CN104123302A - Searching method, device and system - Google Patents
Searching method, device and system Download PDFInfo
- Publication number
- CN104123302A CN104123302A CN201310152830.1A CN201310152830A CN104123302A CN 104123302 A CN104123302 A CN 104123302A CN 201310152830 A CN201310152830 A CN 201310152830A CN 104123302 A CN104123302 A CN 104123302A
- Authority
- CN
- China
- Prior art keywords
- information
- classification
- attribute
- level
- screening conditions
- 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.)
- Granted
Links
- 238000000034 method Methods 0.000 title claims abstract description 62
- 238000012216 screening Methods 0.000 claims abstract description 74
- 238000013499 data model Methods 0.000 claims abstract description 56
- 230000008569 process Effects 0.000 claims abstract description 38
- 238000003860 storage Methods 0.000 claims description 41
- 238000013475 authorization Methods 0.000 claims description 18
- 230000009471 action Effects 0.000 claims description 12
- 230000003247 decreasing effect Effects 0.000 claims description 11
- 230000002159 abnormal effect Effects 0.000 claims description 10
- 230000000694 effects Effects 0.000 description 24
- 238000013461 design Methods 0.000 description 10
- 244000141359 Malus pumila Species 0.000 description 7
- 235000011430 Malus pumila Nutrition 0.000 description 7
- 235000015103 Malus silvestris Nutrition 0.000 description 7
- 238000004519 manufacturing process Methods 0.000 description 7
- 230000002547 anomalous effect Effects 0.000 description 6
- 230000006870 function Effects 0.000 description 6
- 238000009826 distribution Methods 0.000 description 5
- 235000013305 food Nutrition 0.000 description 5
- 238000010586 diagram Methods 0.000 description 4
- 238000005516 engineering process Methods 0.000 description 4
- 230000002452 interceptive effect Effects 0.000 description 4
- 239000000463 material Substances 0.000 description 4
- 241001465754 Metazoa Species 0.000 description 3
- 230000019771 cognition Effects 0.000 description 3
- 238000011835 investigation Methods 0.000 description 3
- 238000007726 management method Methods 0.000 description 3
- 235000012054 meals Nutrition 0.000 description 3
- 238000005259 measurement Methods 0.000 description 3
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 3
- 208000030507 AIDS Diseases 0.000 description 2
- 238000004891 communication Methods 0.000 description 2
- 238000005034 decoration Methods 0.000 description 2
- 230000004069 differentiation Effects 0.000 description 2
- 230000036541 health Effects 0.000 description 2
- 230000014759 maintenance of location Effects 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 230000005180 public health Effects 0.000 description 2
- 208000010711 Cattle disease Diseases 0.000 description 1
- 206010008631 Cholera Diseases 0.000 description 1
- 208000035473 Communicable disease Diseases 0.000 description 1
- 235000007926 Craterellus fallax Nutrition 0.000 description 1
- 240000007175 Datura inoxia Species 0.000 description 1
- 241000196324 Embryophyta Species 0.000 description 1
- 206010019799 Hepatitis viral Diseases 0.000 description 1
- 201000005505 Measles Diseases 0.000 description 1
- CBENFWSGALASAD-UHFFFAOYSA-N Ozone Chemical compound [O-][O+]=O CBENFWSGALASAD-UHFFFAOYSA-N 0.000 description 1
- 244000046052 Phaseolus vulgaris Species 0.000 description 1
- 235000010627 Phaseolus vulgaris Nutrition 0.000 description 1
- 206010035148 Plague Diseases 0.000 description 1
- 208000000474 Poliomyelitis Diseases 0.000 description 1
- 244000062793 Sorghum vulgare Species 0.000 description 1
- 241000607479 Yersinia pestis Species 0.000 description 1
- 230000003044 adaptive effect Effects 0.000 description 1
- 206010064097 avian influenza Diseases 0.000 description 1
- 235000013527 bean curd Nutrition 0.000 description 1
- 230000008901 benefit Effects 0.000 description 1
- 239000008280 blood Substances 0.000 description 1
- 210000004369 blood Anatomy 0.000 description 1
- 238000009395 breeding Methods 0.000 description 1
- 230000001488 breeding effect Effects 0.000 description 1
- 239000003795 chemical substances by application Substances 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 230000008878 coupling Effects 0.000 description 1
- 238000010168 coupling process Methods 0.000 description 1
- 238000005859 coupling reaction Methods 0.000 description 1
- 238000013500 data storage Methods 0.000 description 1
- 238000012217 deletion Methods 0.000 description 1
- 230000037430 deletion Effects 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 235000013399 edible fruits Nutrition 0.000 description 1
- 238000004880 explosion Methods 0.000 description 1
- 238000001914 filtration Methods 0.000 description 1
- 208000015181 infectious disease Diseases 0.000 description 1
- 230000010365 information processing Effects 0.000 description 1
- 229910052500 inorganic mineral Inorganic materials 0.000 description 1
- 238000007689 inspection Methods 0.000 description 1
- 239000011229 interlayer Substances 0.000 description 1
- 238000012423 maintenance Methods 0.000 description 1
- 230000007246 mechanism Effects 0.000 description 1
- 235000019713 millet Nutrition 0.000 description 1
- 239000011707 mineral Substances 0.000 description 1
- 238000005065 mining Methods 0.000 description 1
- 239000000203 mixture Substances 0.000 description 1
- 230000036651 mood Effects 0.000 description 1
- 230000008520 organization Effects 0.000 description 1
- 238000013439 planning Methods 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
- 238000012797 qualification Methods 0.000 description 1
- 238000011084 recovery Methods 0.000 description 1
- 230000007115 recruitment Effects 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 238000012827 research and development Methods 0.000 description 1
- 238000013468 resource allocation Methods 0.000 description 1
- 230000033764 rhythmic process Effects 0.000 description 1
- 235000015067 sauces Nutrition 0.000 description 1
- 239000002689 soil Substances 0.000 description 1
- 239000007858 starting material Substances 0.000 description 1
- 208000011580 syndromic disease Diseases 0.000 description 1
- 230000009897 systematic effect Effects 0.000 description 1
- 238000012360 testing method Methods 0.000 description 1
- 238000012549 training Methods 0.000 description 1
- 238000013519 translation Methods 0.000 description 1
- 238000010200 validation analysis Methods 0.000 description 1
- 238000012795 verification Methods 0.000 description 1
- 239000002699 waste material Substances 0.000 description 1
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
Landscapes
- Engineering & Computer Science (AREA)
- Databases & Information Systems (AREA)
- Theoretical Computer Science (AREA)
- Data Mining & Analysis (AREA)
- Physics & Mathematics (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
Abstract
The invention provides a searching method, device and system. Users need to select class information before searching, and due to the fact that all levels of categories and types of attributes of the same information are consistent in a preset data model, the obtained class information is the same when the different users select the same needed information in the data model, and the process is the process for standardizing the users to input key words. In addition, the class information selected by the users is the key words used by a server during searching, the key words are divided into different weights, the server carries out searching in sequence according to the weights of the key words from large to small to obtain screening information meeting all screening conditions, the server can carry out searching from the maximum range to the minimum range according to the distinguishing of the weights, and therefore the obtained result is more accurate.
Description
Technical field
The present invention relates to technical field of information processing, be specifically related to a kind of search method, Apparatus and system.
Background technology
Along with the development of technology and improving constantly of the level of informatization, we are often by the information of our needs of retrieved web, be accompanied by the continuous quickening of rhythm of life, we wish to obtain more and more sooner information needed, but the method that existing information retrieval adopts keyword coupling to show more, for example: Baidu, the search engines such as Google, when retrieval, need artificially on retrieval hurdle, to input the keyword that oneself needs the things of retrieval, but because different people's knowledge level or use habit are different, keyword for same thing input in retrieval may be different, therefore the result for retrieval obtaining may have multiple, cause inquiry need to result for retrieval repeatedly be screened and be screened, labour intensity is large.
