CN108399491A - A kind of employee's diversity ranking method based on network - Google Patents
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Abstract
A kind of employee's diversity ranking method based on network, includes the following steps：S1 establishes the weighting Undirected networks of task intersite by employee's task locality data；The network transformation of task place is using task type as the undirected Task Network of the weighting of node by S2；S3 obtains the multifarious preliminary ranking of employee according to level of coverage of the affiliated task type of each employee in Task Network；S4 calculates employee similar in level of network coverage the otherness of its task type；S5 integrates the level of network coverage of employee's task type and task otherness obtains employee's diversity final ranking.It is Task Network that the present invention, which will weight undirected task place network transformation, and the multifarious sequence of employee is obtained in conjunction with the otherness of employee's set of tasks according to level of coverage of employee's task type in Task Network.
Description
Technical field
The present invention relates to data minings and Network Science interior joint diversity field, and network is based on more particularly to one kind
Employee's diversity ranking method.
Background technology
All there is diversity in anything, from macroscopic view to microcosmic, there are diversity, biological species for ecological environment, Social Culture
There are diversity for class, commercial product, and there is also diversity for the gene of same species.The diversity of each things would generally protect
Dynamic equilibrium is held, environment is more adapted to.The diversity of things is to keep system normal and basis and the key of continuous running.It is various
Change the inexorable trend for having become social development, the diversity of employee is that enterprise needs various technical ability in the composition of human resources
Employee, diversified staff's benefits are enterprise staffs under the premise of obedience organizes theory in concert, and personal characteristics keeps certain
Difference.The diversification of employee make tissue become intelligence is complementary, energy level rationally, length is mutually helped, target is consistent and solidarity and cooperation it is whole
Body makes system have higher robustness and stability.
The multifarious sequence of employee is necessary, and comprehensive employee's diversity of weighing can investigate employee work situation in time
Or reasonable arrangement personnel change, and guide employee's operative orientation.Employee's structure is excessively single to cause ossifing for enterprise's operating, make
The operation of enterprise lacks flexibility and mobility, is unfavorable for stabilization and the sustainable development of system.Employee's diversity ranking can close
Reason assesses the diversity of each employee, and rational planning is assigned to its task type, peomotes employee individual and enterprise
The joint development of industry.Multifarious difference between employee can be obtained after diversity ranking, and there is assessment to the work of follow-up employee
With the meaning of guidance.
Patent 201410531309.3 discloses a kind of A stars method for searching and system based on binary tree node sequencing, weight
Point is the efficiency optimization to using A star algorithms to node sequencing when, but without reference to the diversity ranking between node.Patent
201310413387.9 relate to communication network node Assessment of Important, weight and are integrated to the various nodal communities of weighted network
Evaluation index, but do not include mainly its multifarious analysis to the assessment of node importance, therefore it is not suitable for the more of employee
Sample sorts.Patent 201610218405.1 is related to a kind of keyword retrieval method based on diversity and proportionality, to defeated
Linking relationship between the keyword entered and tuple returns to the tuple information based on keyword, but is not particularly suited for nodes
Sequence.In view of disadvantages described above, it is Task Network that the present invention, which will weight undirected task place network transformation, according to employee's task
Level of coverage of the type in Task Network obtains the multifarious sequence of employee in conjunction with the otherness of employee's set of tasks.
Invention content
In order to overcome the shortcomings of that traditional employee's arrangement method is single, it is more that the present invention proposes a kind of employee based on network
Sample sort method, will weight undirected task place network transformation is Task Network, according to employee's task type in Task Network
Level of coverage in network obtains the multifarious sequence of employee in conjunction with the otherness of employee's set of tasks.
The technical solution adopted by the present invention to solve the technical problems is as follows：
A kind of employee's diversity ranking method based on network, includes the following steps：
S1：By employee's task locality data, the weighting Undirected networks of task intersite are established；
S2：It is using task type as the undirected Task Network of the weighting of node by the network transformation of task place；
S3：It is multifarious preliminary that employee is obtained according to level of coverage of the affiliated task type of each employee in Task Network
Ranking；
S4：The otherness of its task type is calculated for employee similar in level of network coverage；
S5：The level of network coverage and task otherness of comprehensive employee's task type obtain employee's diversity final ranking.
