System and method for matching resource capacity with resource needs

Resources are required to satisfy various needs and wants of people, businesses, and machines. Resources come in the forms of time, talents, money, materials, energy, services, people, knowledge, communication, and other tangible and intangible assets. When both the capacities and the needs of multiple resources are stored in a way that allows for them to be connected together using computers, they can be efficiently and effectively matched. This matching creates shared value, which has potential academic, economic, societal and philanthropic benefits. Connected computer system(s) can query and match resources together in a way that is mutually beneficial. While a common lexicon is the simplest way to perform the matching, natural language processing, machine translation, or use of similar technologies may be optimal. Any method of collecting these inputs should be able to handle one or multiple capacities, and one or multiple needs.

FIELD OF THE INVENTION

The present invention relates generally to a system and method for matching client resource capacity with client resource needs. In particular, the present invention relates to a host system and method for storing client data inputs, assessing and categorizing the client data inputs to create processed client data, matching the processed client data based on the predetermined parameters to create matching output data, and providing the matching output data to the corresponding clients.

BACKGROUND OF THE INVENTION

The Resources are required to satisfy various needs and wants of people, businesses, and machines. Resources come in the form of time, talents, money, materials, energy, services, people, knowledge, communication, and other tangible and intangible assets. While resource requirements and capacities are often generally known, they are often not specifically articulated. Although resource availability and needs can be generally advertised, there lacks an easy to use host system and method to assess and match clients' specific resource capacities with other clients' correspondingly specific resource needs.

Numerous innovations for capacity and demand matching systems have been provided as described below. Even though these innovations may be suitable for the specific purposes to which they address, they differ significantly from the present invention.

U.S. Pat. No. 8,645,312, to Flinn et al., teaches methods and systems for generating personalized recommendations with an enhanced capacity for beneficial serendipity may be applied to enhance personalization functions; U.S. Pat. No. 8,332,418, to Giordani et al., teaches a method and system for matching people by obtaining, for a set of people, response information associated with previous matches the set of people have been a part of; and U.S. published patent application. No. 2,015,127,565, to Chevalier et al., teaches a method and system for matching people, companies, organizations, and/or the like that may benefit from being connected using a social platform.

Thus there remains a need for a system and method to provide host assessment, categorization and matching of client resource capacity data with client resource needs data. The host system provides client data storage and processing of both the capacity and the needs of multiple resources in a way that allows for the client data to be cross-referenced, then efficiently and effectively matched. This matching creates shared value, which has potential economic, societal, academic, & philanthropic benefits.

Numerous innovations for demand and capacity matching systems have been provided in the prior art that are adequate for various purposes. Even though these innovations may be suitable for the specific purposes they address, they differ from the present invention and would not be suitable for the purposes of the present invention as heretofore described.

SUMMARY OF THE INVENTION

The present invention discloses about a system and method for matching resource capacity with resource needs, wherein the system comprises a host system and method for storing client data inputs, assessing and categorizing the client data inputs to create processed client data, matching the processed client data based on the predetermined parameters to create matching output data, and providing the matching output data to the corresponding clients.

According to the present invention the method and system comprise a capacity and need matching system and method, wherein the system and method comprises multiple entities, wherein each entity provides input data including one or more capacities and one or more needs as well as predetermined parameters; a computer-readable non-transitory memory to receive and store the input data including the capacities and the needs of the entities; and a processor that categorizes the stored capacities and the needs of the entities to generate a processed data, wherein the processor compares the processed data and matches the processed data capacities of one or more entities to corresponding processed data needs of other entities based on the predetermined parameters to generate matched data, further based on the matched data, the processor generates matched output data and transmits the matched output data to the respective entities.

DETAILED DESCRIPTION OF THE INVENTION

In one aspect of the invention, as shown inFIGS. 1-8illustrate a capacity and need matching system100, wherein the system100comprising, multiple entities102, wherein each entity102provides input data104including one or more capacities106and one or more needs108according to predetermined parameters112; a computer-readable non-transitory memory110to receive and store the input data104including the capacities106and the needs108of the entities102; and a processor114categorizes the stored capacities106and the needs108of the entities102to generate a processed data116, wherein the processor114compares the processed data116and matches the processed data capacities118of one or more entities102to corresponding processed data needs120of other entities102based on the predetermined parameters to generate matched data122, further based on the matched data122, the processor114generates matched output data124and transmits126the matched output data124to the respective entities102.