Such as: different people wants to inquire about the price of apple iphone5s, first man input apple price, second people inputs iphone5s, the 3rd people inputs the up-to-date price of apple etc. situation, the result obtaining for different keywords due to server is different, the keyword that first man obtains input obtains the present price that result for retrieval has fruit apple, the price of apple tree, the information of the various relevant apple prices of price of i Phone etc., the keyword of the second comparatively specifically can directly occur that iphone5s for information about, there is price sales situation, the information such as selling area, what the 3rd people inputted that the up-to-date price of apple obtains may have iphone4, iphone4s, iphone5, the up-to-date price of the various models such as iphone5s, therefore different people retrieves same thing due to the difference of input keyword, cause the result of output to vary.
The keyword that the user that how to standardize uses when retrieval, makes server to go retrieval according to normalized keyword, thereby obtains accurately the technical matters that retrieval person's information needed is present required solution.
Summary of the invention
The invention provides a kind of search method, Apparatus and system, for making the keyword of user's operating specification when retrieving, make server to go retrieval according to normalized keyword, thereby obtain accurately retrieval person's information needed.
To achieve these goals, the present invention adopts following technological means:
A search method, comprising:
Receive the classification information that first user is selected in preset data model, described preset data model comprises X one-level classification, each one-level classification comprises Y secondary classification, each secondary classification comprises Z three grades of classifications, the like until each M-1 level classification comprises N M level classification, each M level classification comprises each attribute classification of information, wherein by one-level classification, secondary classification ... other order of M level classification and Attribute class, the weight of each classification is successively decreased successively, described X one-level classification comprises: main information, merchandise news, action message, abnormal information and resource information, described attribute classification comprises industry industry attribute, time-space attribute, essential attribute, attribute of a relation, mutual attribute and Authorization Attributes, X wherein, Y, Z, M and N are the natural number except zero,
By the descending mode of weight of each classification, L classification in the classification information that described first user is selected be successively as the first screening conditions, the second screening conditions ... L screening conditions;
In presetting database, according to described the first screening conditions, carry out information sifting, and obtain the first filter information, in described the first filter information, according to described the second screening conditions, carry out information sifting and obtain the second filter information, the like until obtain L filter information in L-1 filter information;
Export described L filter information.
Preferably, the constructive process of described presetting database comprises:
Receive information and the belonging kinds of described information in the classifications at different levels of preset data model that the second user provides;
Obtain the storage area corresponding with described belonging kinds;
In described storage area by described information by the storage of classifying of described attribute classification.
Preferably, the constructive process of described presetting database also comprises:
Retrieval and described information-related related information in database;
Described related information and described information are carried out to association link.
Preferably, also comprise:
Receive the association link that user clicks;
The related information being associated with described information according to described association link output.
An indexing unit, comprising:
The first receiving element, for receiving the classification information that first user is selected at preset data model, described preset data model comprises X one-level classification, each one-level classification comprises Y secondary classification, each secondary classification comprises Z three grades of classifications, the like until each M-1 level classification comprises N M level classification, each M level classification comprises each attribute classification of information, wherein by one-level classification, secondary classification ... other order of M level classification and Attribute class, the weight of each classification is successively decreased successively, described X one-level classification comprises: main information, merchandise news, action message, abnormal information and resource information, described attribute classification comprises industry industry attribute, time-space attribute, essential attribute, attribute of a relation, mutual attribute and Authorization Attributes, X wherein, Y, Z, M and N are the natural number except zero,
Acquisition condition unit, for by the descending mode of weight of each classification, in the classification information that described first user is selected L classification successively as the first screening conditions, the second screening conditions ... L screening conditions;
Screening unit, for carrying out information sifting in presetting database according to described the first screening conditions, and obtain the first filter information, in described the first filter information, according to described the second screening conditions, carry out information sifting and obtain the second filter information, the like until obtain L filter information in L-1 filter information;
Output unit, for exporting described L filter information.
Preferably, also comprise:
The second receiving element, for receiving information that the second user provides and described information at the belonging kinds of the classifications at different levels of preset data model;
Acquiring unit, for obtaining the storage area corresponding with described belonging kinds;
Storage unit, at described storage area by described information by the storage of classifying of described attribute classification.
Preferably, also comprise:
Search unit, for retrieving and described information-related related information at database;
Associative cell, for carrying out association link by described related information and described information.
Preferably, also comprise:
Related information output unit, the association link of clicking for receiving described first user, the related information being associated with described information according to described association link output.
A searching system, comprising:
Server, for receiving the classification information that first user is selected at preset data model, described preset data model comprises X one-level classification, each one-level classification comprises Y secondary classification, each secondary classification comprises Z three grades of classifications, the like until each M-1 level classification comprises N M level classification, each M level classification comprises each attribute classification of information, wherein by one-level classification, secondary classification ... other order of M level classification and Attribute class, the weight of each classification is successively decreased successively, described X one-level classification comprises: main information, merchandise news, action message, abnormal information and resource information, described attribute classification comprises industry industry attribute, time-space attribute, essential attribute, attribute of a relation, mutual attribute and Authorization Attributes, X wherein, Y, Z, M and N are the natural number except zero, by the descending mode of weight of each classification, in the classification information that described first user is selected, L classification is successively as the first screening conditions, the second screening conditions ... L screening conditions, in presetting database, according to described the first screening conditions, carry out information sifting, and obtain the first filter information, in described the first filter information, according to described the second screening conditions, carry out information sifting and obtain the second filter information, the like until obtain L filter information in L-1 filter information, export described L filter information,
Display, for showing the described information that meets described screening conditions.
In the present invention, user needed to select classification information before search, be classifications at different levels and/or attribute classification, this process is the process that standard user inputs keyword, because same information classifications at different levels in preset data model are consistent with attribute classification, therefore the classification information (classifications at different levels and attribute classification) that different users obtains when the information needed for same is selected in data model is also the same, therefore by user, in the process of preset data Model Selection classification information (classifications at different levels and attribute classification), realized the object that the user that standardizes inputs keyword.
In addition, the keyword using when the classification information that in the present invention, user selects is server search, keyword in the present invention is divided into different weights, server retrieves according to the descending order of the weight of keyword the filter information that is met all screening conditions successively, because the weight of keyword is according to one-level classification secondary classification ... the classification of M level is successively decreased, and the scope of a subseries is greater than secondary classification and is greater than reclassify ... be greater than the classification of M level, because server screens for the proportion of screening conditions, therefore the differentiation by weight can realize the search to minimum zone by maximum magnitude, and then make the result that obtains more accurate.
Accompanying drawing explanation
In order to be illustrated more clearly in the embodiment of the present invention or technical scheme of the prior art, to the accompanying drawing of required use in embodiment or description of the Prior Art be briefly described below, apparently, accompanying drawing in the following describes is only some embodiments of the present invention, for those of ordinary skills, do not paying under the prerequisite of creative work, can also obtain according to these accompanying drawings other accompanying drawing.
Fig. 1 is the process flow diagram of the disclosed search method of figure embodiment of the present invention;
Fig. 2 is the process flow diagram of presetting database constructive process in the disclosed search method of the embodiment of the present invention;
Fig. 3 is the process flow diagram that the embodiment of the present invention discloses presetting database constructive process in another search method;
Fig. 4 is the process flow diagram of the disclosed another search method of the embodiment of the present invention;
Fig. 5 is the structural representation of the disclosed indexing unit of the embodiment of the present invention;
Fig. 6 is the structural representation of the disclosed another indexing unit of the embodiment of the present invention;
Fig. 7 is the structural representation of the disclosed another indexing unit of the embodiment of the present invention;
Fig. 8 is the structural representation of the disclosed searching system of the embodiment of the present invention.
