, attributive character word, functional character word and performance characteristic word.
When server extracts the Feature Words of object to be associated, it can be extracted, can be adopted using character string interception algorithm
It is extracted with natural language processing algorithm, or is extracted using other Feature Words extraction algorithms in the prior art.
S102: this two are judged according to the feature set of words of two objects to be associated for every two object to be associated
Whether the service function that object to be associated is capable of providing matches；If so, carrying out S103；If not, carrying out S104.
In order to realize the association of two objects, server can be directed to every two object to be associated, according to this two wait close
Whether the feature set of words for joining object, the service function for judging that this two objects to be associated provide match.
Server judges the service that this two objects to be associated provide according to the feature set of words of two objects to be associated
Whether function, which matches can be, carries out string matching and/or language for the Feature Words of the feature set of words of two objects to be associated
Whether adopted scene matching matches according to the service function that matching result judges that this two objects to be associated provide.
Server executes corresponding process according to different judging results.
S103: two objects to be associated are associated with.
If it is determined that two objects to be associated be capable of providing service function matching, then be associated with this two it is to be associated right
As.
The process of two objects to be associated of the association belongs to the prior art, does not repeat them here in embodiments of the present invention.
S104: two objects to be associated are not associated.
If it is determined that the service function that two objects to be associated are capable of providing mismatches, then it is to be associated not right to this two
As being associated.
Using affiliated partner method provided in an embodiment of the present invention by correlation rule, realizes object auto-associating and tie up
Determine the object in the cloud application of cloud platform management system, substitution manually searches the operation with selecting object, solution from list object
Management system of having determined user of service searches from mass object and the accuracy and efficiency problem of selecting object.
Server can extract the feature for characterizing the service function that object to be associated is capable of providing in the embodiment of the present invention
The set of word judges that certain two object to be associated is capable of providing then according to the feature set of words of the object to be associated extracted
Service function whether match, when determining two object matchings to be associated, be associated with two objects to be associated, entire object
Association process does not artificially participate in, and substantially increases the accuracy and efficiency of affiliated partner.
Embodiment 2:
In order to further increase the accuracy and flexibility of affiliated partner, on the basis of the above embodiments, the present invention is real
It applies in example, if including name feature word, type for characterizing the Feature Words for the service function that the object to be associated is capable of providing
At least one of in Feature Words and attributive character word, it is described in the content description information of the object to be associated pre-saved,
The feature set of words for extracting the object to be associated includes:
Using natural language processing algorithm, the noun in the content description information is extracted；
According to the noun extracted, the name feature for characterizing the service function that the object to be associated is capable of providing is determined
At least one of in word, type feature word and attributive character word.
It is described if including functional character word for characterizing the Feature Words for the service function that the object to be associated is capable of providing
In the content description information of the object to be associated pre-saved, the feature set of words for extracting the object to be associated includes:
Using natural language processing algorithm, the verb in the content description information is extracted；
According to the verb extracted, the functional character for characterizing the service function that the object to be associated is capable of providing is determined
Word.
It is described if including performance Feature Words for characterizing the Feature Words for the service function that the object to be associated is capable of providing
In the content description information of the object to be associated pre-saved, the feature set of words for extracting the object to be associated includes:
Using natural language processing algorithm, the adjective in the content description information is extracted；
According to the adjective extracted, determine that the performance for characterizing the service function that the object to be associated is capable of providing is special
Levy word.
Semanteme of the usual different types of Feature Words of object to be associated in content description information is different, therefore can basis
Semanteme in content description information extracts the Feature Words of object to be associated.
Normally, name feature word, type feature word and attributive character word are in content description information in the form of noun
Occur, therefore can be by extracting noun in content description information, to determine that name feature word, type feature word and attribute are special
Levy at least one in word.
Noun is extracted in content description information can realize that the natural language processing is calculated using natural language processing algorithm
Method can be existing algorithm, or modified hydrothermal process on the basis of existing algorithm.
According to the noun extracted, the name feature for characterizing the service function that the object to be associated is capable of providing is determined
In word, type feature word and attributive character word at least one of when, can be the type for pre-saving determination in need, such as in advance
Preserve it needs to be determined that name feature word, then the noun extracted is determined directly as name feature word by server, further for
Guarantee accuracy, can also be that the noun that will be extracted is matched with the dictionary pre-saved, according to matched as a result, really
Name at least one claimed in Feature Words, type feature word and attributive character word.
Name feature word can be the title for the unique identification object, and attributive character word can be used to identify the object
Belong to product or subsystem etc., type feature word can be used to identify the products such as the type such as air-conditioning, washing machine of product object.
Normally, functional character word occurs in the form of verb in content description information, therefore can be by content
Verb is extracted in description information, to determine functional character word.
Verb is extracted in content description information can be realized using natural language processing algorithm.