Further, in the step S1, according to the contact between task place in employee's task data, task place is established
Network；Quantitatively difference is deposited in connection between task place, and the number of tasks between two places is as task in spot net
Company's side right weight, the weighted undirected graph of foundation is expressed as G=(V, E, W), wherein V=[υ1,υ2,…,υM] with indicating each task
Point, E=[e1,e2,…,eN] indicate that there are task nexus, W=[w between task place1,w2,…,wN] indicate that each place is appointed
Business number；Undirected networks are weighted according to obtained task place, calculate the intensity of each node, then the strength definition of node i is
Wherein weighted network G includes M node, and weight matrix is W=(wij)。
It further, will be using task place as task ground spot net that node, task type are even side in the step S2
It is mapped as Task Network, wherein node indicates task type, and even there are relationships with same task place for two tasks of side expression；By
It is relatively difficult to the sequence of even side importance in network, therefore the company side in the task of expression place is transformed to the node of task, structure
At Task Network L (G).
Further, in the step S3, each employee has its set of tasks completed, if the task of the task type
Number accounts for the 10% of employee's general assignment, then increases to this task type in the set of tasks of the employee；Check the affiliated task of employee
Level of coverage of the type in Task Network, the i.e. set of tasks of employee account for the proportion of all task types in Task Network.
In the step S4, the similitude between any two node pair in each employee's set of tasks is calculated, to weigh
The otherness of each employee's task；
Simplest similarity indices based on local message are common neighbours, and if two nodes have many common neighbours
Node, then two nodes are similar；For the node ν in networkx, it is Γ (x) to define its neighborhood, then two node νxAnd νy
Similitude be just defined as their common neighbours' numbers, i.e.,
sxy=| Γ (x) ∩ Γ (y) |
Sxy=| Γ (x) ∩ Γ (y) |
The influence that node degree is considered on the basis of common neighbours, has multiple similitudes again in different ways from different perspectives
Index：
Salton indexs are also known as cosine similarity, are defined as
Wherein kx, kyFor the degree of node, the number on the side being connected directly with node is indicated；
Jaccard indexs, are defined as
AA indexs are that each node assigns a weighted value according to the degree of common neighbor node, which is equal to the node
Degree logarithm point one, i.e. Adamic-Adar index definitions are
Resource allocation index considers two node ν not being connected directly in networkxAnd νy, from νxSome moneys can be transmitted
Source is to νy, in the process, their common neighbours just become the medium transmitted；Assuming that there are one the moneys of unit for each medium
Source and mean allocation are transmitted to its neighbours, then νxThe number of resources that can be received just is defined as
For weighted network, the node degree used in above-mentioned formula can use the intensity of node；
When level of coverage of employee's task type in Task Network is close, the otherness of set of tasks is bigger, expression person
The diversity of work is stronger.
In the step S5, the multifarious preliminary sequence of employee, employee are obtained according to the level of coverage of employee's set of tasks
Task type is more in set of tasks, reflects its task and has more diversity；But when level of coverage is close or identical, Yuan Gongren
Otherness between business is bigger, comparatively also has more diversity.
The applicable object of the present invention, which is that similar Hospital Logistic transport is this kind of, has whole user behavioral data, but does not have user
The company of the private datas such as identity.The present invention transports data instance to study Zhejiang Hospital's logistics, with will weighting undirected task
Spot net is transformed to Task Network, according to level of coverage of employee's task type in Task Network, in conjunction with employee's set of tasks
Otherness, obtain the multifarious sequence of employee.
Beneficial effects of the present invention are：With Network Science to the analysis method of node, assessed from network structure
Employee's diversity, and work well.
Description of the drawings
Fig. 1 is the flow chart of employee's diversity ranking based on network of the embodiment of the present invention；
Fig. 2 is the task place network of the embodiment of the present invention；
Fig. 3 is the Task Network figure of the embodiment of the present invention；
Fig. 4 is employee's diversity ranking figure of the embodiment of the present invention.
Specific implementation mode
The present invention will be further described below in conjunction with the accompanying drawings.
Referring to Fig.1~Fig. 4, a kind of employee's diversity ranking method based on network, after the present invention uses Zhejiang Hospital
Diligent to transport data, will weight undirected task place network transformation is Task Network, according to employee's task type in Task Network
In level of coverage obtain the multifarious sequence of employee in conjunction with the otherness of employee's set of tasks.