Embodiment
Below in conjunction with the accompanying drawing in the embodiment of the present invention, the technical scheme in the embodiment of the present invention is clearly and completely described, obviously, described embodiment is only the present invention's part embodiment, rather than whole embodiment.Embodiment based in the present invention, those of ordinary skills, not making the every other embodiment obtaining under creative work prerequisite, belong to the scope of protection of the invention.
As shown in Figure 1, the invention provides a kind of search method, comprising:
Step S101: receive the classification information that first user is selected in preset data model, described preset data model comprises X one-level classification, each one-level classification comprises Y secondary classification, each secondary classification comprises Z three grades of classifications, the like until each M-1 level classification comprises N M level classification, each M level classification comprises each attribute classification of information, wherein by one-level classification, secondary classification ... other order of M level classification and Attribute class, the weight of each classification is successively decreased successively, described X one-level classification comprises: main information, merchandise news, action message, abnormal information and resource information, described attribute classification comprises industry industry attribute, time-space attribute, essential attribute, attribute of a relation, mutual attribute and Authorization Attributes, X wherein, Y, Z, M and N are the natural number except zero,
Default data model is a complete classification of real things, existing thing is divided into X one-level classification on the whole, comprise X main direction, mainly comprise main information, merchandise news, action message, abnormal information and resource information, main information also comprises organizational information and personal information, merchandise news also comprises products & services information, the quantity of X can be along with the cognition of real things is carried out to adaptive increase, each one-level classification comprises Y secondary classification, secondary classification is lower floor's rank of one-level classification, three grades of lower floor's ranks that classification is secondary classification, the like until M level classification, M level classification is according to the bottom classification that can not classify again to the cognition of real things, as from the foregoing, default data model can be seen as the disaggregated model of tree structure.
But in the default data model in the present invention, the weight of each classification is different, concrete, each classification is along with the increase weight of M is less, the larger classification that represents the bottom of M, M is less represents top classification, and top classification weight is larger, and bottom classification weight is minimum.Object so classification and difference weight size, according to the difference of weight, to distinguish the position of each classification when facilitating subsequent searches, and determine database is searched for time screening conditions order, this partial content is elaborated in following step.
The present invention, before retrieving, needs to set up the database of storage first user information needed, and the constructive process of presetting database, as shown in Figure 2, comprising:
Step S201: receive information and the belonging kinds of described information in the classifications at different levels of described preset data model that the second user provides.
First need to set up a database corresponding with default data model, the class models that wherein preset data model is tree structure, according to default data model, Database X one-level, identify as X one-level classification, under each one-level sign, set up Y secondary sign as secondary classification, under each secondary sign, set up Z three grades of signs as three grades of classifications, the like until set up N M level classification under each M-1 level classification, in database, claim that the M of the bottom and classification are belonging kinds.
Each attribute classification that also comprises information in M level classification, in like manner each attribute classification also also has corresponding with it identification information in database, in database, set up the storage area corresponding with each belonging kinds (or each home identity), belonging kinds comprises the attribute classification of information, attribute classification at least comprises industry industry attribute, time-space attribute, essential attribute, attribute of a relation, mutual attribute and Authorization Attributes, corresponding each attribute has corresponding with it storage area, each storage area is for storing the attribute information corresponding with information, said process is the process of preliminary building database framework, following content is stored to database by describing the information how the second user being provided.
The second user is according to the information providing, by information according to one-level classification---secondary classification---three grades of classifications ... the order of M level classification, at preset data model, select finally to determine information M level classification and the belonging kinds of information that such another name is provided for the second user.
Data model is the general frame of database, the information that user provides is the content in framework, the process that information is stored in database according to the classification of data model is the process of horn of plenty database, information is the information that the second user provides, first the second user need artificial according to the classifications at different levels under each classification judgement information of data model until the final belonging kinds of information, be one-level classification-secondary classification ... to belonging kinds, user's classification information at different levels are inputed in database.
The object of this preset model for can both find corresponding belonging kinds by the various things in real world in preset data model provided by the invention.Classifications at different levels in the present invention and other quantity of Attribute class can be along with can else carrying out adaptability revision to the quantity of classifications at different levels and Attribute class to the cognition of things, so the present invention does not limit quantity and the title of the classification of the quantity of one-level classification, lower floor's classification and quantity and attribute information.
Step S202: obtain the storage area corresponding with described belonging kinds;
Database receives the classifications at different levels about information that the second user provides, and classifications at different levels are converted into identification information: one-level sign, secondary sign ... M level sign, home identity, and according to one-level sign, secondary sign ... the order of M level sign, home identity obtains home identity, and in database, find the storage area corresponding with home identity, thereby obtain the storage area corresponding with belonging kinds.
Step S203: in described storage area by described information by the storage of classifying of described attribute classification.
Receive the information that the second user provides, and in the storage area corresponding with belonging kinds, obtain and other storage area of each Attribute class in database, the information that user provides according to self, information classification is filled in the storage area of different attribute classification, database receives the information that user provides in storage area corresponding to each attribute classification, and it is stored in corresponding data storage areas according to corresponding attribute-bit.
Repeatedly carry out above process, a plurality of information that the second user can be provided are stored in database, the presetting database of the database after storage information in retrieving of the present invention.
Step S102: by the descending mode of weight of each classification, L classification in the classification information that described first user is selected is successively as the first screening conditions, the second screening conditions ... L screening conditions, are about to described classification information as screening conditions;
The classification information that first user is selected in preset data model, if first user is selected L classification in preset data model, according to the weight of each classification in preset data model, L the category classification that first user is selected given different weights, according to the descending order of weight successively using L classification as the first screening conditions, the second screening conditions ... L screening conditions.
This step is main inventive point of the present invention, according to the difference of weight, keyword is divided into different weights, and unlike in prior art, the weight of each keyword is all the same, and the result therefore searching out is by each area of industry-by-industry, and information is comparatively numerous and diverse inaccurate.In the present invention, keyword is divided into different weights, when making search, in database, first carry out the selection of highest level type, select the type of this information, then progressively refinement, until minimum classification, make the information that search obtains through method of the present invention more accurate, meet user's demand, avoided user in numerous and diverse information, to carry out the process of binary search.
Step S103: carry out information sifting according to described the first screening conditions in presetting database, and obtain the first filter information, in described the first filter information, according to described the second screening conditions, carry out information sifting and obtain the second filter information, the like until obtain L filter information in L-1 filter information, in database, carry out information sifting;
In database, according to the first screening conditions, carry out information sifting, and obtain the first filter information, next screening conditions are also the screenings again of carrying out on the basis of upper once filter information, therefore the L filter information finally obtaining, the final result having obtained for carried out L level screening in database.This result is the information that meets user's screening conditions.
Step S104: export described L filter information, i.e. output meets the information of described screening conditions.
In the storage area finally obtaining in above-mentioned steps, obtain information needed, and information needed is exported, to show by display, the information of weight maximum is placed to the foremost of viewing area when showing on server or host computer.In the present invention, user needed to select classification information before search, be classifications at different levels and/or attribute classification, this process is the process that standard user inputs keyword, because same information classifications at different levels in preset data model are consistent with attribute classification, therefore the classification information (classifications at different levels and attribute classification) that different users obtains when the information needed for same is selected in data model is also the same, therefore by user, in the process of preset data Model Selection classification information (classifications at different levels and attribute classification), realized the object that the user that standardizes inputs keyword.
