CN104240025A - Product design knowledge management service evaluation method - Google Patents
Product design knowledge management service evaluation method Download PDFInfo
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- CN104240025A CN104240025A CN201410452471.6A CN201410452471A CN104240025A CN 104240025 A CN104240025 A CN 104240025A CN 201410452471 A CN201410452471 A CN 201410452471A CN 104240025 A CN104240025 A CN 104240025A
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Abstract
The invention provides a product design knowledge management service evaluation method. The method includes the following steps that (1) firstly a knowledge service object required to be evaluated should be made clear, the feature of the product development knowledge service evaluation is analyzed, and a product development knowledge service platform evaluation index system is built based on the demand feature of the knowledge service and the service resource feature; (2) a product design knowledge management service evaluation process is designed, and the knowledge service is evaluated according to a product design knowledge management service evaluation algorithm. According to the product design knowledge management service evaluation method, through knowledge service platform feedback and optimization, such as knowledge service content optimization and knowledge service platform optimization, the using value of the knowledge service platform can be improved.
Description
Technical field
The present invention relates to a kind of management service evaluation method, particularly, relate to a kind of product-design knowledge management service evaluation method.
Background technology
At present, knowledge management method provides knowledge to browse and inquires about as main document management, its object mainly knowledge share, cause the specific aim of knowledge services and professional not strong, be difficult to for user provides knowledge accurately, the level of knowledge services is also lower in addition, is difficult to provide support business intelligence decision-making.
People are to the basis for estimation wide material sources of objective things, and have multiple different combined factors to be formed, reach a conclusion by considering many factors, this is called comprehensive evaluation.In daily life and practice, the information that we touch is often fuzzy, and containing more uncertainty, people need just to be judged and evaluate by the understanding of perception, and this is called fuzzy synthetic appraisement method.But when in the face of challenge, usually problem can be divided into different levels, the level of the more complicated division of problem is more, according to the difference dividing level quantity, becomes one-level, secondary and multi-step Fuzzy Comprehensive Evaluation.
Due to the complicacy of knowledge services, relate to all too many levels and participant, therefore need to consider many factors to the comprehensive consideration of product-design knowledge management service and evaluation, whether the expression-form as knowledge resource can represent knowledge intension, whether the content of knowledge services meets the requirements, and whether the mode of Knowledge Sharing meets use habit etc.Current evaluation method lacks from knowledge services content and platform two aspect structure index system, to service process and service ability evaluation study.From knowledge services content and Knowledge Service Platform structure assessment indicator system, performance appraisal should be launched.
Summary of the invention
For defect of the prior art, the object of this invention is to provide a kind of product-design knowledge management service evaluation method, its
According to an aspect of the present invention, a kind of product-design knowledge management service evaluation method is provided, it is characterized in that, comprise the following steps: step 1: the knowledge services object first should specifying needs assessment, the feature of analytic product development knowledge service evaluation, demand characteristic and the service resource characteristic of knowledge based service build product development Knowledge Service Platform assessment indicator system; Step 2: deisgn product Design Knowledge Management service evaluation flow process, carries out the evaluation of knowledge services according to product-design knowledge management service evaluation algorithms.
Preferably, the product development Knowledge Service Platform assessment indicator system of described step 1 is divided into information management service content and information management service platform.
Preferably, the evaluation index of described information management service content pushes four aspects launch from knowledge representation, knowledge organization, Knowledge Sharing, knowledge.
Preferably, described information management service platform is evaluated from knowledge services function and knowledge services flow process two aspects.
Preferably, described knowledge services function mainly comprises knowledge services reliability, knowledge services level and knowledge services individual needs.
Preferably, first described step 2 presses some attribute all these influence factors divide into several classes, in each class, carry out one-level fuzzy overall evaluation; Secondly Secondary Fuzzy Comprehensive Evaluation is carried out again according to all kinds of one-level evaluation result.
Preferably, described one-level fuzzy overall evaluation, Secondary Fuzzy Comprehensive Evaluation all comprise four fundamental: set of factors X={x
1, x
2..., x
n, evaluate collection Y={y
1, y
2..., y
m, single factor evaluation matrix R=(r
ij)
nm, factor weight A=(a
1, a
2..., a
n).