According to the verb extracted, the functional character for characterizing the service function that the object to be associated is capable of providing is determined
Word can be the verb that will be extracted and be determined directly as functional character word, and further for accuracy is guaranteed, can also be will be mentioned
The verb got is matched with the dictionary pre-saved, according to matched as a result, determining functional character word.
Normally, performance characteristic word occurs in the form of adjectival in content description information, therefore by content
Adjective is extracted in description information, to determine performance Feature Words.
Adjective is extracted in content description information can be realized using natural language processing algorithm.
According to the adjective extracted, determine that the performance for characterizing the service function that the object to be associated is capable of providing is special
Word is levied, the adjective that will be extracted is can be and is determined directly as performance characteristic word, further for accuracy is guaranteed, can also be
The adjective extracted is matched with the dictionary pre-saved, according to matched as a result, determining performance Feature Words.
Specifically, the content description information of an object is usually one section of word, this section of words are divided into several languages first
The independent sentence of justice.Then the subject and other related terms in sentence are found out, is split.Then around these subjects with
And other related terms extract adjective and the verb containing Special Significance, split.Finally, these are split
Word form feature set of words.
Such as product, the Feature Words of extraction such as noun: air-conditioning, refrigerator, water heater.Adjective: it is energy-efficient, it is fresh-keeping,
Quietly, calm.Verb: refrigeration, dry-cleaning.
Such as subsystem, the Feature Words of extraction such as noun: electricity consumption, water consumption, remote controler, customer service, service, door
Shop, voice, Gree store, specification, product, progress, model.Adjective: power consumption, it is energy-efficient, cheap.Verb: maintenance,
It reports for repairment, buys, reserve, inquire, talk with, make a price reduction, give a discount, introduce, download, recycle, clean, install, use.
Due to providing the determination process of various features word in the embodiment of the present invention, association pair can be further increased
The accuracy and flexibility of elephant.
Embodiment 3:
On the basis of the various embodiments described above, in the embodiment of the present invention, the feature according to two objects to be associated
Set of words, judging whether service function that two objects to be associated are capable of providing matches includes:
According to the Feature Words in the feature set of words of two objects to be associated, the matching of two objects to be associated is determined
Degree；
Judge whether the matching degree of two objects to be associated is greater than the matching degree threshold value of setting.
It, can be according to two objects to be associated due to having extracted the feature set of words of two objects to be associated
Feature set of words in Feature Words, determine the matching degrees of two objects to be associated to judge that two objects to be associated are
No matching.
Server determines two objects to be associated according to the Feature Words in the feature set of words of two objects to be associated
Matching degree process, can be according to similarity mode algorithm and be determined, specifically can be according to string matching and/
Or the matched matching result of semantic scene, determine the matching degree of two objects to be associated.
Server can association by the matching degree of determining two objects to be associated, as two objects to be associated
Degree.
The matching degree threshold value of setting is pre-saved in server, setting is servicing when which can be factory
In device, can be according to the use demand of user and habit be arranged in the server etc., in embodiments of the present invention to
Value with degree threshold value is without limitation.
Server may determine that whether the matching degree of two objects to be associated is greater than the matching degree threshold value of setting, if should
The matching degree of two objects to be associated is greater than matching degree threshold value, it is believed that and the correlation degree of two objects to be associated is larger,
The service function matching degree that two objects to be associated are capable of providing is higher, so that two objects to be associated be closed
Connection.If the matching degree of two objects to be associated is not more than matching degree threshold value, it is believed that the pass of two objects to be associated
Connection degree is smaller, and the service function matching degree which is capable of providing is lower, thus not to this two wait close
Connection object is associated.
The method that method in matching rule is not limited to feature extraction and similarity mode can choose other higher efficiencies
Or inefficient method replaces.The last screening numerical value of matching degree can be set according to the quantity of the card module in system
It sets and is selected between this section 50%-100%.
The various embodiments described above are illustrated by taking Fig. 2 as an example below, server is directed to object to be associated, in object to be associated
Content description information in, extract the Feature Words such as the object oriented of object to be associated, constitute the corresponding spy of different objects to be associated
Levy set of words.Server calculates the correlation degree of the corresponding feature set of words of difference object to be associated according to matching rule.Service
Correlation degree is greater than two objects to be associated of certain value by device, is associated in corresponding cloud application platform.
Due to, according to the Feature Words in the feature set of words of two objects to be associated, determined in the embodiment of the present invention this two
The matching of a object to be associated, to whether be greater than the judgement knot of matching degree threshold value according to the matching degree of two objects to be associated
Fruit, to determine whether two objects to be associated are associated.
Embodiment 4:
On the basis of the various embodiments described above, in the embodiment of the present invention, the feature according to two objects to be associated
Set of words determines that the matching degree of two objects to be associated includes:
Feature Words in the feature set of words of two objects to be associated are subjected to string matching and/or semantic scene
Match, determines the matching degree of two objects to be associated.