In addition, the keyword using when the classification information that in the present invention, user selects is server search, keyword in the present invention is divided into different weights, server retrieves according to the descending order of the weight of keyword the filter information that is met all screening conditions successively, because the weight of keyword is according to one-level classification secondary classification ... the classification of M level is successively decreased, and the scope of a subseries is greater than secondary classification and is greater than reclassify ... be greater than the classification of M level, because server screens for the proportion of screening conditions, therefore the differentiation by weight can realize the search to minimum zone by maximum magnitude, and then make the result that obtains more accurate.Following the present embodiment will be introduced the content of relevant data model in detail.
Data model comprises that each level classification will describe each level classification once in detail:
One-level main classes is other: main information, merchandise news, action message, anomalous event and resource information.
Main information: be mainly organizational information and personal information, also can be general things, merchandise news: be divided into product information and information on services.
The secondary classification of tissue comprises industry and industry;
Three grades of classifications of tissue:
Lower floor's classification of industry: traffic, food and drink, amusement, leisure, tourism, lodging, house property property, shopping and market, construction and decoration, health care, financial instrument, government affairs, public utilities, education, human resources, service for life, commerce services, style, medium, information industry, scientific research technology, breeding and planting, mining industry, manufacturing industry, mass organizations, other etc.;
Lower floor's classification of industry: A (information+wisdom+standard), B (consulting+debugging+test+screening), C build, D (supporting+complete), E(design+research and development), F (manufacturing+consume provides), G (tissue+management+supervision), H (training+cultivation), I (beautify+pack), J (marketing+agency+transaction), K (lease+debt-credit), L (storage+transportation+record), M operation support, N (treat+prevent+maintain+protect), O (recovery+disposal), P other etc.;
When determining each level classification of tissue, first choose a trade and then select industry, thereby determined the category attribute of tissue; For example: each level classification process of determining Yi Ge website design company is that selection " information industry/internet " first in the industry is then located " E ", then selected " design " in E class in industry; These three grades of attributes are with regard to each level classification of clear and definite location Liao Gai website design company.This because not only embodied the relation that also embodies Liao Gai website company and industry with the relation of industry in the present invention, therefore more accurately determines the related information of Liao Gai website design company from generally that design corporation's classification is different in commerce services at present.
Individual's secondary classification comprises industry, industry and occupation.
Three grades of classifications of industry and industry, as above-mentioned, repeat no more;
Three grades of classifications of occupation: sell, customer service, skilled worker/workman, general work, foreground, Admin Staff, driver, security personnel, civilian, translation, courier, merchandiser, salesman, shopping guide, storekeeper, purchasing agent, waiter, cashier, cook, cut allotment of labor, keep a public place clean, nurse/nurse, millet cake teacher, bartender, accounting, cashier, gaffer, dishwasher, teacher, shopkeeper, machinery/instrument, decoration design, webmaster project, manager, editor/publication, estate management, technical support, the fine arts/design, market/public relations etc.
When determining each level classification of individual, first choose a trade, then select industry, then choose a profession, three grades of classifications bind together, and are exactly each level classification of individual; For example: the accounting of Yi Ge website design company determines that first each level classification chooses a trade " information industry/internet ", then selects industry " E ", then selects " design ", then choose a profession " accounting " thus determine each level classification of individual.
The secondary classification of product information and information on services: industry and industry.
Movable secondary classification: levy the activity of seeking, in partnership, investigation activity ... social activities etc.
Levy and seek movable three grades of classifications and comprise: marriage-seeking, conscription, contributions, question and answer game, missing, look for something, recruit, wanted circular, recruitment drive, Articles found, owner please contact, recall, promote trade and investment, join (agency, intermediary, distribution, chain), bring in funds, introduce technology, other ...
Three grades of classifications in partnership comprise: share, manage jointly, spell room, share-car, spelling drink, spell meal, spell song, spell trip, spell play, spell chat, spell learn, spell with, spelling, spelling purchase, spell motion, joining-card, other.
Investigation activity three and classification comprise: investigate, inspect, investigation (market survey, survey, ballot activity), study, prove, investigate secretly, other ...
Social activities: community activity, public welfare activities, charitable activity, donations activity, the activity of visiting underprivileged homes, commemorative activity, volunteer are movable, other ...
Restriction is just enumerated having made partly of classification as space is limited, in the specific implementation can be different classes of according to different activity characteristic selections, according to concrete class, can infinitely segment.
Anomalous event secondary classification: public accident, disaster event ... industrial and commercial event etc.
Three grades of classifications of public accident comprise public service event, public health event and occurred events of public safety.
The level Four classification of public service event: cut off the water, have a power failure, stop the supple of gas or steam, stop heat, communication disconnection, broadcasting and TV and break ...
The level Four classification of public health event: infectious disease SARS, bird flu, mad cattle disease, acquired immune deficiency syndrome (AIDS), the plague, cholera, virus hepatitis, polio, measles ...
Three grades of classifications of disaster event: earthquake, tsunami, storm wind (wind spout), heavy rain, sandstorm, arid, severe snow, thunder and lightning, sudden-heat, flood, rubble flow, landslide, volcanic explosion, solar windstorm, ozone black hole ...
Three grades of classifications of industrial and commercial event: unlicensed business activity, unreal advertisement, super scope operation, close down place, antitrust, illegitimate competition, combat bribery in busines, the smuggling and distribution of smuggled goods ...
Different classes of according to the characteristic selection of different anomalous events, according to concrete class, can infinitely segment;
The secondary classification of resource is as follows: place resource, material resources, natural resources ...
Three grades of classifications of place resource: facility, equipment, instrument, starting material, waste and old material ...
Three grades of classifications of material resources: human resources, animal power resource, financial resource, equity, credits, option, power resource administration license (card for operating, the pass) ...
Three grades of classifications of natural resources: mineral wealth, Animal resources, plant resources, biology, water resource, climate resources, soil, place ...
The resource characteristics that wherein foundation is different is selected different classes of, according to concrete class, can infinitely segment, for example:
Wherein place can also classification be: planning region, special-purpose place
Administrative area: country, provinces, cities and autonomous regions, cities and counties, cities and counties, district, Jie Zhen, village community, sector ...
Functional areas: residential quarter, community, village, village, holiday village ...
Circuit urban road, highway, railway, path, water route, airline, sail line, space line, other particular course ...
Special-purpose place: platform (bus station, bus station, railway station, harbour, safety check station, border inspection station, depot, workstation, freeway toll station, traffic toll gate, law enforcement station, medical station ...); Critical point (harbour, pass), field, garden, palace, altar, building, hall, the Room, shop, institute, room, field, chamber, booth, shop ...
With this, set up the base class of main body, commodity, activity, anomalous event and resource, for creating, show, inquiring about, set up information framework.By each level attributes step by step within lower minute, obtain final belonging kinds, and under belonging kinds, set up attribute classification, will describe other classification of Attribute class below in detail.
Other one-level classification of Attribute class: time-space attribute, attribute of a relation, mutual attribute and Authorization Attributes and essential attribute, the time-space attribute of each classification, attribute of a relation, mutual attribute and Authorization Attributes are done to same description below, essential attribute is done separately and is introduced.
Time-space attribute secondary classification: time attribute and address properties;
Time attribute, the time uses general list below to describe:
Field comprise title, time type (time point, period, duration), geochron/dynasty information, time-zone information, time reference dot information (Christian era, present, self-defined), time orientation information (forward and backward), time numerical value, time counting unit, time measurement unit (year, month, day, hour, min, second, delicate, millisecond), repeat rule (only once, by day, by week, monthly, quarterly, by ten days, per year) and then the versatility description of time of forming.