Preferably, the evaluation model of the evaluation model of described one-level fuzzy overall evaluation, comprehensive evaluation that secondary is fuzzy all as shown in the formula:
Wherein, r
ijrepresent single factor evaluation matrix, a
irepresent factor weight.
Preferably, the flow process of described level fuzzy overall evaluation and Secondary Fuzzy Comprehensive Evaluation comprises the following steps: the first step: single factor evaluation; Second step: one-level fuzzy overall evaluation; 3rd step: secondary fuzzy evaluation; 4th step: based on the improvement of evaluation result.
Preferably, described first step single factor evaluation comprises following sub-step: first, by set of factors X={X
1, X
2..., X
nclassification, oneself number sorted is s, therefore X={X
1, X
2..., X
s, wherein, X
i(i=1,2 ..., n), X
j(j=1,2 ..., s), X
irepresent i-th influence factor, X
jrepresent jth sub-set of factors, the then following condition of demand fulfillment: all subclass X
j(j=1,2 ..., s) the number summation of containing element, result is n;
secondly, set up single factor evaluation collection, build single factor evaluation matrix.
Compared with prior art, the present invention has following beneficial effect: one, help enterprise that user is compiled using the problem that finds in Knowledge Service Platform process or unreasonable part, and improve flow process and the content of knowledge services in time, meet the knowledge requirement in design process.Two, help the sustainable development of Company Knowledge service platform.Three, help enterprise to improve the service performance of Knowledge Service Platform.Four, by the feedback of Knowledge Service Platform and optimization, as the optimization of knowledge services content, the optimization etc. of Knowledge Service Platform, the use value of Knowledge Service Platform can be improved.The more important thing is can the result of use of continuous improving product development knowledge service platform, the problem that user is in use found or unreasonable part are compiled, and improve flow process and the content of knowledge services in time, thus improve the service performance of Knowledge Service Platform.
Accompanying drawing explanation
By reading the detailed description done non-limiting example with reference to the following drawings, other features, objects and advantages of the present invention will become more obvious:
Fig. 1 is the schematic diagram of the information management service evaluation flow process of product design in the present invention.
Embodiment
Below in conjunction with specific embodiment, the present invention is described in detail.Following examples will contribute to those skilled in the art and understand the present invention further, but not limit the present invention in any form.It should be pointed out that to those skilled in the art, without departing from the inventive concept of the premise, some distortion and improvement can also be made.These all belong to protection scope of the present invention.
Product-design knowledge management service evaluation method of the present invention comprises the following steps:
Step 1: the knowledge services object first should specifying needs assessment, as " explicit evaluation object " in Fig. 1, the feature of analytic product development knowledge service evaluation, demand characteristic and the service resource characteristic of knowledge based service build product development Knowledge Service Platform assessment indicator system, " structure index system " in Fig. 1, the product development Knowledge Service Platform assessment indicator system chosen mainly is divided into two parts, is information management service content and information management service platform respectively.The evaluation index of information management service content is from knowledge representation (B
1), knowledge organization (B
2), Knowledge Sharing (B
3), knowledge push (B
4) etc. four aspects launch; Information management service platform is from knowledge services function (B
5) and knowledge services flow process (B
6) two aspects evaluate, (see table 1 knowledge services assessment indicator system) Formal Representation is formula (1):
AS＝(KRepresentation,KIntegration,KSharing,KRecommendation,KSFunction,KSProcess)………………………………………………………………………(1)
Table 1
(1) knowledge representation (B
1)
Whether knowledge representation evaluation index mainly refers to the rationality that knowledge resource is expressed, easily received by knowledge user and understand, and ease for use.Knowledge representation index KRep (S) represents.This is comprising knowledge Comprehensible (B
11), knowledge accepts complexity (B
12) and knowledge ease for use (B
13), Formal Representation is formula (2):
KRep(S)＝KRepcomp(S)+KRep
acce(S)+KRep
usab(S)………………………(2)
1.1) knowledge Comprehensible (B
11)
The expression of knowledge resource, for understanding knowledge services user and the complexity of study, uses KRep
comp(S) represent.
1.2) knowledge accepts complexity (B
12)
The expression of knowledge services resource is difficult to degree for what accept knowledge services user, uses KRep
acce(S) represent.