The Feature Words by the feature set of words of two objects to be associated carry out string matching, determine this two
The matching degree of object to be associated includes:
Feature Words in the feature set of words of two objects to be associated are subjected to string matching；
According to the quantity of matched Feature Words, the matching degree of two objects to be associated is determined.
The Feature Words by the feature set of words of two objects to be associated carry out semantic scene matching, determine this two
The matching degree of a object to be associated includes:
To in the feature set of words of two objects to be associated Feature Words carry out semantic scene division, determine this two to
The semantic scene set of affiliated partner；
By in the semantic scene set of two objects to be associated Feature Words and the semantic scene dictionary that pre-saves into
Row matching, determines the semantic scene feature set of words of two objects to be associated；
Semantic scene Feature Words in the semantic scene feature set of words of two objects to be associated are subjected to character string
Match, according to the quantity of matched semantic scene Feature Words, determines the matching degree of two objects to be associated.
Server can by the Feature Words in the feature set of words of two objects to be associated carry out string matching and/or
Semantic scene matching, to determine the matching degree of two objects to be associated, thus according to the matching degree of two objects to be associated
Determine whether to be associated with two objects to be associated.
If the Feature Words in the feature set of words of two objects to be associated are carried out string matching by server, determine
Matching degree, then server by the feature set of words of two objects to be associated Feature Words carry out string matching, according to
The quantity for the Feature Words matched determines the matching degree of two objects to be associated.
The process for carrying out string matching belongs to the prior art, does not repeat them here in embodiments of the present invention.
According to the quantity of matched Feature Words, the matching degree of two objects to be associated is determined, can be matched spy
The ratio of the total quantity of the quantity and Feature Words of sign word is determined as the matching degree of two objects to be associated, and can be will be matched
The ratio of the quantity for the Feature Words for including in the feature set of words of the quantity of Feature Words and any object to be associated be determined as this two
The matching degree etc. of a object to be associated.
If the Feature Words in the feature set of words of two objects to be associated are carried out semantic scene matching by server, really
Determine matching degree, then the Feature Words in the feature set of words of two objects to be associated are carried out semantic scene division by server, really
The semantic scene set of fixed two objects to be associated.
The process for carrying out the determining semantic scene set of semantic scene division belongs to the prior art, in the embodiment of the present invention
In do not repeat them here.
After server determines the semantic scene set of two objects to be associated, by the semantic field of two objects to be associated
Feature Words in scape are matched with the semantic scene dictionary pre-saved, if successful match, will use semantic scene word
Semantic scene Feature Words in library are replaced corresponding Feature Words in feature set of words, so that it is determined that this two to be associated right
Feature Words in feature set of words can directly be determined as by the semantic scene feature set of words of elephant if matching is unsuccessful
Semantic scene Feature Words in semantic scene feature set of words.
Semantic scene Feature Words in this two semantic scene feature set of words to be associated are carried out character string by server
Matching, according to the quantity of matched semantic scene Feature Words, determines the matched process of two objects to be associated, with above-mentioned word
The process for according with String matching is similar, and this will not be repeated here.
If the Feature Words in the feature set of words of two objects to be associated are carried out string matching and language by server
Adopted scene matching when determining the matching degree of two objects to be associated, can be the corresponding matching degree of string matching directly
Match corresponding matching degree with semantic scene and value, is determined as the matching degree of two objects to be associated, can be character
The corresponding matching degree of String matching matches corresponding matching degree with the product of corresponding the first weight pre-saved and semantic scene
Obtain with the product addition of corresponding the second weight pre-saved and value, is determined as the matching of two objects to be associated
Degree.
The embodiment of the present invention is illustrated with a specific embodiment below, as shown in Figure 3:
Cloud background management system has the function of management system object.Cloud background management system is responsible for management system object
Title, the brief introduction of object, object function description, object access link, object association other systems unique mark
Know the contents such as ID.
For example, including subsystem object and product object in the object possessed in barcode scanning cloud background management system.Wherein, often
A sub- system object provides corresponding function services.Subsystem object adds or manages user's addition, subsystem by enterprise customer
The access link of system is directed toward enterprise customer or manages the subsystem server of user, is cloud background management system access sub-system
The interface of service function.There are also the role of enterprise customer in cloud management system, enterprise customer is responsible for adding product, subsystem etc..
When enterprise customer needs to be associated with subsystem object relevant with the object when adding a product or subsystem object, in day
Corresponding function services are provided for the object in use afterwards.
When enterprise customer adds the product or subsystem object of enterprise on background management system, system is according to product
With the correlation rule of subsystem, the subsystem matched is associated with to the object automatically, enterprise customer is gone by relevant operation mode
Manage these associated subsystems.
