CN103995886A - Multidimensional product design knowledge pushing frame and construction method - Google Patents
Multidimensional product design knowledge pushing frame and construction method Download PDFInfo
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- CN103995886A CN103995886A CN201410239135.3A CN201410239135A CN103995886A CN 103995886 A CN103995886 A CN 103995886A CN 201410239135 A CN201410239135 A CN 201410239135A CN 103995886 A CN103995886 A CN 103995886A
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- 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
Abstract
The invention provides a multidimensional product design knowledge pushing frame and a construction method. The construction method includes the steps that first, dimension characteristics with knowledge pushing as the center and a dimension characteristic similarity association list are established according to product design demands of an enterprise; second, a hybrid user model based on the multiple dimension characteristics is established according to the dimension characteristic similarity association list; third, knowledge is primarily filtered through a behavior data set of a user; fourth, after the timing for triggering pushing is met, the preliminary filtered knowledge obtained in the third step is transmitted to pushing sub-engines of all the dimension characteristics, and the pushing results of all the dimension characteristics are respectively calculated through the hybrid user model established in the second step; fifth, the pushing results obtained in the fourth step are fused to be displayed to the current user; sixth, if the user triggers to push an ending event, the current pushing operation is stopped; before the user ends one time of knowledge pushing, the third step to the sixth step are repeated every time behaviors are generated.
Description
Technical field
The invention belongs to Computer Applied Technology field, be specifically related to a kind of various dimensions product design knowledge and push framework and construction method.
Background technology
In day by day fierce market competition, knowledge-intensive enterprise's run-up in operation process of being engaged in product design works a large amount of knowledge networks that form core competitiveness.The enforcement of information management increases Knowledge Stock gradually, and it is abundant that Knowledge Source is tending towards; But while facing a large amount of knowledge, the problem that user can not effectively immediately obtain required knowledge exposes gradually.
How, effectively for designer, realize transmission and the Push Service of knowledge, to reach the recreation of the sharing of knowledge, knowledge in enterprise, become problem in the urgent need to address.Different enterprises under same group, and the same enterprise of different times under the continuous quickening of turn of the market, its operation flow may be completely different, and this causes its structure of knowledge difference, and the scene of use knowledge is also different from demand.Therefore for different external change, building adaptive various dimensions knowledge propelling movement framework is necessary to meet the knowledge requirement that employee is changeable.
At present, as the push technology that solves the fundamental way that is difficult to obtain required knowledge problem in current enterprise " knowledge ocean ", the research of its each side is especially burning hot.Various dimensions are one of trend of push technology development, are also the very important breakthrough points of various algorithms.But with regard to current, rarely have scholar to study the framework pushing towards product design various dimensions knowledge both at home and abroad.Existing rule-based method can be brought good result, but needs customization operation too much, performance difficulty; Collaborative filtering has higher automaticity, low and can bring higher accuracy rate to structured data request, but can suffer the problems such as sparse property and cold start-up.
The current research that knowledge is pushed only limits to of the process that pushes itself, comprises how representing knowledge and classification, how to reduce error of prediction scoring etc.To pushing structure and follow-up whole calculating process of various dimensions, do as a whole consideration and few.In short, the propelling movement process of existing technical description in the situation that of existed system daily record, is carried out the excavation of variety of way often to data, and the subject matter of considering during propelling movement is how to produce the propelling movement that precision is higher.Before its tangible register system user behaviors log, should set up according to the particular community of supplying system the user behaviors log recording mode of various dimensions, and then consider how with accurate algorithm, to produce and to push.Existing push technology defect is just to fail the factor of various dimensions is considered in advance and be established in supplying system behavior record, accurate and complicated propelling movement algorithm is moved in coarse data, cause pushing the imbalance of algorithm and data, affect the performance of the advantage of knowledge supplying system.
Existing method for pushing and theoretical improving and will cause not:
1) statistical calculation simplification.Under single dimension, behavioral data does not decompose and to cause quantity very huge and have a more noise data owing to carrying out various dimensions.Even if use Cluster Classification algorithm, also just in data source, carry out estimating stealthyly, make computing numerous and diverse consuming time; Because source is single, when the final result pushing fails to consider product design, the various dimensions characteristic of knowledge requirement, causes poor effect.