The entities102of the systems100are an individual person or a group of people or a society or any resources, clients such as client users, business clients, customer clients or the like or an organization or an institution or a machine like a business system or a computer or a robot or the like who have specific one or more capacities106or needs108or both. Wherein the capacities106and needs108are resources that come in the forms of time, talents, money, materials, energy, services, people, knowledge, communication, and other tangible and intangible assets.

In another aspect of the invention, as showing inFIG. 1, illustrates a method for matching one or more capacities106and one or more needs108of entities102comprising, providing input data104including one or more capacities106and one or more needs108of each entity102according to predetermined parameters112; receiving and storing the input data104including the capacities106and the needs108of the entities102in a computer-readable non-transitory memory110; and categorizing the stored capacities106and the needs108of the entities102to generate a processed data116by a processor114, wherein the processor114compares the processed data116and matches the processed data capacities118of one or more entities102to corresponding processed data needs120of other entities102based on the predetermined parameters112to generate matched data122, further based on the matched data122, the processor114generates matched output data124and transmits126the matched output data124to the respective entities102.

In one embodiment, a host system100may include a data store109having a provider processor114and one or more provider database storage units110. Entities102such as client users access the host system and provide client resource input data104according to predetermined parameters112. The client resource input data104is stored on the provider database storage units110. The provider processor114assesses and categorizes the client resource input data104to create processed client data116. The provider processor114compares the processed client data116and matches the processed client data capacities118to corresponding process client data needs120based on the predetermined parameters112. Upon matching of processed client data116and utilizing the matched data122, the provider processor114generates matching output data124. The host system100provides the matching output data124to the corresponding clients/entities102to guide the clients102in selection of the appropriate resources match.

Various predetermined parameters associated with the entities102may be used in the assessment to provide the most effective matches for presentation of the matching output data124to the clients/users/entities102. Examples of predetermined parameters associated with the entities102may include location (e.g. local vs. distant), language, communication preferences (e.g. voice, text, email, in-person), demographic factors (e.g. education level, occupation, household size/status, values), & business characteristics (number of employees, market area, ownership, workforce structure, competencies). Other types of parameters may be used in the assessment. These parameters and the full set of system capacities and needs are categorized112by the processor114.

FIG. 2is a schematic diagram showing an example of client resource input data104provided to a provider data store109by one or more resources/entities102comprising a computer-readable non-transitory memory110and a processor114embedded in a data store (e.g. laptop, desktop, mobile phone, tablet, server)109for storing and processing the input data104according to an embodiment of the present invention.

FIG. 3is a schematic diagram showing an example of assessment, categorization and matching of client resource input data104by the processor114of data store/server109providing matching output data124available to the clients/entities102according to an embodiment of the present invention.

FIG. 4is a schematic diagram showing an example of the availability of matching output data124to the clients/entities102to help each other and create optimal pairings so as to create mutual value for each other.

For an example as illustrated inFIG. 5ashowing matching, two types of clients/entities102may include unemployed individuals and business executives. Some business executives have little time and some discretionary income. These executives may want to input104into a computer system their resource capacity106, “$100 per month” and their resource needs108, “time”. Some currently unemployed individuals have the capacity to provide time-saving services that can be made available to these business executives. These individuals may want to input104into the same (or a connected) computer system their various resource capacities106, e.g. “Car Detail & Washing”, “House Cleaning”, “Home Organization”, “Grocery Delivery”. The computer system(s) can query and match resources together in a way that is mutually beneficial. While a common lexicon is the simplest way to perform the matching, natural language processing, machine translation, or use of similar technologies may be optimal.

In another example, matching two individual clients/entities102may have compatible talents as illustrated inFIG. 5b. A first client may need creative assistance in starting his business, and is skilled with computers. He can input into the computer system his resource capacity106, “intelligence with computers”, and his needs108, “creativity in business planning”. A second client may be an experienced entrepreneur and needs help with computers. She can input into a connected computer system her resource capacity106, “entrepreneurship”, and her resource needs108, “intelligence with computers”. The connected computer systems can use natural language processing or machine translation to match the first client and the second client together in a way that is mutually beneficial, even though the exact terms may vary. The first client may receive computer help, and the second client may receive help starting his business.