The object that product and the mutual correlation rule of subsystem object are implemented is product object and subsystem object
Name character string, content describe character string, function describes character string, and to extract this respectively several for the method first extracted using Feature Words
Feature Words in a character string, and correspondingly constitute several feature set of words, be respectively divided the corresponding Feature Words of product and
In the corresponding feature set of words of subsystem.Then it goes to calculate between these set using the method for similarity mode and be associated to
Degree.Finally, according to numerical values recited, ranking, the service subsystem for choosing matching degree numerical value greater than certain value are recommended simultaneously from big to small
It is associated with the product object or subsystem object.
Wherein, the method that the method for similarity mode mainly uses string matching and semantic matches.Firstly, to that can be associated with
The feature set of words of object and the feature set of words that can be associated object are matched (string matching), according to successful match
Number calculates score value, obtains matching degree numerical value A.Then, according to semantic scene module, to can affiliated partner feature set of words
With can be associated object feature set of words carry out semantic scene division, then obtain can affiliated partner semantic scene word set
The semantic scene set of words of object is closed and can be associated, and uses above-mentioned matching process (string matching), calculates matching journey
Degree value B.Finally, coefficient is added according to a certain percentage respectively with B by two matched numerical value A, final matching is calculated
Degree numerical value, the calculation method that two matchings numerical value A and B obtain final matching degree numerical value in Similarity Match Method can be used
Other methods substitution.
After association, system provides the interface of management to user, and user can choose whether that these systems is needed to close automatically
The object of connection.System default user selects to need these objects.
Embodiment 5:
On the basis of the various embodiments described above, the embodiment of the invention also provides a kind of servers 400, as shown in figure 4, packet
It includes: processor 401, communication interface 402, memory 403 and communication bus 404, wherein processor 401, communication interface 402 are deposited
Reservoir 403 completes mutual communication by communication bus 404；
It is stored with computer program in the memory 403, when described program is executed by the processor 401, so that
The processor 401 executes following steps:
For each object to be associated, in the content description information of the object to be associated pre-saved, extracting should be to
The feature set of words of affiliated partner, wherein the Feature Words set is for characterizing the service function that the object to be associated is capable of providing
Feature Words set；
For every two object to be associated, according to the feature set of words of two objects to be associated, judge this two wait close
Whether the service function that connection object is capable of providing matches；If so, being associated with two objects to be associated.
Server provided in an embodiment of the present invention is specifically as follows desktop computer, server, network side equipment etc..
The communication bus that above-mentioned server is mentioned can be Peripheral Component Interconnect standard (Peripheral Component
Interconnect, PCI) bus or expanding the industrial standard structure (Extended Industry Standard
Architecture, EISA) bus etc..The communication bus can be divided into address bus, data/address bus, control bus etc..For just
It is only indicated with a thick line in expression, figure, it is not intended that an only bus or a type of bus.
Communication interface 402 is for the communication between above-mentioned server and other equipment.
Memory may include random access memory (Random Access Memory, RAM), also may include non-easy
The property lost memory (Non-Volatile Memory, NVM), for example, at least a magnetic disk storage.Optionally, memory may be used also
To be storage device that at least one is located remotely from aforementioned processor.
Above-mentioned processor can be general processor, including central processing unit, network processing unit (Network
Processor, NP) etc.；It can also be digital command processor (Digital Signal Processing, DSP), dedicated collection
At circuit, field programmable gate array or other programmable logic device, discrete gate or transistor logic, discrete hard
Part component etc..
In embodiments of the present invention, when processor executes the program stored on memory, realization, which is extracted, to be characterized wait close
The set of the Feature Words for the service function that connection object is capable of providing, then according to the feature word set of the object to be associated extracted
It closes, whether the service function for judging that certain two object to be associated is capable of providing match, when determining two object matchings to be associated
When, two objects to be associated are associated with, entire object association process does not artificially participate in, during substantially increasing affiliated partner
Accuracy and efficiency.
Embodiment 6:
On the basis of the various embodiments described above, the embodiment of the invention also provides a kind of computers to store readable storage medium
Matter is stored with the computer program that can be executed by server in the computer readable storage medium, when described program is described
When being run on server, so that the server realizes following steps when executing:
For each object to be associated, in the content description information of the object to be associated pre-saved, extracting should be to
The feature set of words of affiliated partner, wherein the Feature Words set is for characterizing the service function that the object to be associated is capable of providing
Feature Words set；
For every two object to be associated, according to the feature set of words of two objects to be associated, judge this two wait close
Whether the service function that connection object is capable of providing matches；If so, being associated with two objects to be associated.