2) sparse property and cold start-up.What common impact pushed quality has sparse property and a cold start-up problem.Under conventional frame, user's behavior meeting seems very sparse, and the effect of collaborative filtering scheduling algorithm reduces greatly, is called sparse property problem.And that the user who newly enters and knowledge are difficult to because behavior is less is associated, cause these users to be difficult to receive the knowledge of effective propelling movement, these knowledge are also difficult to be pushed to user, and this phenomenon is exactly cold start-up.Sparse property and cold start-up problem easily cause pushing quality and reduce, and make supplying system enter vicious cycle.
3) various dimensions method is perfect not.The knowledge that in the past had scholar to propose various dimensions pushes, but from the system of selection of setting up of dimension, to the fusion of last various dimensions, does not propose complete a set of framework and method, so that be difficult to really to implement the knowledge of various dimensions, pushes.
4) be difficult to routinely improve.The information of traditional user behaviors log record is very few, and behavior meaning is behind difficult to effectively be excavated, and deciphering even makes the mistake.According to " useless input, useless output " principle (GIGO), do not consider that the various dimensions characteristic of behavior easily causes invalid improvement, impact pushes algorithm and promotes adaptively.
Summary of the invention
The object of the invention is, in order to overcome the defect of prior art, in order to solve designer, to obtain the problem of Knowledge Capability deficiency, propose a kind of various dimensions product design knowledge and push framework and construction method.
The inventive method is achieved through the following technical solutions:
Various dimensions product design knowledge pushes framework and a construction method, comprises the following steps:
Step 1, dimensional characteristics and the similar contingency table of dimensional characteristics according to the foundation of enterprise product design requirement centered by knowledge pushes;
Step 2, the hybrid subscriber model according to the similar contingency table foundation of dimensional characteristics based on various dimensions feature;
Step 3, utilize user's behavioral data set pair knowledge tentatively to filter;
Step 4, after the opportunity meet to trigger pushing, the knowledge after the preliminary filtration that step 3 is obtained passes to the sub-engine of propelling movement of each dimensional characteristics, the hybrid subscriber model that utilizes step 2 to set up calculates respectively the propelling movement result of each dimensional characteristics;
Step 5, the propelling movement result that step 4 is obtained show active user after merging;
If step 6 user triggers propelling movement End Event, this pushes computing and stops; User finishes a knowledge and pushes before use, and whenever there being behavior generation, repeating step 3 to 6;
Since then, just completed the process of various dimensions knowledge propelling movement framework and system constructing.
Innovative point of the present invention and the effect reaching are mainly reflected in the following aspects:
(1) foundation of various dimensions makes to push while calculating more foundation, has strengthened the processing power to noise data, has improved the quality of user model;
(2) be easy to provide the explanation of propelling movement, make to push transparent procedures, be beneficial to content and check system problem that user uses propelling movement;
(3) can overcome preferably sparse property, the deciphering due to various dimensions when data are a small amount of significantly reduces the barren situation of propelling movement calculating;
(4) overcome preferably cold start-up problem, the user who newly adds is only that this dimension data of user is less, but is difficult to occur that a plurality of dimensions are all the situations of new data simultaneously; The knowledge newly adding is because the existence of classification dimension will have no small chance to be pushed to be ready to accept the user of new knowledge, thereby this framework is from itself to a certain degree having overcome the cold start-up problem that one-dimensional degree exists;
(5) propose a set of perfect various dimensions method, made various dimensions practical, really given play to the advantage of a plurality of dimensions;
(6) while pushing calculating, operand is little, and pushes content real-time update, possesses good novelty;
(7) can by learning adaptive meet the knowledge requirement of user's various dimensions, strengthen the ability that enterprise staff obtains knowledge.
Whole framework and construction method can instruct the building process of enterprise's supplying system when carrying out information management, thereby strengthen employee's knowledge transmission and acquisition capability, guarantee the advantage of enterprise in market competition.
Accompanying drawing explanation
Fig. 1 is that various dimensions product design knowledge of the present invention pushes framework and construction method process flow diagram;
Fig. 2 is that in the specific embodiment of the invention, knowledge propelling movement result is shown vivid schematic diagram.
Embodiment
Below in conjunction with the drawings and specific embodiments, the present invention is described in detail.