FIG. 6aandFIG. 6bis a schematic diagram showing an example of matching of clients with computer or business system resource capacity106to clients with computer or business system resource needs108.FIG. 6aillustrates an exemplary embodiment showing systems as entities102, where one system has capacity106of offering storage space and need108of CPU capacity whereas another system has capacity106of offering CPU capacity and need108of storage space thereby matching the capacities106and needs108of the entities102by the data store/server109to create an optimal use of both computer systems' resources.FIG. 6billustrates an exemplary embodiment showing business organizations as entities102, where a small business organization that specializes in graphic design as its capacity106but it cannot keep up with requests to create websites as its needs108, where another small business organization that specializes in web development as its capacity106but it spends too much time in creating appealing graphic design as its needs108, thereby matching the capacities106and needs108of the entities102by the data store/server109to create an optimal mutual benefit for both businesses. In above examples ofFIG. 5a,FIG. 5b,FIG. 6aandFIG. 6bfor simplicity of describing the invention a one-to-one relationship is shown, however in actual implementation one-to-one relationship or many-to-one relationship one-to-many relationship or many-to-many relationships may happen.

FIG. 7is a schematic diagram showing an example of matching of a business client/entity102with multiple capacities106to customer clients/entities102who needs one or more services as resource needs108. Wherein the business entity needs108money in exchange to it its service capacities106and the customers need108services by paying with respect to their money paying capacities106.

In an alternate embodiment of the invention, as shown inFIG. 8, illustrates a method for optimally matching one or more capacities and one or more needs of entities while minimizing costs comprising, providing input data (A1, A2, A3) including one or more capacities A1and one or more needs A2and one or more actions received for inputs from the entities or entity information (A3) of each entity through input device(s) A connected to each entity. Upon receiving the input data (A1, A2, A3) the input devices A transmit the input data (A1, A2, A3) to the data store B as shown in step A4. The data store B receives (B1) the input data (A1, A2, A3) and categorizes the input data (A1, A2, A3) based on the entity constraints or predefined parameters B2and the processor of the data store B optimizes the capacity A1with demand A2to generate actions that maximizes each entity's/resource's benefits and minimizes each entity's/resource's costs as represented in step B3, then the datastore B transmits optimized costs, benefits, & actions to the entities' devices A as represented in step B4. Upon receiving the optimized costs, benefits, & actions by entities' devices A as represented in step A5the entities provide actions to optimize cost and benefits (A6) through their devices A and is transmitted to the datastore as represented in step A7. The data store then receives the actions taken as represented in step B5. If the matching between the capacity A1and demand A2is still not optimized the process is repeated on a configurable basis to make adjustments based on the most current data.

In an exemplary embodiment of the system, all resources/entities102will also have variable needs108for how often optimizations occur, some resources/entities102will need to optimize more frequently than others. All resources/entities102will also have variable capacities106to adjust the frequency they are available for optimizations. All resources' optimization needs108and capacities106will fluctuate over time based on the resources inherent needs108and capacities106. This optimization process should be able to generate Markov Chains or Global Cascades or other forms of efficiently & effectively using all available resources.

For example, a Global Cascades model may be used.

In one such example, individual resources may select one of two possible decisions (e.g. answering “yes” or “no”). A given resource is surrounded by other resources, and the choices of other resources (“neighbors”) may influence the choice of any selected resource.

An implementation of the method may seek to identify which portions of the network of resources can trigger full optimization of the network.

The influence of any individual resource on another may be strong or weak based on the predetermined parameters, so matching may vary from strictly united one (under very strong influence) to chaotic distribution of individual decisions (under very weak influence).

All of the different types of resources are part of the network of resources. A change in one resource will have a strong influence among its neighbors and a weak influence on other resources based on network proximity.

The threshold ϕ corresponds to capacities and needs of an individual resource. The distribution f(ϕ) relates to portions of the resources in the network with the threshold specified. Probability pkrelates to a portion of resources in the network, possessing exactly k neighbors.

As mentioned above, a given implementation may seek to use a moment generating function to trigger full network optimization. A moment generating function may is a purely technical function which dramatically decreases complexity of optimizing the network of resources. Using a moment generating function in a given implementation may be desirable.

The moment generations function in this example works in a non-obvious way. First, it does not require a list of resources comprising the network, because it never uses the predetermined parameters or specific resource capacities and needs. It only uses distribution of threshold. In discrete case the distribution would look like: 10% of the resources in the network possess threshold ϕ1, 20% people in the net possess threshold ϕ2, and the rest 70% possess threshold ϕ3. This distribution is assumed continuous, and is described by distribution density. Other implementations of the invention may use different distributions.