Above-mentioned computer readable storage medium can be any usable medium that the processor in server can access or
Data storage device, including but not limited to magnetic storage such as floppy disk, hard disk, tape, magneto-optic disk (MO) etc., optical memory are such as
CD, DVD, BD, HVD etc. and semiconductor memory such as ROM, EPROM, EEPROM, nonvolatile memory (NAND
FLASH), solid state hard disk (SSD) etc..
Computer program, computer program are provided in the computer readable storage medium provided in embodiments of the present invention
When being executed by processor, the set for extracting the Feature Words for characterizing the service function that object to be associated is capable of providing is realized, then
According to the feature set of words of the object to be associated extracted, judge whether is service function that certain two object to be associated is capable of providing
Matching, when determining two object matchings to be associated, is associated with two objects to be associated, entire object association process nobody
To participate in, the accuracy and efficiency during affiliated partner is substantially increased.
Fig. 5 is a kind of 500 schematic diagram of object association means provided in an embodiment of the present invention, is applied to server, the device
Include:
Extraction module 501 is described for being directed to each object to be associated in the content of the object to be associated pre-saved
In information, the feature set of words of the object to be associated is extracted, wherein the Feature Words set is for characterizing the object energy to be associated
The set of the Feature Words of the service function enough provided；
Relating module 502, for being directed to every two object to be associated, according to the feature word set of two objects to be associated
It closes, whether the service function for judging that two objects to be associated are capable of providing matches；If so, be associated with this two it is to be associated right
As.
Each object to be associated belongs to same cloud application.
Feature Words for characterizing the service function that the object to be associated is capable of providing include at least one of the following: title spy
Levy word, type feature word, attributive character word, functional character word and performance characteristic word.
If including name feature word, type for characterizing the Feature Words for the service function that the object to be associated is capable of providing
At least one of in Feature Words and attributive character word, the extraction module 501 is specifically used for using natural language processing algorithm,
Extract the noun in the content description information；According to the noun extracted, determination can be mentioned for characterizing the object to be associated
At least one of in the name feature word of the service function of confession, type feature word and attributive character word.
It is described if including functional character word for characterizing the Feature Words for the service function that the object to be associated is capable of providing
Extraction module 501 is specifically used for using natural language processing algorithm, extracts the verb in the content description information；According to mentioning
The verb got determines the functional character word for characterizing the service function that the object to be associated is capable of providing.
It is described if including performance Feature Words for characterizing the Feature Words for the service function that the object to be associated is capable of providing
Extraction module 501 is specifically used for using natural language processing algorithm, extracts the adjective in the content description information；According to
The adjective extracted determines the performance characteristic word for characterizing the service function that the object to be associated is capable of providing.
The relating module 502, specifically for the Feature Words in the feature set of words according to two objects to be associated, really
The matching degree of fixed two objects to be associated；Judge whether the matching degree of two objects to be associated is greater than the matching degree threshold of setting
Value.
The relating module 502, specifically for carrying out the Feature Words in the feature set of words of two objects to be associated
String matching and/or semantic scene matching, determine the matching degree of two objects to be associated.
The relating module 502, specifically for carrying out the Feature Words in the feature set of words of two objects to be associated
String matching；According to the quantity of matched Feature Words, the matching degree of two objects to be associated is determined.
The relating module 502 is carried out specifically for the Feature Words in the feature set of words to two objects to be associated
Semantic scene divides, and determines the semantic scene set of two objects to be associated；By the semantic scene of two objects to be associated
Feature Words in set are matched with the semantic scene dictionary pre-saved, determine the semantic scene of two objects to be associated
Feature set of words；Semantic scene Feature Words in the semantic scene feature set of words of two objects to be associated are subjected to character string
Matching, according to the quantity of matched semantic scene Feature Words, determines the matching degree of two objects to be associated.
Server can extract the feature for characterizing the service function that object to be associated is capable of providing in the embodiment of the present invention
The set of word judges that certain two object to be associated is capable of providing then according to the feature set of words of the object to be associated extracted
Service function whether match, when determining two object matchings to be associated, be associated with two objects to be associated, entire object
Association process does not artificially participate in, and substantially increases the accuracy and efficiency during affiliated partner.
For systems/devices embodiment, since it is substantially similar to the method embodiment, so the comparison of description is simple
Single, the relevent part can refer to the partial explaination of embodiments of method.
It should be noted that, in this document, relational terms such as first and second and the like are used merely to a reality
Body or an operation are distinguished with another entity or another operation, without necessarily requiring or implying these entities
Or there are any actual relationship or orders between operation.
It should be understood by those skilled in the art that, embodiments herein can provide as method, system or computer program
Product.Therefore, complete hardware embodiment, complete software embodiment or reality combining software and hardware aspects can be used in the application
Apply the form of example.Moreover, it wherein includes the computer of computer usable program code that the application, which can be used in one or more,
The computer program implemented in usable storage medium (including but not limited to magnetic disk storage, CD-ROM, optical memory etc.) produces
The form of product.