A kind of various dimensions product design knowledge of the present invention pushes framework and construction method, specifically according to following steps, implements:
Step 1, according to the combing of enterprise product design requirement and set up dimensional characteristics and the similar contingency table of dimensional characteristics centered by knowledge pushes.
Defining 1 dimension is concrete object or the things relating in whole knowledge supplying system, mainly contains user, role, task, design object, time, place, use software, knowledge etc.Definition dimension is
Dimension=and user, role, task, design object, the time, place, is used software, knowledge ...
Define 2 dimensional characteristics and be and be under the jurisdiction of dimension and for characterizing the attribute of certain dimension.Dimensional characteristics is the expansion specific to dimension, under each dimension, may have one or more dimensional characteristics.The main method of native system is all launched based on dimensional characteristics.Dimensional characteristics main in this framework has: individual subscriber, user role, design objective, design objective classification, design object, each attribute of design object, time of the act, place, use software assembly, knowledge, the multiple classification of knowledge etc.
Dimensional characteristics={ individual subscriber, user role, design objective, design objective classification, design object, design object attribute 1, design object attribute 2 ..., design object attribute N, time of the act, place, use software assembly, knowledge, knowledge classification 1, knowledge classification ..., knowledge classification M etc. }
Step 1.1, combing are also determined a plurality of dimensions centered by knowledge pushes.Can to default dimensions content, adjust according to enterprise's real needs.
Step 1.2, according to dimension, combing goes out to knowledge to push relevant dimensional characteristics.Can to default dimensions feature, adjust according to enterprise's real needs.
Step 1.3, the similar contingency table of dimensional characteristics according to dimensional characteristics foundation centered by knowledge pushes, each dimensional characteristics can be set up the interior similar table about other a certain features of eigen, the incidence relation of these two features is recorded in this table, the main necessity of setting up similarity between each dimensional characteristics of expressing, and the mode of setting up of similarity, for sky does not have similar incidence relation.If row " design object " are " having " with the similarity relation of row " design object attribute 1 (design object purposes and usable range) ", represent that design object has one about the similarity table of purposes and usable range.Step 2.2 is shown in the foundation of concrete each similarity table.
Step 1.4, according to the similar contingency table of dimensional characteristics, the dimensional characteristics collection select needing, sets up the similar computing of various dimensions for each dimensional characteristics wherein, forms the corresponding sub-engine that pushes.The similarity that pushes sub-engine use must meet the similar contingency table of step 1.3 dimensional characteristics, and the mode of Input knowledge must meet the preliminary result of filtering of step 3, and output must meet the standard of the propelling movement result in definition 6, is more than the constraint that pushes framework antithetical phrase engine.In this constraint, can rebuild arbitrarily as required or change the sub-engine of propelling movement.
Defining the similar computing of 3 various dimensions is for current a certain feature, produces the computing pushing by one of two kinds of modes.1) first by its most similar N that gets of this dimensional characteristics
1individual value, and then get the N the most similar to these values
2individual value, so repeats after X time, explains, as pushing result enclosing to push with the strongest and up-to-date Knowledge Set of these feature associations; 2) first obtain the value the strongest and up-to-date associated knowledge with this dimensional characteristics, get its most similar N bar knowledge, and then get the M the most similar to these knowledge
1individual knowledge, so repeats after X time, the Knowledge Set obtaining is enclosed to push and explain, as pushing result.User, feature, knowledge similarity separately can have multiple, and therefore the feature of same dimension can have the sub-engine of a plurality of propelling movements.By A/B, test dividing technology and user behavior feeds back, use artificial neural network learning optimize N, M ..., X value.
Step 2, the hybrid subscriber model according to dimensional information foundation based on various dimensions feature.
Step 2.1, whenever a vaild act of record, by producing all dimensional characteristics that relate in this behavior, be all recorded in daily record.If existing similarity table is skips steps 2.2, directly enter step 2.3.
Define the set that 4 behaviors are user's all behavioural informations in supplying system.Mainly comprising collection, share, pay close attention to, drag scroll bar etc., is the raw data source of portraying user model.Define behavior is
Behavior={ scoring, shares, and drags scroll bar, clickthrough, button click for collection, comment ...