The present invention is divided into following steps：
S1：By employee's task locality data, the weighting Undirected networks of task intersite are established；
S2：It is using task type as the undirected Task Network of the weighting of node by the network transformation of task place；
S3：It is multifarious preliminary that employee is obtained according to level of coverage of the affiliated task type of each employee in Task Network
Ranking；
S4：The otherness of its task type is calculated for employee similar in level of network coverage；
S5：The level of network coverage and task otherness of comprehensive employee's task type obtain employee's diversity final ranking.
Further, in the step S1, according to the contact between task place in employee's task data, task place is established
Network；Quantitatively difference is deposited in connection between task place, and the number of tasks between two places is as task in spot net
Company's side right weight, the weighted undirected graph of foundation is expressed as G=(V, E, W), wherein V=[υ1,υ2,…,υM] with indicating each task
Point, E=[e1,e2,…,eN] indicate that there are task nexus, W=[w between task place1,w2,…,wN] indicate that each place is appointed
Business number；Undirected networks are weighted according to obtained task place, calculate the intensity of each node, then the strength definition of node i is
Wherein weighted network G includes M node, and weight matrix is W=(wij)。
It further, will be using task place as task ground spot net that node, task type are even side in the step S2
It is mapped as Task Network, wherein node indicates task type, and even there are relationships with same task place for two tasks of side expression；By
It is relatively difficult to the sequence of even side importance in network, therefore the company side in the task of expression place is transformed to the node of task, structure
At Task Network L (G)；The topological structure of task nodes after analytic transformation can obtain different task type in structure
On feature.
Further, in the step S3, each employee has its set of tasks completed, if the task of the task type
Number accounts for the 10% of employee's general assignment, then increases to this task type in the set of tasks of the employee；Check the affiliated task of employee
Level of coverage of the type in Task Network, the i.e. set of tasks of employee account for the proportion of all task types in Task Network, come
The diversity for substantially assessing employee's task, is expressed as
Wherein coverageiIndicate the level of network coverage of employee i, ciIndicate the task type number of employee i, cnetIt indicates to appoint
The general assignment number of business network.
In the step S4, the similitude between any two node pair in each employee's set of tasks is calculated, to weigh
The otherness of each employee's task；
Simplest similarity indices based on local message are common neighbours, and if two nodes have many common neighbours
Node, then two nodes are similar；For the node ν in networkx, it is Γ (x) to define its neighborhood, then two node νxAnd νy
Similitude be just defined as their common neighbours' numbers, i.e.,
sxy=| Γ (x) ∩ Γ (y) |
Sxy=| Γ (x) ∩ Γ (y) |
The influence that node degree is considered on the basis of common neighbours, has multiple similitudes again in different ways from different perspectives
Index：
Salton indexs are also known as cosine similarity, are defined as
Wherein kx, kyFor the degree of node, the number on the side being connected directly with node is indicated.
Jaccard indexs, are defined as
AA indexs are that each node assigns a weighted value according to the degree of common neighbor node, which is equal to the node
Degree logarithm point one, i.e. Adamic-Adar index definitions are
Resource allocation index considers two node ν not being connected directly in networkxAnd νy, from νxSome moneys can be transmitted
Source is to νy, in the process, their common neighbours just become the medium transmitted；Assuming that there are one the moneys of unit for each medium
Source and mean allocation are transmitted to its neighbours, then νxThe number of resources that can be received just is defined as
For weighted network, the node degree used in above-mentioned formula can use the intensity of node；
When level of coverage of employee's task type in Task Network is close, the otherness of set of tasks is bigger, expression person
The diversity of work is stronger.
In the step S5, the multifarious preliminary sequence of employee, employee are obtained according to the level of coverage of employee's set of tasks
Task type is more in set of tasks, reflects its task and has more diversity；But when level of coverage is close or identical, Yuan Gongren
Otherness between business is bigger, comparatively also has more diversity.
It is as described above the embodiment introduction of employee's diversity ranking method of the invention in Hospital Logistic delivery system, this
It is Task Network that invention, which will weight undirected task place network transformation, according to covering of employee's task type in Task Network
Degree obtains the multifarious sequence of employee in conjunction with the otherness of employee's set of tasks.Hospital Logistic is weighed from network topology structure
The diversity ranking for transporting employee has reached the requirement of actual use.It is merely illustrative for invention, and not restrictive
's.Those skilled in the art understand that in the spirit and scope defined by invention claim many changes can be carried out to it, repair
Change or even equivalent, but falls in protection scope of the present invention.