The application is referring to method, the process of equipment (system) and computer program product according to the embodiment of the present application
Figure and/or block diagram describe.It should be understood that every one stream in flowchart and/or the block diagram can be realized by computer program instructions
The combination of process and/or box in journey and/or box and flowchart and/or the block diagram.It can provide these computer programs
Instruct the processor of general purpose computer, special purpose computer, Embedded Processor or other programmable data processing devices to produce
A raw machine, so that being generated by the instruction that computer or the processor of other programmable data processing devices execute for real
The device for the function of being specified in present one or more flows of the flowchart and/or one or more blocks of the block diagram.
These computer program instructions, which may also be stored in, is able to guide computer or other programmable data processing devices with spy
Determine in the computer-readable memory that mode works, so that it includes referring to that instruction stored in the computer readable memory, which generates,
Enable the manufacture of device, the command device realize in one box of one or more flows of the flowchart and/or block diagram or
The function of being specified in multiple boxes.
These computer program instructions also can be loaded onto a computer or other programmable data processing device, so that counting
Series of operation steps are executed on calculation machine or other programmable devices to generate computer implemented processing, thus in computer or
The instruction executed on other programmable devices is provided for realizing in one or more flows of the flowchart and/or block diagram one
The step of function of being specified in a box or multiple boxes.
Although the preferred embodiment of the application has been described, it is created once a person skilled in the art knows basic
Property concept, then additional changes and modifications can be made to these embodiments.So it includes excellent that the following claims are intended to be interpreted as
It selects embodiment and falls into all change and modification of the application range.
Obviously, various changes and modifications can be made to the invention without departing from essence of the invention by those skilled in the art
Mind and range.In this way, if these modifications and changes of the present invention belongs to the range of the claims in the present invention and its equivalent technologies
Within, then the present invention is also intended to include these modifications and variations.
Claims (22)
1. a kind of method of mapping, which is characterized in that it is applied to server, this method comprises:
It is to be associated to extract this in the content description information of the object to be associated pre-saved for each object to be associated
The feature set of words of object, wherein the Feature Words set is used to characterize the spy for the service function that the object to be associated is capable of providing
Levy the set of word；
For every two object to be associated, according to the feature set of words of two objects to be associated, judge this two it is to be associated right
As whether the service function being capable of providing matches；If so, being associated with two objects to be associated.
2. the method as described in claim 1, which is characterized in that each object to be associated belongs to same cloud application.
3. the method as described in claim 1, which is characterized in that the service function being capable of providing for characterizing the object to be associated
Feature Words include at least one of the following: that name feature word, type feature word, attributive character word, functional character word and performance are special
Levy word.
4. method as claimed in claim 3, which is characterized in that if for characterizing the service that the object to be associated is capable of providing
The Feature Words of function include at least one in name feature word, type feature word and attributive character word, described to pre-save
The object to be associated content description information in, the feature set of words for extracting the object to be associated includes:
Using natural language processing algorithm, the noun in the content description information is extracted；
According to the noun extracted, the determining name feature word for characterizing the service function that the object to be associated is capable of providing,
At least one of in type feature word and attributive character word.
5. method as claimed in claim 3, which is characterized in that if for characterizing the service that the object to be associated is capable of providing
The Feature Words of function include functional character word, described in the content description information of the object to be associated pre-saved, are extracted
The feature set of words of the object to be associated includes:
Using natural language processing algorithm, the verb in the content description information is extracted；
According to the verb extracted, the functional character word for characterizing the service function that the object to be associated is capable of providing is determined.
6. method as claimed in claim 3, which is characterized in that if for characterizing the service that the object to be associated is capable of providing
The Feature Words of function include performance Feature Words, described in the content description information of the object to be associated pre-saved, are extracted
The feature set of words of the object to be associated includes:
Using natural language processing algorithm, the adjective in the content description information is extracted；
According to the adjective extracted, the performance characteristic for characterizing the service function that the object to be associated is capable of providing is determined
Word.
7. as the method according to claim 1 to 6, which is characterized in that the feature according to two objects to be associated
Set of words, judging whether service function that two objects to be associated are capable of providing matches includes:
According to the Feature Words in the feature set of words of two objects to be associated, the matching degree of two objects to be associated is determined；
Judge whether the matching degree of two objects to be associated is greater than the matching degree threshold value of setting.
8. the method for claim 7, which is characterized in that the feature set of words according to two objects to be associated,
The matching degree for determining two objects to be associated includes:
Feature Words in the feature set of words of two objects to be associated are subjected to string matching and/or semantic scene matching,
Determine the matching degree of two objects to be associated.