Address properties divides place, location and region, and field comprises:
The whole world/country/province/city ()/county (district)/street (town)/village (society)/team (community)/Lou Dong/unit/floor/room number/interlayer/subregion/row/number/wait to describe; It should be noted that address can infinitely segment according to actual conditions;
Attribute of a relation: bean vermicelli, pay close attention to, credit list (blacklist, bad, good), classmate, friend, household, colleague, teachers and students, fellow villager, neighbours, business relation (supplier, client, rival, co-worker), administration is subordinate to external relations (higher level, at the same level, subordinate), internal relations (buying, sell, logistics, finance etc.), social circle's (sector coil, industry circle, geographical circle, blood relationship circle, god's edge circle, literary composition edge circle, love circle, experience circle, interest circle etc.) ...,
Mutual attribute: minute social and business's friendship
Social attribute comprises: make a speech, comment on, criticize, pay close attention to, like, make a suggestion, give advice, think, leave a message, complain, praise etc.;
Business hands over attribute to comprise: demand, register, be shortlisted for, supply, market, alternately, transaction, revenue and expenditure, subscription etc.;
Authorization Attributes:
Should comprise field: power kind (weigh: access, register, issue, report to the police, notify, comment on by supply; Demand power: check, download, register, subscribe, buy; Cooperation power: agency, distribution, propagation, advertisement, administrative power: modification, deletion, establishment, undercarriage, control etc.), Permission Levels, authorization object, verification mode, authorising conditional ...
Being more than the total attribute of each classification information, is below the essential attribute (doing independent description) of each classification information:
Organization field comprises: registration code, login name, informant, trade mark, management place, contact details, industrial and commercial registration information, location, individualized signature, operation history, tissue are introduced (scale, honor qualification, the chronicle of events, resource, case, mechanism's setting, theory, culture, environment, characteristic, business), public's impression, business stage, real-time business status, property tax information etc.
Individual's field comprises: registration code, login name, the pet name, communication information, ID (identity number) card information, relative address (native place, place of working, residence, life ground, fallow land, in real time etc.), nationality, birthday, division of life span, real-time status (mood, health), occupation, academic title, position, faith, a family, resume, personal information product, constellation.Symbolic animal of the birth year, income, marital status, hobby, taboo, brief introduction, give people's impression etc.
Product field comprises: registration code, login name, informant, brand, model, classification, making pattern, production life cycle, location, specific, form, grade, process introduction, parameter index, authentication information, brief introduction, style, applicable object, effect, use notice, shelf-life, relevant important persons, scale, method of supplying, supply quantity, supply time, the place of production, date of manufacture, lot number, string number, size, quality, color, pattern, measurement unit, stock, supply of material state, shipping requirement, accumulating information, pricing information, mode of doing business, marketing sign, order condition, exchange of value mode, shift to an earlier date the ticket reserving time, retention time, amount on order restriction, clause etc. after sale.
Service field comprises: registration code, login name, informant, brand, model, classification, life cycle, location, service ability, resource is supporting, characteristic, purposes effect, flow process is introduced, notice, grade, authentication information, brief introduction, adequate and systematic service, presentation mode, supply quantity, supply time, obligate information, supply status, measurement unit, suitable object, shift to an earlier date the ticket reserving time, retention time, pricing information, mode of doing business, marketing sign, restricted number, order condition, exchange of value mode, consumption notice, after sale service etc.
Action field comprises: registration code, login name, informant, the class of activity, participation mode, rank, scale, participation method, quantity and distribution, activity object, activity context, correlative charges, organizer and resource, hold time, host place, contact person, schedule and responsible official, requirement and restriction, power and responsibility, policy of rewards, financial policy, stage, real-time status, registration and competition, summary, details, points for attention etc.;
Anomalous event field comprises: registration code, login name, informant, the relation to event, troublemaker, accident treatment people, resource allocation and support, kind, event stage, the phase of impact, event level, event details, influenced object, reply and disposal, result and summary, relevant place, stage, real-time status, bring out event, recover with reconstruction etc.;
Resources field comprises: login name, login name, informant, classification, right (entitlement, administrative power, the right to use) people, right disposal, the right term of validity, maintenance information, stage, real-time status, archives and deed, brief introduction, residual value, access warrant and the term of validity, storing place, be subordinate to, from product, output product etc.
In resource, place field comprises: resource, area, location, advantage, brief introduction, archives deed, address (place, route, region, Virtual Space), distribution plan, right and disposal, near terrestrial reference, complete sets of basic equipment, traffic and communal facility, environment periphery, stage, real-time status etc. in registration code, login name, informant, classification, law warrant, applicable industry, district.
Above content describes the situation of data model in detail, below by the process by data model building database.
As shown in Figure 3, the present embodiment provides the process of establishing method of presetting database, comprising:
Step S301: receive information and the belonging kinds of described information in the classifications at different levels of preset data model that the second user provides;
Step S302: obtain the storage area corresponding with described belonging kinds;
Step S303: in described storage area by described information by the storage of classifying of described attribute classification.
Step S304: obtain and described information-related related information;
In the existing information of database, obtain the related information with described information, and obtain the identification information of each level classification of its related information, or outside database, obtain the related information with described information association, and by the related information obtaining outside database, process according to step S301-S303 is stored in database, and obtains the identification information of each level classification of related information.
Step S305: described related information and described information are carried out to association link.
Content at storage area corresponding to the attribute classification of described information, such as the second user provides information, it is film news briefing, the one-level classification that this information belongs to is for movable, secondary classification is media, three grades of classifications are news conference, in the essential attribute of this news conference, there is " activity object ", " activity object " and " Titanic " film are connected, concrete connects " activity object " and each rank identification information described in " Titanic " film, finally link to the storage area of the attribute information of film, make first user can jump to the interested content of user place by this link.
More than describe the process of establishing of database in detail, will introduce in detail the process of carrying out multidimensional search according to this database below.
As shown in Figure 4, the invention provides a kind of search method, comprising:
Step S401: set up multidimensional axle according to preset data model;
Multidimensional axle is each classification in preset data model, also comprises the identification information of each classification in multidimensional axle.
X-axis: one-level classification
X1: main body:
X1-1: tissue
X1-1-1: food and drink, X1-1-2: amusement, X1-1-3: leisure etc.
X1-2: individual
X1-2-1: accounting, X1-2-2: cashier, X1-2-3: sell etc.
X2: commodity
X2-1: product,
X2-1-1: food and drink
X2-1-1-1: Chinese meal
X2-1-1-1: stirfried bean curd in hot sauce
X2-1-2: amusement, X2-1-3: leisure etc.
X2-2: service
X2-2-1: food and drink, X2-2-2: amusement, X2-2-3: leisure etc.
X3: activity
X3-1: rally, X3-2: marketing, X3-3: promote trade and investment etc.
X4: anomalous event
X4-1: traffic hazard, X4-2: natural event, X4-3: business event etc.
X5: resource
X5-1: place, X5-2: tissue, X5-3: equipment etc.
Y-axis: industry axle
Y1: food and drink
Y1-1: Chinese meal
Z axis: time shaft
Z1: time value
Z1-1: year
Z1-1-1: month
Z1-1-1-1: day
Z1-1-1-1-1: time
Z1-1-1-1-1-1: minute
U axle: address axle
U1: China
U1-1: Sichuan
U1-1-1: Chengdu
U1-1-1-1: Wuhou District
U1-1-1-1-1: mill bridge
A axle: be related to axle
A1: business hands over
B axle: essential axle
B9: presentation mode
B9-2: deliver goods to the customers
C axle: mutual axle
C1: demand
D axle: authority axle
D1: power kind
D1-1: purchase right
Step S402: first user login retrieval platform is confirmed identity;
The platform of first user login retrieval, and confirm user identity by account information.