Claims (6)
1. a kind of employee's diversity ranking method based on network, it is characterised in that：The sort method includes the following steps：
S1：By employee's task locality data, the weighting Undirected networks of task intersite are established；
S2：It is using task type as the undirected Task Network of the weighting of node by the network transformation of task place；
S3：The multifarious preliminary row of employee is obtained according to level of coverage of the affiliated task type of each employee in Task Network
Name；
S4：The otherness of its task type is calculated for employee similar in level of network coverage；
S5：The level of network coverage and task otherness of comprehensive employee's task type obtain employee's diversity final ranking.
2. a kind of employee's diversity ranking method based on network as described in claim 1, it is characterised in that：The step
In S1, according to the contact between task place in employee's task data, with establishing task spot net；Connection between task place
Quantitatively difference is deposited, as task the company's side right weight in spot net of the number of tasks between two places, the weighting nothing of foundation
It is shown as G=(V, E, W), wherein V=[υ to chart1,υ2,…,υM] indicate each task place, E=[e1,e2,…,eN] indicate
There are task nexus, W=[w between task place1,w2,…,wN] indicate each place number of tasks；According to obtained task place
Undirected networks are weighted, calculate the intensity of each node, then the strength definition of node i is
Wherein weighted network G includes M node, and weight matrix is W=(wij)。
3. a kind of employee's diversity ranking method based on network as claimed in claim 1 or 2, it is characterised in that：It is described
In step S2, by using task place be node, task type be even side the network mapping of task place for Task Network, wherein saving
Point indicates task type, and even there are relationships with same task place for two tasks of side expression；Due in network to even side importance
Sequence it is relatively difficult, therefore will indicate that the company side in task place is transformed to the node of task, constitute Task Network L (G).
4. a kind of employee's diversity ranking method based on network as claimed in claim 1 or 2, it is characterised in that：It is described
In step S3, each employee has its set of tasks completed, if the number of tasks of the task type accounts for the 10% of employee's general assignment,
Then this task type is increased in the set of tasks of the employee；Check covering of the affiliated task type of employee in Task Network
Degree, the i.e. set of tasks of employee account for the proportion of all task types in Task Network.
5. a kind of employee's diversity ranking method based on network as claimed in claim 1 or 2, it is characterised in that：It is described
In step S4, the similitude between any two node pair in each employee's set of tasks is calculated, to weigh each employee's task
Otherness；
Simplest similarity indices based on local message are common neighbours, and if two nodes have many common neighbours' sections
Point, then two nodes are similar；For the node ν in networkx, it is Γ (x) to define its neighborhood, then two node νxAnd νy's
Similitude is just defined as their common neighbours' numbers, i.e.,
sxy=| Γ (x) ∩ Γ (y) |
The influence that node degree is considered on the basis of common neighbours, has multiple similitudes to refer to again in different ways from different perspectives
Mark：
Salton indexs are also known as cosine similarity, are defined as
Wherein kx, kyFor the degree of node, the number on the side being connected directly with node is indicated；
Jaccard indexs, are defined as
AA indexs are that each node assigns a weighted value according to the degree of common neighbor node, which is equal to the degree of the node
Logarithm point one, i.e. Adamic-Adar index definitions are
Resource allocation index considers two node ν not being connected directly in networkxAnd νy, from νxSome resources can be transmitted to arrive
νy, in the process, their common neighbours just become the medium transmitted；Assuming that each medium there are one the resources of unit simultaneously
And mean allocation is transmitted to its neighbours, then νxThe number of resources that can be received just is defined as
For weighted network, the node degree used in above-mentioned formula can use the intensity of node；
When level of coverage of employee's task type in Task Network is close, the otherness of set of tasks is bigger, indicates employee's
Diversity is stronger.
6. a kind of employee's diversity ranking method based on network as claimed in claim 1 or 2, it is characterised in that：It is described
In step S5, the multifarious preliminary sequence of employee is obtained according to the level of coverage of employee's set of tasks, is appointed in employee's set of tasks
Type of being engaged in is more, reflects its task and has more diversity；But when level of coverage is close or identical, the otherness between employee's task
It is bigger, comparatively also have more diversity.
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