Defining 5 vaild acts is the behaviors that meet the condition of assert that certain behavior is representative.Common condition as the browsing time, comment on mark, drag scroll bar number of times etc.Defining vaild act is
Vaild act={ A|A ∈ behavior, attribute (A) ∈ vaild act condition set }
Step 2.2, the similar contingency table of dimensional characteristics of setting up according to step 1.3 are set up two-dimentional similarity table.The ranks of each similarity table are the type (as the row of the value of the 13 row first row " vaild act " " individual subscriber ") of the row of the similar contingency table of dimensional characteristics, the similarity of two values that the value in similar table is the type.
Step 2.3, renewal similarity.To not for upgrading the vaild act log of similarity, behavior record whenever the same value of the type (as knowledge) of the row of the similar contingency table of dimensional characteristics, and respective column type (as individual subscriber) is different value, the certain similarity of the increase between the different value of respective column.Conventionally the common behavior record occurring is more, and the popularity of the value of ranks type is lower, and similarity is higher, can suitably revise or select different similarity computing functions according to concrete dimensional characteristics.Before increase, can necessarily decay according to the time.
Step 2.4, will carry out mark for having upgraded the vaild act log of each similarity, will can not be used further to upgrade later.
Step 3, utilize user's behavioral data set pair knowledge tentatively to filter.Specifically according to following steps, implement:
Step 3.1, definite alternative Knowledge Set pushing;
Step 3.2, remove the clear and definite mark of user wherein and do not want the knowledge pushing;
Step 3.3, according to user, arrange and select to get rid of the knowledge that once produced behavior within the scope of user's certain hour;
Step 3.4, according to user, arrange and select to get rid of certain attribute and meet/do not meet the knowledge of certain condition.
Step 4, after the opportunity meet to trigger pushing, the knowledge that step 3 is obtained passes to the sub-engine of propelling movement of each dimensional characteristics, calculates respectively the propelling movement result of each dimensional characteristics.Specifically according to following steps, implement:
Step 4.1, selected need opportunity of pushing, such as primary design product, trial-production revise product, while arbitrarily browsing;
Step 4.2, obtain the current dimensional characteristics being in, the alternative collection of knowledge after step 3 is filtered passes to the sub-engine of propelling movement of each dimensional characteristics, by the similar computing of various dimensions, obtains pushing result;
It is to explain by the knowledge content pushing, propelling movement level and propelling movement the complete object forming that definition 6 pushes result.Wherein the propelling movement level of the propelling movement result of each intermediate computations must be explained associated with a certain propelling movement.Only have the propelling movement result of last displaying to allow the propelling movement level of propelling movement explanation of the same type to merge.
Definition 7 pushes explains it is to user interpretation, to push the brief statement of knowledge content in this result why, as the user who finds according to role's similarity of user, its knowledge interpretation with reference to also approval can be written as " the user XXX similar to you role is once with reference to this knowledge ".
The 8 propelling movement levels that define are a certain knowledge pushed significance levels that go out aspect a certain propelling movement explanation.
Step 5, after being merged, propelling movement result shows active user.Specifically according to following steps, implement:
Step 5.1, traversal push the propelling movement level that in result, each propelling movement is explained, the horizontal averaged of respectively propelling movement of same type being explained;
Step 5.2, the mean value by the level of each propelling movement explanation divided by the type calculating in step 5.1, then be multiplied by the weight of setting this dimensional characteristics.Weight can be optimized by evaluating feedback learning.
Step 5.3, the propelling movement result that each sub-engine is drawn merge according to the ID of knowledge, add simultaneously with each knowledge ID under propelling movement level draw total propelling movement level;
Step 5.4, by total propelling movement result of some that pushes after horizontal descending sort before intercepting as final propelling movement result;
Step 5.5, for final propelling movement, each pushes in result, by the propelling movement level of each explanation, carries out the interpretative reservation of some before intercepting after descending sort, returns to foreground and shows user.The knowledge that Figure 2 shows that the knowledge supplying system that the present embodiment provides pushes the final vivid schematic diagram of showing of result.
If step 6 user triggers propelling movement End Event, this pushes computing and stops; User finishes a knowledge and pushes before use, and whenever there being behavior generation, repeating step 3 to 6.
The arrangement process flow diagram of step 2 to 6 as shown in Figure 1.For saving computational resource, step 2 conventionally and other steps separate at one's leisure and carry out.
Since then, just completed/realized the process of various dimensions knowledge propelling movement framework and system constructing.