Step S403: the classifications at different levels of selecting expectation affairs by multidimensional axle;
Different attribute by industry, industry, time, place, affairs itself carries out conditional filtering, in no particular order, freely screens;
Step S404: using described classifications at different levels and described attribute classification as screening conditions;
Information axle is the condition entry of upper level, and each information field is the condition entry of next stage, and condition in no particular order.
Step S405: carry out information sifting according to described screening conditions in presetting database;
In database, screening meets the information of each information axle condition, the information of satisfying condition is to the affairs of expectation.
Step S406: output meets the expectation affairs of described screening conditions;
Step S407: judge registrant's interactive function of whether having the right to use by Authorization Attributes;
Possible the interactive function that provides of affairs of expectation: social, business's friendship, judges registrant's interactive function of whether having the right to use according to Authorization Attributes.
For example, it is business status collector that a certain company provides a kind of product, wish this production marketing (business hands over function) to go out, but the said firm does not wish to sell to the client of all regions, only want business status collector to be sold to the commission merchant of In Chengdu, the said firm is therefore when uploading sale business collector to server, when setting up Authorization Attributes, set authority: In Chengdu+commission merchant's (attribute of a relation), after information is published out, a certain individual wants to buy business status collector, system judgement the other side identity (is generally first to login platform, platform judges identity according to user name), see that object is whether in authorising conditional: whether the client who is whether In Chengdu is commission merchant, if, this client just can buy business status collector so, if not in authorization object, to show: " you also do not obtain the purchase mandate of business status collector ", system will stop this client's process of purchase.
Step S408: realize relevant issues or business after authorizing.
If consumer has the right to use interactive function, server can be to first user mandate, so that first user is realized relevant issues or business.
For example: consumer's first need to be bought these affairs of computer, first login system, its identity of system validation is first, select commodity one-level classification information, then select information industry, then select computer industry, select computer, can select supply time 2013-3-8, Chengdu, place mill bridge simultaneously, then select essential attribute, brand association, price 3000-5000, then selects to deliver goods to the customers etc., mutual attribute is to buy during business hands over, system judges whether first has purchase right, if passed through, carries out purchase business: place an order, pay the bill, receive etc.So just realized first by the corresponding brand of time, place, purchase, the expected price of his expectation, and commodity presentation mode commodity have been bought.
Described embodiment has realized an affairs inquiry and associated process, by attribute item, carries out association and screening, has realized and having searched and business realizing, sets up common template and the processing procedure of real affairs, realizes interconnection, has promoted service efficiency.
In the present invention, user selected classifications at different levels and other process of Attribute class before search, be the process that standard user inputs keyword, because same information classification in preset data model is consistent with attribute information, therefore the classifications at different levels that different users obtains when the information needed for same is selected in data model are also the same with attribute classification, therefore by user, in preset data Model Selection classifications at different levels and other process of Attribute class, have realized the object that the user that standardizes inputs keyword.
In addition the present invention carries out keyword search at different categories to information needed by classifications at different levels and attribute classification, different categories are various dimensions, therefore the present invention has realized information needed has been carried out to various dimensions retrieval, server is retrieved and is obtained information needed under the cooperation of various dimensions keyword, in prior art, substantially by a kind of or a class keywords, search for, the result obtaining is more numerous and diverse inaccurate, it is more accurate that the present invention retrieves by various dimensions the result obtaining, and the information needed that therefore the present invention is obtained is more accurate.Therefore the present invention has realized the keyword that standardization user uses when retrieval, makes server to go retrieval according to normalized keyword, thereby obtains accurately retrieval person's information needed.
As shown in Figure 5, the present invention also provides a kind of indexing unit, comprising:
The first receiving element 100, for receiving the classification information that first user is selected at preset data model, described preset data model comprises X one-level classification, each one-level classification comprises Y secondary classification, each secondary classification comprises Z three grades of classifications, the like until each M-1 level classification comprises N M level classification, each M level classification comprises each attribute classification of information, wherein by one-level classification, secondary classification ... other order of M level classification and Attribute class, the weight of each classification is successively decreased successively, described X one-level classification comprises: main information, merchandise news, action message, abnormal information and resource information, described attribute classification comprises industry industry attribute, time-space attribute, essential attribute, attribute of a relation, mutual attribute and Authorization Attributes, X wherein, Y, Z, M and N are the natural number except zero,
Acquisition condition unit 200, for by the descending mode of weight of each classification, in the classification information that described first user is selected L classification successively as the first screening conditions, the second screening conditions ... L screening conditions;
Screening unit 300, for carrying out information sifting in presetting database according to described the first screening conditions, and obtain the first filter information, in described the first filter information, according to described the second screening conditions, carry out information sifting and obtain the second filter information, the like until obtain L filter information in L-1 filter information;
Output unit 400, for exporting described L filter information.
As shown in Figure 6, described device also comprises:
The second receiving element 500, for receiving information that the second user provides and described information at the belonging kinds of the classifications at different levels of preset data model;
Acquiring unit 600, for obtaining the storage area corresponding with described belonging kinds;
Storage unit 700, at described storage area by described information by the storage of classifying of described attribute classification.
As shown in Figure 7, described device also comprises:
Search unit 800, for database retrieval by with described information-related related information;
Associative cell 900, for carrying out association link by described related information and described information.
As shown in Figure 7, described device also comprises:
Related information output unit 1000, the association link of clicking for receiving first user, the related information being associated with described information according to described association link output.
As shown in Figure 8, the present invention also provides a kind of searching system, comprising:
Server 1100, for receiving the classification information that first user is selected at preset data model, described preset data model comprises X one-level classification, each one-level classification comprises Y secondary classification, each secondary classification comprises Z three grades of classifications, the like until each M-1 level classification comprises N M level classification, each M level classification comprises each attribute classification of information, wherein by one-level classification, secondary classification ... other order of M level classification and Attribute class, the weight of each classification is successively decreased successively, described X one-level classification comprises: main information, merchandise news, action message, abnormal information and resource information, described attribute classification comprises industry industry attribute, time-space attribute, essential attribute, attribute of a relation, mutual attribute and Authorization Attributes, X wherein, Y, Z, M and N are the natural number except zero, by the descending mode of weight of each classification, in the classification information that described first user is selected, L classification is successively as the first screening conditions, the second screening conditions ... L screening conditions, in presetting database, according to described the first screening conditions, carry out information sifting, and obtain the first filter information, in described the first filter information, according to described the second screening conditions, carry out information sifting and obtain the second filter information, the like until obtain L filter information in L-1 filter information, export described L filter information,
Display 1200, for showing the described information that meets described screening conditions.
If the function described in the present embodiment method usings that the form of SFU software functional unit realizes and during as production marketing independently or use, can be stored in a computing equipment read/write memory medium.Understanding based on such, the part that the embodiment of the present invention contributes to prior art or the part of this technical scheme can embody with the form of software product, this software product is stored in a storage medium, comprise that some instructions are with so that a computing equipment (can be personal computer, server, mobile computing device or the network equipment etc.) carry out all or part of step of method described in each embodiment of the present invention.And aforesaid storage medium comprises: various media that can be program code stored such as USB flash disk, portable hard drive, ROM (read-only memory) (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), magnetic disc or CDs.
In this instructions, each embodiment adopts the mode of going forward one by one to describe, and each embodiment stresses is the difference with other embodiment, between each embodiment same or similar part mutually referring to.