1.3) knowledge ease for use (B
13)
After knowledge services user gets knowledge resource, the whether convenient study of the expression of knowledge resource and use consider index, use KRep
usab(S) represent.
(2) knowledge organization (B
2)
Knowledge organization evaluation index is mainly evaluated the integrated of knowledge, comprises the aspect factors such as the complexity obtaining the coverage rate of knowledge, the degree of integration of knowledge and knowledge.Knowledge organization index KInt (S) represents, this is comprising the easy coverage rate (B of knowledge
21), Knowledge Aggregation degree (B
22) and knowledge complexity (B
23), Formal Representation is formula (3):
KInt(S)＝KInt
cove(S)+KInt
inte(S)+KInt
comx(S)………………………(3)
2.1) knowledge coverage rate (B
21)
Knowledge coverage rate refers to the comprehensive of the knowledge that knowledge services user is got by knowledge retrieval mode, and whether the knowledge retrieved can meet personal knowledge demand, uses KInt
cove(S) represent.
2.2) Knowledge Aggregation degree (B
22)
How the degree of integration of knowledge refers to the integrality of the knowledge that user gets, and uses KInt
inte(S) represent.
2.3) knowledge complexity (B
23)
Knowledge complexity refers to the complexity of the knowledge that knowledge services user gets, and whether whether aspect uses, be easy to accept, use KInt
comx(S) represent.
(3) Knowledge Sharing (B
3)
Knowledge Sharing index mainly refers to the complexity etc. of the matching degree of result in knowledge retrieval process, availability and knowledge retrieval here, represents, mainly comprise knowledge matching degree (B with KShar (S)
31), knowledge availability (B
32) and knowledge retrieval complexity (B
33), Formal Representation formula is formula (4):
KShar(S)＝KShar
matc(S)+KShar
avai(S)+KShar
comx(S)…………………(4)
3.1) knowledge matching degree (B
31)
Knowledge matching degree refers to the matching degree between knowledge retrieval result and knowledge services user demand, whether can meet the retrieval requirement of user, use KShar
matc(S) represent.
3.2) knowledge availability (B
32)
Knowledge availability refers to the probability that the knowledge resource obtained by knowledge retrieval can normally be used, and uses KShar
avai(S) represent.
3.3) knowledge retrieval complexity (B
33)
Knowledge retrieval complexity refers to that user is in the complexity of carrying out operating in the process of knowledge retrieval, and efficient knowledge retrieval can reduce the time greatly and improve development efficiency, uses KShar
comx(S) represent.
(4) knowledge pushes (B
4)
Knowledge pushes index and is used for evaluating the performance that knowledge pushes, and mainly launches to evaluate towards three kinds of different propelling movement modes.Represent with KReco (S), mainly comprise the matching degree (B of knowledge and task
41), the degree of conformity (B of knowledge and interest
42) and the matching degree (B of knowledge professional
43) etc., Formal Representation is formula (5):
KReco(S)＝KReco
task(S)+KReco
inte(S)+KReco
expe(S)…………………(5)
4.1) matching degree (B of knowledge and task
41)
Knowledge and the matching degree of task mainly refer to mates order of accuarcy between the task that the knowledge content of propelling movement and user will develop, and uses KReco
task(S) represent.
4.2) degree of conformity (B of knowledge and interest
42)
The degree of conformity of knowledge and interest mainly refer to the knowledge content of propelling movement and the personal interest of user like between matching degree, use KReco
inte(S) represent.
4.3) matching degree (B of knowledge professional
43)
The matching degree of knowledge professional mainly refers to the matching degree between the knowledge professional of propelling movement and the product development field of carrying out, and whether the knowledge professional pushed suits the requirements, and uses KReco
expe(S) represent.
(5) knowledge services function (B
5)
The service ability of knowledge services functional parameter primary evaluation Knowledge Service Platform, considers the interests can brought to user, represents, mainly comprise knowledge services reliability (B with KSFu (S) from the angle of value of services
51), knowledge services level (B
52) and knowledge services individual needs (B
53), Formal Representation is formula (6):
KSFu(S)＝KSFu
capa(S)+KSFu
indi(S)+KSFu
reli(S)…………………………(6)
5.1) knowledge services reliability (B
51)
Knowledge services reliability refers to that knowledge services completes the probability that function does not cause inefficacy within the regular hour, uses KSFu
reli(S) represent.