9. method according to claim 8, which is characterized in that it is described will be in the feature set of words of two objects to be associated
Feature Words carry out string matching, determine that the matching degree of two objects to be associated includes:
Feature Words in the feature set of words of two objects to be associated are subjected to string matching；
According to the quantity of matched Feature Words, the matching degree of two objects to be associated is determined.
10. method according to claim 8, which is characterized in that it is described will be in the feature set of words of two objects to be associated
Feature Words carry out semantic scene matching, determine that the matching degree of two objects to be associated includes:
To in the feature set of words of two objects to be associated Feature Words carry out semantic scene division, determine this two it is to be associated
The semantic scene set of object；
By the Feature Words in the semantic scene set of two objects to be associated and the semantic scene dictionary pre-saved progress
Match, determines the semantic scene feature set of words of two objects to be associated；
Semantic scene Feature Words in the semantic scene feature set of words of two objects to be associated are subjected to string matching, root
According to the quantity of matched semantic scene Feature Words, the matching degree of two objects to be associated is determined.
11. a kind of object association means, which is characterized in that be applied to server, which includes:
Extraction module, for being directed to each object to be associated, in the content description information of the object to be associated pre-saved,
The feature set of words of the object to be associated is extracted, wherein the Feature Words set is for characterizing what the object to be associated was capable of providing
The set of the Feature Words of service function；
Relating module, for being directed to every two object to be associated, according to the feature set of words of two objects to be associated, judgement should
Whether the service function that two objects to be associated are capable of providing matches；If so, being associated with two objects to be associated.
12. device as claimed in claim 11, which is characterized in that each object to be associated belongs to same cloud application.
13. device as claimed in claim 11, which is characterized in that the service function being capable of providing for characterizing the object to be associated
The Feature Words of energy include at least one of the following: name feature word, type feature word, attributive character word, functional character word and performance
Feature Words.
14. device as claimed in claim 13, which is characterized in that if for characterizing the clothes that the object to be associated is capable of providing
Business function Feature Words include in name feature word, type feature word and attributive character word at least one of, the extraction module,
Specifically for using natural language processing algorithm, the noun in the content description information is extracted；According to the noun extracted, really
In fixed name feature word, type feature word and attributive character word for characterizing the service function that the object to be associated is capable of providing
At least one of.
15. device as claimed in claim 13, which is characterized in that if for characterizing the clothes that the object to be associated is capable of providing
The Feature Words of business function include functional character word, and the extraction module is specifically used for using natural language processing algorithm, extracts institute
State the verb in content description information；According to the verb extracted, the clothes being capable of providing for characterizing the object to be associated are determined
The functional character word for function of being engaged in.
16. device as claimed in claim 13, which is characterized in that if for characterizing the clothes that the object to be associated is capable of providing
The Feature Words of business function include performance Feature Words, and the extraction module is specifically used for using natural language processing algorithm, extracts institute
State the adjective in content description information；According to the adjective extracted, determination is capable of providing for characterizing the object to be associated
Service function performance characteristic word.
17. such as the described in any item devices of claim 11-16, which is characterized in that the relating module, being specifically used for basis should
Feature Words in the feature set of words of two objects to be associated, determine the matching degree of two objects to be associated；Judge this two
Whether the matching degree of object to be associated is greater than the matching degree threshold value of setting.
18. device as claimed in claim 17, which is characterized in that the relating module is specifically used for be associated by this two
Feature Words in the feature set of words of object carry out string matching and/or semantic scene matching, determine this two it is to be associated right
The matching degree of elephant.
19. device as claimed in claim 18, which is characterized in that the relating module is specifically used for be associated by this two
Feature Words in the feature set of words of object carry out string matching；According to the quantity of matched Feature Words, determine this two to
The matching degree of affiliated partner.
20. device as claimed in claim 18, which is characterized in that the relating module is specifically used for be associated to this two
Feature Words in the feature set of words of object carry out semantic scene division, determine the semantic scene collection of two objects to be associated
It closes；By the Feature Words in the semantic scene set of two objects to be associated and the semantic scene dictionary pre-saved progress
Match, determines the semantic scene feature set of words of two objects to be associated；By the semantic scene feature of two objects to be associated
Semantic scene Feature Words in set of words carry out string matching, and according to the quantity of matched semantic scene Feature Words, determining should
The matching degree of two objects to be associated.
21. a kind of server characterized by comprising processor, communication interface, memory and communication bus, wherein processing
Device, communication interface, memory complete mutual communication by communication bus；
It is stored with computer program in the memory, when described program is executed by the processor, so that the processor
Perform claim requires the step of any one of 1~10 the method.