Above-mentioned explanation to the disclosed embodiments, makes professional and technical personnel in the field can realize or use the present invention.To the multiple modification of these embodiment, will be apparent for those skilled in the art, General Principle as defined herein can, in the situation that not departing from the spirit or scope of the present invention, realize in other embodiments.Therefore, the present invention will can not be restricted to these embodiment shown in this article, but will meet the widest scope consistent with principle disclosed herein and features of novelty.
Claims (9)
1. a search method, is characterized in that, comprising:
Receive the classification information that first user is selected in preset data model, described preset data model comprises X one-level classification, each one-level classification comprises Y secondary classification, each secondary classification comprises Z three grades of classifications, the like until each M-1 level classification comprises N M level classification, each M level classification comprises each attribute classification of information, wherein by one-level classification, secondary classification ... other order of M level classification and Attribute class, the weight of each classification is successively decreased successively, described X one-level classification comprises: main information, merchandise news, action message, abnormal information and resource information, described attribute classification comprises industry industry attribute, time-space attribute, essential attribute, attribute of a relation, mutual attribute and Authorization Attributes, X wherein, Y, Z, M and N are the natural number except zero,
By the descending mode of weight of each classification, L classification in the classification information that described first user is selected be successively as the first screening conditions, the second screening conditions ... L screening conditions;
In presetting database, according to described the first screening conditions, carry out information sifting, and obtain the first filter information, in described the first filter information, according to described the second screening conditions, carry out information sifting and obtain the second filter information, the like until obtain L filter information in L-1 filter information;
Export described L filter information.
2. the method for claim 1, is characterized in that, the constructive process of described presetting database comprises:
Receive information and the belonging kinds of described information in the classifications at different levels of preset data model that the second user provides;
Obtain the storage area corresponding with described belonging kinds;
In described storage area by described information by the storage of classifying of described attribute classification.
3. method as claimed in claim 2, is characterized in that, the constructive process of described presetting database also comprises:
Retrieval and described information-related related information in database;
Described related information and described information are carried out to association link.
4. the method for claim 1, is characterized in that, also comprises:
Receive the association link that user clicks;
The related information being associated with described information according to described association link output.
5. an indexing unit, is characterized in that, comprising:
The first receiving element, for receiving the classification information that first user is selected at preset data model, described preset data model comprises X one-level classification, each one-level classification comprises Y secondary classification, each secondary classification comprises Z three grades of classifications, the like until each M-1 level classification comprises N M level classification, each M level classification comprises each attribute classification of information, wherein by one-level classification, secondary classification ... other order of M level classification and Attribute class, the weight of each classification is successively decreased successively, described X one-level classification comprises: main information, merchandise news, action message, abnormal information and resource information, described attribute classification comprises industry industry attribute, time-space attribute, essential attribute, attribute of a relation, mutual attribute and Authorization Attributes, X wherein, Y, Z, M and N are the natural number except zero,
Acquisition condition unit, for by the descending mode of weight of each classification, in the classification information that described first user is selected L classification successively as the first screening conditions, the second screening conditions ... L screening conditions;
Screening unit, for carrying out information sifting in presetting database according to described the first screening conditions, and obtain the first filter information, in described the first filter information, according to described the second screening conditions, carry out information sifting and obtain the second filter information, the like until obtain L filter information in L-1 filter information;
Output unit, for exporting described L filter information.
6. device as claimed in claim 5, is characterized in that, also comprises:
The second receiving element, for receiving information that the second user provides and described information at the belonging kinds of the classifications at different levels of preset data model;
Acquiring unit, for obtaining the storage area corresponding with described belonging kinds;
Storage unit, at described storage area by described information by the storage of classifying of described attribute classification.
7. device as claimed in claim 5, is characterized in that, also comprises:
Search unit, for retrieving and described information-related related information at database;
Associative cell, for carrying out association link by described related information and described information.
8. device as claimed in claim 7, is characterized in that, also comprises:
Related information output unit, the association link of clicking for receiving described first user, the related information being associated with described information according to described association link output.
9. a searching system, is characterized in that, comprising:
Server, for receiving the classification information that first user is selected at preset data model, described preset data model comprises X one-level classification, each one-level classification comprises Y secondary classification, each secondary classification comprises Z three grades of classifications, the like until each M-1 level classification comprises N M level classification, each M level classification comprises each attribute classification of information, wherein by one-level classification, secondary classification ... other order of M level classification and Attribute class, the weight of each classification is successively decreased successively, described X one-level classification comprises: main information, merchandise news, action message, abnormal information and resource information, described attribute classification comprises industry industry attribute, time-space attribute, essential attribute, attribute of a relation, mutual attribute and Authorization Attributes, X wherein, Y, Z, M and N are the natural number except zero, by the descending mode of weight of each classification, in the classification information that described first user is selected, L classification is successively as the first screening conditions, the second screening conditions ... L screening conditions, in presetting database, according to described the first screening conditions, carry out information sifting, and obtain the first filter information, in described the first filter information, according to described the second screening conditions, carry out information sifting and obtain the second filter information, the like until obtain L filter information in L-1 filter information, export described L filter information,
Display, for showing the described information that meets described screening conditions.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201310152830.1A CN104123302B (en) | 2013-04-27 | 2013-04-27 | Search method, apparatus and system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201310152830.1A CN104123302B (en) | 2013-04-27 | 2013-04-27 | Search method, apparatus and system |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN104123302A true CN104123302A (en) | 2014-10-29 |
| CN104123302B CN104123302B (en) | 2018-10-19 |
Family
ID=51768714
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201310152830.1A Expired - Fee Related CN104123302B (en) | 2013-04-27 | 2013-04-27 | Search method, apparatus and system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN104123302B (en) |