5.2) knowledge services level (B
52)
Knowledge services level refers to the effect that the knowledge services resource got can play in product development process, helps product development man winding Quality of Product and efficiency, uses KSFu
capa(S) represent.
5.3) knowledge services individual needs (B
53)
Knowledge services individual needs refers to that knowledge services is in the ability meeting user knowledge demand, uses KSFu
indi(S) represent.
(6) knowledge services flow process (B
6)
Knowledge services flow process evaluates the index of user in the process using information management service platform in individual perception, represents with KSPr (S), mainly comprises service platform response (B
61), service platform reaction velocity (B
62), service platform Service Source (B
63), services platform user participate in (B
64) and service platform security (B
65), Formal Representation is formula (7):
KSPr(S)＝KSPr
resp(S)+KSPr
reac(S)+KSPr
reso(S)+KSPr
part(S)+KSPr
safe(S)………(7)
6.1) service platform response (B
61)
After service platform response refers to that user produces input to service platform, service platform receives the input of user, after then making relevant process, produces and exports, use KSPr
resp(S) represent.
6.2) service platform reaction velocity (B
62)
Service platform reaction velocity refer to user send demand application or operation application after system time of making a response, use KSPr
reac(S) represent.
6.3) service platform Service Source (B
63)
Service platform Service Source refer to user usage platform process China can get knowledge resource enrich degree, use KSPr
reso(S) represent.
6.4) services platform user participates in (B
64)
As long as Knowledge Service Platform degree of participation instigate user obtain knowledge resource process in participation method and degree of participation, use KSPr
part(S) represent.
6.5) service platform security (B
65)
The safe coefficient of service platform security reflection Knowledge Service System and knowledge services, uses KSPr
safe(S) represent.
Step 2: the information management service evaluation flow process of deisgn product design, build knowledge services evaluation model, as " structure evaluation model " in Fig. 1, the evaluation (the information management service evaluation flow process see the product design of Fig. 1) of knowledge services is carried out according to product-design knowledge management service evaluation algorithms, as " model evaluation " in Fig. 1, be specially: first, by some attribute all these influence factors divide into several classes, in each class, carry out one-level fuzzy overall evaluation; Secondly, carry out Secondary Fuzzy Comprehensive Evaluation again according to all kinds of one-level evaluation result, particular content is as follows:
(2-1) one-level fuzzy overall evaluation, Secondary Fuzzy Comprehensive Evaluation all comprise four fundamental: set of factors X={x
1, x
2..., x
n, evaluate collection Y={y
1, y
2..., y
m, single factor evaluation matrix R=(r
ij)
nm, factor weight A=(a
1, a
2..., a
n).As " agriculture products value " and " agriculture products weight " in table 1.
(2-2) evaluation model of the evaluation model of one-level fuzzy overall evaluation, comprehensive evaluation that secondary is fuzzy is all as shown in the formula (8):
Wherein, r
ijrepresent single factor evaluation matrix, a
irepresent factor weight.
(2-3) flow process of one-level fuzzy overall evaluation and Secondary Fuzzy Comprehensive Evaluation comprises the following steps:
The first step: single factor evaluation
First, by set of factors X={X
1, X
2..., X
nclassification, oneself number sorted is s, therefore X={X
1, X
2..., X
s, wherein, X
i(i=1,2 ..., n), X
j(j=1,2 ..., s), X
irepresent i-th influence factor, X
jrepresent jth sub-set of factors, the then following condition of demand fulfillment:
2-3-1) all subclass X
j(j=1,2 ..., s) the number summation of containing element, result is n;
2-3-2)
2-3-3)
Secondly, set up single factor evaluation collection, build single factor evaluation matrix R
i(i=1,2 ..., s).
Second step: one-level fuzzy overall evaluation
Suppose sub-set of factors X
i(i=1,2 ..., containing n s)
iindividual element, then have Σ n
i=n (i=1,2 ..., s), same, suppose sub-set of factors X
isingle factor evaluation matrix be R
i.
First X is defined
i(i=1,2 ..., each factor weight s),
wherein
Then, according to one-level fuzzy evaluation model, obtain one-level fuzzy evaluation vector B
i, B
i=A
io R
i=(b
i1, b
i2..., b
im).