Second, the threshold ϕ is not a number of resources required for the network to modify its current state, it is rather a portion of neighbors required to change the resource's current state.

For example, a person may initially decline to purchase a new car but then changes his/her opinion not when (say) 3 weakly linked resources hold that opinion, but when (say) 40% of strongly linked resources purchase a new car. Thus the threshold is measured in the scale [0,1].

Next, the number of resources k varies from resource to resource in a random mode, that is, we know the probabilities pkthat a person has exactly k neighbors, and we also know the average number of neighbors z.

The model is represented by a graph with nodes (resources) and edges (connections with neighbors).

Initially (at time 0) all the resources (nodes of a graph) are in the state 0. Then a small fraction Φ0of the nodes is set to the state 1 (fully utilized). After that the process evolves according to the threshold distribution rules. The solution of the problem using this model is presented in the form of generating functions.

This model takes the following inputs;

distribution of neighbors number, that is, the probabilities pk, k=0,1,2, . . . ;probability density of a threshold f(ϕ), ϕ∈[0,1];
It then calculates intermediate parametersaverage number of neighbors (average “degree”) z=Σkkpk;Cumulative Distribution of a threshold F(ϕ)=∫0ϕf(t)dt;Probability ρkthat a vertex with k neighbors is vulnerable, ρk=F(1/k) k=1,2, . . . ;Generating function G0(x)=Σkρkpkxk;Its second derivative at 1: G″0(1)=Σkk(k−1)ρkpk;
and the output values of interestVulnerable fraction of the network
Pv=G0(1)=ΣkρkpkAverage degree of vulnerable vertices
zv=G′0(1)=ΣkkρkpkAverage vulnerable cluster size
<n>=G0(1)+(G′0(1))2/(z−G″0(1)).

When G″0(1)<z, the vulnerable clusters are small, under the opposite inequality G″0(1)>z the vulnerable clusters are infinite and all resources using the system will be impacted (works like a critical mass in chain reaction).

The output values of interest can then be used to identify portions of the network that can generate the desired network optimization.

One objective of the present invention is to provide a mutually beneficial system for sharing and matching resources' needs108and capacities106.

Another objective is to provide a system, wherein the entities102of the systems100are an individual person or a group of people or a society or any resources, clients such as client users, business clients, customer clients or the like or an organization or an institution or a machine like a business system or a computer or a robot or the like who have specific one or more capacities106or needs108or both.

Yet another objective is to provide a system100, wherein the capacities106and the needs108are resources that come in the forms of time, talents, money, materials, energy, services, people, knowledge, communication, and other tangible and intangible assets, thereby the matching of the capacities106and the needs108create shared value, which has practical benefits across numerous industries and verticals.

Yet another objective is to provide a system100, wherein the categorized predetermined parameters112comprise location preferences, language preferences, availability preferences, communication preferences, demographic factors, business characteristics and other types of parameters that are used in the assessment of the capacities106and the needs108of the entities102.

Yet another objective is to provide a system100, wherein the entities102input data104including the capacities106and the needs108through an application program interface of the system100.

Yet another objective is to provide a system100, wherein the entities102receive their respective matched output data124in full view or summary view or any statistical analysis view over an interface of the system100or through communication device of the entities102.

Yet another objective is to provide a system100, wherein the entities102are interconnected with each other through the system via a network in a one-to-one relationship or many-to-one relationship or many-to-many relationships.

Yet another objective is to provide a system100, wherein the matching of the capacities106and the needs108of the entities102are optimized to generate Markov Chains or Global Cascades or other efficient & effective uses of all available resources.

Yet another objective is to provide a system100, wherein the processor114uses natural language processing, machine translation and similar technologies to generate processed data116and the processor114uses common lexicon or synonyms or similarities between the capacities106and the needs108for matching the processed data116.

Yet another objective is to provide a system100, wherein the entities102are authenticated using an authentication process that uses one or more, variable authentication factors that are based on the value of the capacities106and needs108being matched.

Yet another objective is to provide a system100, wherein the system100uses a payment gateway for receiving an optional entity registration fee and monetizes the release of entity102and matched data124in full view or summary view or any statistical analysis view.