Claims (4)
1. various dimensions product design knowledge pushes framework and a construction method, it is characterized in that, comprises the following steps:
Step 1, dimensional characteristics and the similar contingency table of dimensional characteristics according to the foundation of enterprise product design requirement centered by knowledge pushes;
Step 2, the hybrid subscriber model according to the similar contingency table foundation of dimensional characteristics based on various dimensions feature;
Step 3, utilize user's behavioral data set pair knowledge tentatively to filter;
Step 4, after the opportunity meet to trigger pushing, the knowledge after the preliminary filtration that step 3 is obtained passes to the sub-engine of propelling movement of each dimensional characteristics, the hybrid subscriber model that utilizes step 2 to set up calculates respectively the propelling movement result of each dimensional characteristics;
Step 5, the propelling movement result that step 4 is obtained show active user after merging;
If step 6 user triggers propelling movement End Event, this pushes computing and stops; User finishes a knowledge and pushes before use, and whenever there being behavior generation, repeating step 3 to 6;
Since then, just completed the process of various dimensions knowledge propelling movement framework and system constructing.
2. a kind of various dimensions product design knowledge as claimed in claim 1 pushes framework and construction method, it is characterized in that, sets up the similar contingency table of dimensional characteristics and dimensional characteristics and adopts following methods:
Step 1.1, definite a plurality of dimensions centered by knowledge pushes, adjust default dimensions content according to enterprise's real needs;
Step 1.2, according to dimension content, combing goes out to knowledge to push relevant dimensional characteristics, according to enterprise's real needs, default dimensions feature is adjusted;
Step 1.3, the similar contingency table of dimensional characteristics according to dimensional characteristics foundation centered by knowledge pushes;
Step 1.4, according to the similar contingency table of dimensional characteristics, the dimensional characteristics collection select needing, sets up the similar computing of various dimensions for each dimensional characteristics wherein, forms the corresponding sub-engine that pushes.
3. a kind of various dimensions product design knowledge as claimed in claim 1 or 2 pushes framework and construction method, it is characterized in that, the described hybrid subscriber model of setting up adopts following methods:
Step 2.1, whenever a vaild act of record, by producing all dimensional characteristics that relate in this behavior, be all recorded in daily record.If existing similarity table is skips steps 2.2, directly enter step 2.3;
Step 2.2, according to the similar contingency table of dimensional characteristics of setting up, set up two-dimentional similarity table, the ranks of each similarity table are the type of the row of the similar contingency table of dimensional characteristics, the similarity of two values that the value in similar table is the type;
Step 2.3, renewal similarity, to not for upgrading the vaild act log of similarity, whenever the behavior record of the same value of the type of the row of the similar contingency table of dimensional characteristics, and respective column type is different value, the certain similarity of the increase between the different value of respective column;
Step 2.4, will carry out mark for having upgraded the vaild act log of each similarity, will can not be used further to upgrade later.
4. a kind of various dimensions product design knowledge as claimed in claim 1 or 2 pushes framework and construction method, it is characterized in that, after described fusion, shows active user to adopt following methods:
Step 5.1, traversal push the propelling movement level that in result, each propelling movement is explained, the horizontal averaged of respectively propelling movement of same type being explained;
Step 5.2, the mean value by the level of each propelling movement explanation divided by the type calculating in step 5.1, then be multiplied by the weight of setting this dimensional characteristics;
Step 5.3, the propelling movement result that each sub-engine is drawn merge according to the ID of knowledge, add simultaneously with each knowledge ID under propelling movement level draw total propelling movement level;
Step 5.4, by total propelling movement result of some that pushes after horizontal descending sort before intercepting as final propelling movement result;
Step 5.5, for final propelling movement, each pushes in result, by the propelling movement level of each explanation, carries out the interpretative reservation of some before intercepting after descending sort, returns to foreground and shows user.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN106406889A (en) * | 2016-09-22 | 2017-02-15 | 广州华克力信息科技有限公司 | A heterogeneous application system content intelligent conversion engine suitable for mobile clients |
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| CN107194609A (en) * | 2017-06-15 | 2017-09-22 | 北京理工大学 | A kind of product design system and method |
| CN116401468A (en) * | 2023-04-17 | 2023-07-07 | 哈尔滨工业大学 | Intelligent recommendation system and method based on product concept design characteristic combination |
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