3rd step: secondary fuzzy evaluation
First, X
ibe factor, then an X={x
1, x
2..., x
s, the single factor evaluation matrix of X asks R, such as formula (9):
Secondary weight vectors is A=(a
1, a
2..., a
s), obtain Secondary Fuzzy Comprehensive Evaluation vector B, B=A o R=(b
1, b
2..., b
m)
To the element row descending in Secondary Fuzzy Comprehensive Evaluation vector, the position that greatest member is corresponding is final appraisal results.
4th step: based on the improvement of evaluation result
This part content is technical (as " interpretation of result " in Fig. 1) analyzed evaluation result, the final purpose evaluated the effect of information management service platform improves the weak link that information management is served according to evaluation result, to improve the performance of information management service platform, improve organization knowledge utilization factor and user satisfaction.When after the comprehensive evaluation value obtaining indices, trap queuing can be carried out according to comprehensive evaluation value to the user satisfaction of indices, and then determine index to be modified, carry out the improvement having pin a pair property.The corresponding concrete improvement strategy of indices is:
(2-4-1) to the improvement of information management service content
According to the index that knowledge propelling movement content factors comprises, the improvement of following aspect can be carried out:
To the improvement of content degree of correlation and information management efficiency of service, can Ontology Evolution be passed through, make the statement of knowledge content and knowledge requirement more in detail, clear and definite; By the renewal of knowledge, obtain up-to-date knowledge, to improve the effectiveness of knowledge; By improving knowledge retrieval mechanism (increase task situation coupling, knowledge difficulty are mated with member's human-subject test), improve the matching degree of member's demand and service content;
To the improvement of knowledge representation form, continue the individual preference deeply excavating member, represent knowledge with the understandable form of member, use advanced representation aids and technology, as graph generator, voice operation demonstrator, numeral is become chart with text conversion, speech form sends member to;
To the improvement of content coverage rate, can according to body, the scope of the association that expands knowledge, and adjust coupling and close value, will be included in service content with member's demand relevant knowledge.
To the improvement of knowledge complexity, note the cognitive development following the tracks of member, give its suitable know-how (being stored in user profile), divide the difficulty rank of knowledge in detail, push the knowledge adapted with its human-subject test to member;
To the improvement of knowledge layout, in user profile, upgrade Studying Situntion and the task situation of member, express knowledge with the form meeting member's learning characteristic and work habit.
(2-4-2) to the improvement of Knowledge Service Platform
According to the index that information management service platform comprises, the improvement of following aspect can be carried out:
(2-4-2-1) to the improvement receiving patency, according to the improvement idea of member, to meet most a kind of mode (or various ways combines) reception knowledge that member receives custom;
(2-4-2-2) to the adaptive improvement of frequency, be also the customization according to organizational requirements and member, push knowledge with suitable frequency;
(2-4-2-3) to the improvement of service promptness, note the change following the tracks of organization knowledge demand, set up renewal of knowledge monitoring mechanism, emphasis is for new knowledge requirement and focus knowledge requirement, carry out knowledge search, adding when there being new knowledge fashionablely provides to member in time.
In sum, the present invention is directed to the performance problem of product-design knowledge management service, from fuzzy theory, use Secondary Fuzzy Comprehensive Evaluation method, towards the expression of fuzzy language, build rational assessment indicator system, launch to evaluate.By the feedback of Knowledge Service Platform, to the optimization etc. of knowledge services content and lethal rear service platform, improve the use value of Knowledge Service Platform.
Above specific embodiments of the invention are described.It is to be appreciated that the present invention is not limited to above-mentioned particular implementation, those skilled in the art can make various distortion or amendment within the scope of the claims, and this does not affect flesh and blood of the present invention.
Claims (10)
1. a product-design knowledge management service evaluation method, is characterized in that, comprises the following steps:
Step 1: the knowledge services object first should specifying needs assessment, the feature of analytic product development knowledge service evaluation, demand characteristic and the service resource characteristic of knowledge based service build product development Knowledge Service Platform assessment indicator system;
Step 2: deisgn product Design Knowledge Management service evaluation flow process, carries out the evaluation of knowledge services according to product-design knowledge management service evaluation algorithms.