22. a kind of computer readable storage medium, which is characterized in that it is stored with the computer program that can be executed by server,
When described program is run on the server, so that the server perform claim requires any one of 1~10 the method
The step of.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811409565.XA CN109543188A (en) | 2018-11-23 | 2018-11-23 | Object association method, device, server and readable storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811409565.XA CN109543188A (en) | 2018-11-23 | 2018-11-23 | Object association method, device, server and readable storage medium |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN109543188A true CN109543188A (en) | 2019-03-29 |
Family
ID=65850427
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201811409565.XA Pending CN109543188A (en) | 2018-11-23 | 2018-11-23 | Object association method, device, server and readable storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109543188A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111796830A (en) * | 2020-06-08 | 2020-10-20 | 成都数之联科技有限公司 | Protocol analysis processing method, device, equipment and medium |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103530376A (en) * | 2013-10-15 | 2014-01-22 | 北京百度网讯科技有限公司 | Method and device for providing screening conditions and searching method and device |
| CN104615605A (en) * | 2013-11-05 | 2015-05-13 | 阿里巴巴集团控股有限公司 | Method and device for predicting category of data object |
| CN106227837A (en) * | 2016-07-27 | 2016-12-14 | 浪潮（苏州）金融技术服务有限公司 | A kind of data analysing method and device |
| US20180113936A1 (en) * | 2016-10-25 | 2018-04-26 | International Business Machines Corporation | Organization for Efficient Data Analytics |
| CN108123821A (en) * | 2016-11-30 | 2018-06-05 | 华为技术有限公司 | A kind of data analysing method and device |
-
2018
- 2018-11-23 CN CN201811409565.XA patent/CN109543188A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103530376A (en) * | 2013-10-15 | 2014-01-22 | 北京百度网讯科技有限公司 | Method and device for providing screening conditions and searching method and device |
| CN104615605A (en) * | 2013-11-05 | 2015-05-13 | 阿里巴巴集团控股有限公司 | Method and device for predicting category of data object |
| CN106227837A (en) * | 2016-07-27 | 2016-12-14 | 浪潮（苏州）金融技术服务有限公司 | A kind of data analysing method and device |
| US20180113936A1 (en) * | 2016-10-25 | 2018-04-26 | International Business Machines Corporation | Organization for Efficient Data Analytics |
| CN108123821A (en) * | 2016-11-30 | 2018-06-05 | 华为技术有限公司 | A kind of data analysing method and device |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111796830A (en) * | 2020-06-08 | 2020-10-20 | 成都数之联科技有限公司 | Protocol analysis processing method, device, equipment and medium |
| CN111796830B (en) * | 2020-06-08 | 2023-09-19 | 成都数之联科技股份有限公司 | Protocol analysis processing method, device, equipment and medium |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN108322473A (en) | User behavior analysis method and apparatus | |
| WO2021169115A1 (en) | Risk control method, apparatus, electronic device, and computer-readable storage medium | |
| CN110196908A (en) | Data classification method, device, computer installation and storage medium | |
| EP2988230A1 (en) | Data processing method and computer system | |
| CN107992585A (en) | Universal tag method for digging, device, server and medium | |
| CN110598070B (en) | Application type identification method and device, server and storage medium | |
| CN113722493B (en) | Text classification data processing method, apparatus and storage medium | |
| WO2022083093A1 (en) | Probability calculation method and apparatus in graph, computer device and storage medium | |
| US11423307B2 (en) | Taxonomy construction via graph-based cross-domain knowledge transfer | |
| CN109492222A (en) | Intension recognizing method, device and computer equipment based on conceptional tree | |
| CN111080304A (en) | Credible relationship identification method, device and equipment | |
| WO2020233360A1 (en) | Method and device for generating product evaluation model | |
| CN107818491A (en) | Electronic installation, Products Show method and storage medium based on user's Internet data | |
| CN110706015B (en) | Feature selection method for advertisement click rate prediction | |
| CN109325146A (en) | A kind of video recommendation method, device, storage medium and server | |
| CN109598517A (en) | Commodity clearance processing, the processing of object and its class prediction method and apparatus | |
| CN110399499A (en) | Corpus generation method and device, electronic equipment and readable storage medium | |
| CN113011646A (en) | Data processing method and device and readable storage medium | |
| WO2023272862A1 (en) | Risk control recognition method and apparatus based on network behavior data, and electronic device and medium | |
| CN112328657A (en) | Feature derivation method, feature derivation device, computer equipment and medium | |
| CN113934851A (en) | Data enhancement method and device for text classification and electronic equipment | |
| WO2024139703A1 (en) | Object recognition model updating method and apparatus, electronic device, storage medium, and computer program product | |
| CN113190746B (en) | Recommendation model evaluation method and device and electronic equipment | |
| CN113591881A (en) | Intention recognition method and device based on model fusion, electronic equipment and medium | |
| CN109543188A (en) | Object association method, device, server and readable storage medium |
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 |
Application publication date: 20190329 |
|
| RJ01 | Rejection of invention patent application after publication |