Cited By (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104636451A (en) * | 2015-01-27 | 2015-05-20 | 孙继荣 | Searching method for agriculture electronic goods |
| CN104731851A (en) * | 2014-12-16 | 2015-06-24 | 芜湖乐锐思信息咨询有限公司 | Big data analysis method based on topological network |
| CN105488121A (en) * | 2015-11-24 | 2016-04-13 | 魏强 | Accurate retrieval system |
| CN107229636A (en) * | 2016-03-24 | 2017-10-03 | 腾讯科技（深圳）有限公司 | A kind of method and device of word's kinds |
| CN107590223A (en) * | 2017-09-04 | 2018-01-16 | 苏州英诺迈医学创新服务有限公司 | A kind of searching method, client and system |
| CN108170743A (en) * | 2017-12-19 | 2018-06-15 | 北京辰森世纪科技股份有限公司 | A kind of search method and device for chain shops's menu |
| CN108563727A (en) * | 2018-03-30 | 2018-09-21 | 新华三大数据技术有限公司 | Data processing method and device |
| WO2019028599A1 (en) * | 2017-08-07 | 2019-02-14 | 深圳益强信息科技有限公司 | Artificial intelligence-based figurative trademark registration possibility determining method and device |
| CN109657664A (en) * | 2017-10-12 | 2019-04-19 | 杭州海康威视数字技术股份有限公司 | A kind of recognition methods, device and the electronic equipment of license plate type |
| CN109933681A (en) * | 2019-03-19 | 2019-06-25 | 深圳Tcl新技术有限公司 | Image searching method, device and computer readable storage medium |
| CN111383071A (en) * | 2018-12-30 | 2020-07-07 | 贝壳技术有限公司 | Method and device for screening conditions of scenes related to real estate transaction system |
| CN111400474A (en) * | 2020-03-20 | 2020-07-10 | 腾讯云计算（北京）有限责任公司 | Intelligent customer service question and answer method and device for government affair service |
| CN113495984A (en) * | 2020-03-20 | 2021-10-12 | 华为技术有限公司 | Statement retrieval method and related device |
| CN115098536A (en) * | 2022-08-24 | 2022-09-23 | 长沙广立微电子有限公司 | Semiconductor data query method, device, electronic equipment and storage medium |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101042705A (en) * | 2006-03-22 | 2007-09-26 | 王克继 | Garment development and production system utilizing a standardized garment data format |
| CN102236691A (en) * | 2010-05-04 | 2011-11-09 | 张文广 | Precision guided searching tool system |
| CN102880624A (en) * | 2011-07-16 | 2013-01-16 | 张文广 | Website navigation tool system |
| US20130097205A1 (en) * | 2011-10-12 | 2013-04-18 | Alibaba Group Holding Limited | Data Classification |
-
2013
- 2013-04-27 CN CN201310152830.1A patent/CN104123302B/en not_active Expired - Fee Related
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101042705A (en) * | 2006-03-22 | 2007-09-26 | 王克继 | Garment development and production system utilizing a standardized garment data format |
| CN102236691A (en) * | 2010-05-04 | 2011-11-09 | 张文广 | Precision guided searching tool system |
| CN102880624A (en) * | 2011-07-16 | 2013-01-16 | 张文广 | Website navigation tool system |
| US20130097205A1 (en) * | 2011-10-12 | 2013-04-18 | Alibaba Group Holding Limited | Data Classification |
Cited By (20)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104731851A (en) * | 2014-12-16 | 2015-06-24 | 芜湖乐锐思信息咨询有限公司 | Big data analysis method based on topological network |
| CN104731851B (en) * | 2014-12-16 | 2018-12-21 | 深圳市易图诚泰数据服务有限公司 | Big data analysis method based on topological network |
| CN104636451B (en) * | 2015-01-27 | 2018-03-09 | 孙继荣 | A kind of searching method of agriculture electronic goods |
| CN104636451A (en) * | 2015-01-27 | 2015-05-20 | 孙继荣 | Searching method for agriculture electronic goods |
| CN105488121A (en) * | 2015-11-24 | 2016-04-13 | 魏强 | Accurate retrieval system |
| CN107229636B (en) * | 2016-03-24 | 2021-08-13 | 腾讯科技（深圳）有限公司 | Word classification method and device |
| CN107229636A (en) * | 2016-03-24 | 2017-10-03 | 腾讯科技（深圳）有限公司 | A kind of method and device of word's kinds |
| WO2019028599A1 (en) * | 2017-08-07 | 2019-02-14 | 深圳益强信息科技有限公司 | Artificial intelligence-based figurative trademark registration possibility determining method and device |
| CN107590223A (en) * | 2017-09-04 | 2018-01-16 | 苏州英诺迈医学创新服务有限公司 | A kind of searching method, client and system |
| CN109657664A (en) * | 2017-10-12 | 2019-04-19 | 杭州海康威视数字技术股份有限公司 | A kind of recognition methods, device and the electronic equipment of license plate type |
| CN108170743A (en) * | 2017-12-19 | 2018-06-15 | 北京辰森世纪科技股份有限公司 | A kind of search method and device for chain shops's menu |
| CN108563727B (en) * | 2018-03-30 | 2020-12-25 | 新华三大数据技术有限公司 | Data processing method and device |
| CN108563727A (en) * | 2018-03-30 | 2018-09-21 | 新华三大数据技术有限公司 | Data processing method and device |
| CN111383071A (en) * | 2018-12-30 | 2020-07-07 | 贝壳技术有限公司 | Method and device for screening conditions of scenes related to real estate transaction system |
| CN111383071B (en) * | 2018-12-30 | 2023-10-27 | 贝壳技术有限公司 | Method and device for screening conditions of scenes related to real estate transaction system |
| CN109933681A (en) * | 2019-03-19 | 2019-06-25 | 深圳Tcl新技术有限公司 | Image searching method, device and computer readable storage medium |
| CN111400474A (en) * | 2020-03-20 | 2020-07-10 | 腾讯云计算（北京）有限责任公司 | Intelligent customer service question and answer method and device for government affair service |
| CN113495984A (en) * | 2020-03-20 | 2021-10-12 | 华为技术有限公司 | Statement retrieval method and related device |
| CN111400474B (en) * | 2020-03-20 | 2023-02-03 | 腾讯云计算（北京）有限责任公司 | Intelligent customer service question and answer method and device for government affair service |
| CN115098536A (en) * | 2022-08-24 | 2022-09-23 | 长沙广立微电子有限公司 | Semiconductor data query method, device, electronic equipment and storage medium |
Also Published As
| Publication number | Publication date |
|---|---|
| CN104123302B (en) | 2018-10-19 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN104123302B (en) | Search method, apparatus and system | |
| Zheng et al. | Does government investment in local public goods spur gentrification? Evidence from Beijing | |
| Wongtada | Street vending phenomena: A literature review and research agenda | |
| Yau | Eco‐labels and willingness‐to‐pay: a Hong Kong study | |
| CN107424041A (en) | Agricultural product coproduction is distributed and joint exhibiting and marketing electric business platform | |
| Coiacetto | Industry structure in real estate development: Is city building competitive? | |
| Azman et al. | Statistical evaluation of pre-selection criteria for industrialized building system (IBS) | |
| An et al. | A study on the impact of soft location factors in the relocation of service and manufacturing firms | |
| Manda | Inside Zambia's ‘new normal:’COVID‐19 policy responses and implications for peri‐urban food security and livelihoods | |
| Greenhalgh et al. | Using GIS to explore the potential of business rating data to analyse stock and value change for land administration: A case study of York | |
| Domingos | Online Consumer Behaviour: How to Create and Maintain E-Loyalty | |
| Feldstein | Zoning and land use controls: beyond agriculture | |
| Nie | Empowering informal settlements in Jakarta with urban agriculture: exploring a community-based approach | |
| Kalinina et al. | Methodological approach to evaluating the prospects of agrotourism development | |
| Rowan | Guaranteed electronic markets: the backbone of a twenty-first century economy? | |
| Wood et al. | Maintaining town centre vitality in competitive environments: pedestrian movements, land-use and built-form in Armidale and Tamworth, NSW | |
| Ngochi | Impacts of University Location on Rural Neighborhood Land Use a Case of Kenya Methodist University Main Campus in Meru County | |
| AKAKANDELWA | THE COPPERBELT UNIVERSITY | |
| Satrio et al. | Development of Public Relation Strategy with Marketing Mix and SOSTAC Approach on Tourism Product, Case Study of Belitung Tourism | |
| Domröse et al. | Assessment report: recent initiatives in science and policy to promote sustainable consumption and recommendations to enhance the German sustainable development strategy in, with and by Germany | |
| Gathura | Urban-rural Linkages: Covid-19 Impacts on Soko Mjinga Market Center and Rural Smallholder Communities in Kinale Ward, Kiambu County. | |
| Nansongole | Determinants of foreign direct investment in tourism: The case of Malawi | |
| Tong | A study of industrial agglomeration and co-location in China | |
| Asahi et al. | Toward Sustainable Regions: Essays in Honor of Kiyoko Hagihara | |
| US10915930B2 (en) | System for selling |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| TA01 | Transfer of patent application right | ||
| TA01 | Transfer of patent application right |
Effective date of registration: 20180904 Address after: 510000 room 1905, Tianhe Road, Tianhe District, Guangzhou, Guangdong, 1905 Applicant after: Guangdong Shang Wen Science and Technology Ltd. s Address before: 610000 22-A, No. 22, West Tower, new century garden, two section of South section of Wuhou District first ring road, Chengdu, Sichuan. Applicant before: SICHUAN HOFOO WIRELESS TECHNOLOGY Co.,Ltd. |
|
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| CF01 | Termination of patent right due to non-payment of annual fee | ||
| CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20181019 |