2. product-design knowledge management service evaluation method according to claim 1, is characterized in that, the product development Knowledge Service Platform assessment indicator system of described step 1 is divided into information management service content and information management service platform.
3. product-design knowledge management service evaluation method according to claim 2, is characterized in that, the evaluation index of described information management service content pushes four aspects launch from knowledge representation, knowledge organization, Knowledge Sharing, knowledge.
4. product-design knowledge management service evaluation method according to claim 2, is characterized in that, described information management service platform is evaluated from knowledge services function and knowledge services flow process two aspects.
5. product-design knowledge management service evaluation method according to claim 4, is characterized in that, described knowledge services function mainly comprises knowledge services reliability, knowledge services level and knowledge services individual needs.
6. product-design knowledge management service evaluation method according to claim 1, is characterized in that, first described step 2 presses some attribute all these influence factors divide into several classes, in each class, carry out one-level fuzzy overall evaluation; Secondly Secondary Fuzzy Comprehensive Evaluation is carried out again according to all kinds of one-level evaluation result.
7. product-design knowledge management service evaluation method according to claim 6, is characterized in that, described one-level fuzzy overall evaluation, Secondary Fuzzy Comprehensive Evaluation all comprise four fundamental: set of factors X={x
1, x
2..., x
n, evaluate collection Y={y
1, y
2..., y
m, single factor evaluation matrix R=(r
ij)
nm, factor weight A=(a
1, a
2..., a
n).
8. product-design knowledge management service evaluation method according to claim 7, is characterized in that, the evaluation model of the evaluation model of described one-level fuzzy overall evaluation, comprehensive evaluation that secondary is fuzzy all as shown in the formula:
Wherein, r
ijrepresent single factor evaluation matrix, a
irepresent factor weight.
9. product-design knowledge management service evaluation method according to claim 8, is characterized in that, the flow process of described level fuzzy overall evaluation and Secondary Fuzzy Comprehensive Evaluation comprises the following steps:
The first step: single factor evaluation;
Second step: one-level fuzzy overall evaluation;
3rd step: secondary fuzzy evaluation;
4th step: based on the improvement of evaluation result.
10. product-design knowledge management service evaluation method according to claim 9, is characterized in that, described first step single factor evaluation comprises following sub-step:
First, by set of factors X={X
1, X
2..., X
nclassification, oneself number sorted is s, therefore X={X
1, X
2..., X
s, wherein, X
i(i=1,2 ..., n), X
j(j=1,2 ..., s), X
irepresent i-th influence factor, X
jrepresent jth sub-set of factors, the then following condition of demand fulfillment: all subclass X
j(j=1,2 ..., s) the number summation of containing element, result is n;
secondly, set up single factor evaluation collection, build single factor evaluation matrix.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108390903A (en) * | 2017-12-25 | 2018-08-10 | 潘彦伶 | A kind of In-vehicle networking music system |
| CN110472852A (en) * | 2019-08-02 | 2019-11-19 | 上海云扩信息科技有限公司 | A kind of experience assessment implementation management method of electrical power services application |
| CN111708934A (en) * | 2020-05-14 | 2020-09-25 | 北京百度网讯科技有限公司 | Knowledge content evaluation method and device, electronic equipment and storage medium |
-
2014
- 2014-09-05 CN CN201410452471.6A patent/CN104240025A/en active Pending
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108390903A (en) * | 2017-12-25 | 2018-08-10 | 潘彦伶 | A kind of In-vehicle networking music system |
| CN110472852A (en) * | 2019-08-02 | 2019-11-19 | 上海云扩信息科技有限公司 | A kind of experience assessment implementation management method of electrical power services application |
| CN110472852B (en) * | 2019-08-02 | 2023-03-03 | 上海云扩信息科技有限公司 | Experience evaluation implementation management method for power service application |
| CN111708934A (en) * | 2020-05-14 | 2020-09-25 | 北京百度网讯科技有限公司 | Knowledge content evaluation method and device, electronic equipment and storage medium |
| CN111708934B (en) * | 2020-05-14 | 2023-06-20 | 北京百度网讯科技有限公司 | Knowledge content evaluation method, device, electronic equipment and storage medium |
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Application publication date: 20141224 |