Claims:We Claim:
1. A method of pairing requests, comprising:
a. estimating at least one content-specific or requestor-specific characteristic associated with a request;
b. determining a set of available partners, each having at least one respective partner characteristic;
c. evaluating, with at least one automated processor,
d. generating a control signal, by the at least one automated processor, selectively dependent on the evaluating.
2. The method according to claim 1, wherein the evaluator having an economic function further dependent on a pairing cost or benefit of the requestor with respective partners.
3. The method according to claim 2, wherein the evaluator having a receiving bid from respective partners.
4. The method according to claim 1, wherein the evaluator having a multivariate function of at least two content-specific or requestor-specific characteristics and at least two respective partner characteristics.
5. The method according to claim 1, wherein the evaluator function having a clustering algorithm.
6. The method according to claim 5, wherein the clustering algorithm a multidimensional clustering algorithm for clustering data in a space having at least 3 dimensions.
7. The method according to claim 1, wherein the evaluator is a hierarchical Markov model.
8. The method according to claim 1, wherein the evaluator is a Bayesian network.
9. The method according to claim 1, wherein the evaluator a neural network.
10. The method according to claim 1, wherein the evaluator is dependent on a shape of at least one probability distribution.
, Description:Technical Field of the Invention
The present invention relates generally to computer integrated telecommunications systems and more particularly to a system and method employing an intelligent switching architecture.
Background of the Invention
The description of the invention herein is intended to provide information for one skilled in the art to understand and practice the full scope of the invention, but is not intended to be limiting as to the scope of available knowledge, nor admit that any particular reference, nor the combinations and analysis of this information as presented herein, is itself a part of the prior art. It is, in fact, a part of the present invention to aggregate the below cited information as a part of the disclosure, without limiting the scope thereof. All the below-identified references are therefore expressly incorporated herein by reference, as if the entirety thereof was recited completely herein. It is particularly noted that the present invention is not limited by a narrow or precise discussion herein, nor is it intended that any disclaimer, limitation, or mandatory language as applied to any embodiment or embodiments be considered to limit the scope of the invention as a whole. The scope of the invention is therefore to be construed as the entire literal scope of the claims, as well as any equivalents thereof as provided by law. It is also understood that the title, abstract, field of the invention, and dependent claims are not intended to, and do not, limit the scope of the independent claims.
Real-time communications are typically handled by dedicated systems which assure that the management and control operations are handled in a manner to keep up with the communications process, and to avoid imposing inordinate delays. In order to provide cost-effective performance, complex processes incidental to the management or control of the communication are typically externalized. Thus, the communications process is generally unburdened from tasks requiring a high degree of intelligence, for example the evaluation of complex algorithms and real time optimizations. One possible exception is least cost routing (LCR), which seeks to employ a communications channel which is anticipated to have a lowest cost per unit. In fact, LCR schemes, when implemented in conjunction with a communications switch, either employ simple predetermined rules, or externalize the analysis. Modern computer telephone integrated systems typically employ a general-purpose computer with dedicated voice-communication hardware peripherals, for example boards made by Dialogic, Inc. The voice communication peripherals execute the low-level processing and switching of the voice channels, under control from the general-purpose processor. Therefore, the voice-information is generally not communicated on the computer bus.
This architecture typically allows the computing platform to run a modern, non-deterministic operating system, such as Windows 2000, without impairing the real-time performance of the system, since the communications control functions are not as time critical as the voice processing functions. However, as is well known, non-deterministic operating systems, such as Windows 2000, are subject to significant latencies, especially when multiple tasks are executing, and when contention exists between resources, especially hard disk access and virtual memory. Therefore, in order to assure that system operation is unimpeded by inconsistent demands on the platform, typically the host computer system for the telephony peripherals is “dedicated”, and attempts are made to eliminate extraneous software tasks. On the other hand, externalizing essential functions imposes potential latencies due to communications and external processing.
Object of the Invention
The present invention provides a system and method for intelligent communication routing within a low-level communication server system.
Summary of The Invention
The summary description of the invention herein provides disclosure of a number of embodiments of the invention. Language describing one embodiment or set of embodiments is not intended to, and does not, limit or constrain the scope of other embodiments of the invention. Therefore, it allows replacement or supplementation of telephone numbers, IP addresses, e-mail addresses and the like, to identify targets accessible by the system with high-level definitions, which are contextually interpreted at the time of communications routing, to appropriately direct the communication. Therefore, the target of a communication is defined by an algorithm, rather than a predetermined address or simple rule, and the algorithm evaluated in real time for resolution of the target, to deliver the communication or establish a real or virtual channel.
Alternately, the intelligence of the server may be used to implement telephony or computer-telephony integration features, other than destination or target. Therefore, according to the present invention, communications are, or may be, routed or other telecommunications features implemented, inferentially or intelligently, at a relatively low level within the communications management architecture. For example, in a call center, the software system which handles virtual or real circuit switching and management resolves the destination using an algorithm or the like, rather than an unambiguous target.
An embodiment according to the present invention, the control over switching in a circuit switch is partitioned together with intelligent functions.
Intelligent functions include, for example, but are not limited to, optimizations, artificial neural network implementation, probabilistic and stochastic process calculations, fuzzy logic, Bayesian logic and hierarchical Markov models (HMMs), or the like.
A particularly preferred embodiment provides a skill-based call automatic call director for routing an incoming call in a call center to an appropriate or optimal agent. While skill-based routing technologies are known in the art, the intelligence for routing the call is separate from the voice routing call management system. Thus, the prior art provides a separate and distinct process, and generally a separate system or partition of a system, for evaluation of the skill-based routing functionality. For example, while the low-level voice channel switching is performed in a PBX, the high-level policy management is often performed in a separate computer system, linked to the PBX through a packet switched network and/or bus data link.
The present invention, however, integrates evaluation of intelligent aspects of the control algorithm with the communications management. This integration therefore allows communications to be established based on an inferential description of a target, rather than a concrete description, and allows a plurality of considerations to be applied, rather than a single unambiguous decision rule.
Brief Description of Drawings
FIG. 1 shows a first flow chart showing a skill routing method according to the present invention.
Detailed Description of Invention
FIG. 1 shows a flow chard of an incoming call routing algorithm according to a preferred embodiment of the present invention. A call is placed by a caller to a call center. The call is directed, through the public switched telephone network, although, calls or communications may also be received through other channels, such as the Internet, private branch exchange, intranet VOIP, etc. The source address of the call, for example the calling telephone number, IP address, or other identifier, is received to identify the caller. While the call is in the waiting queue, this identifier is then used to call up an associated database record, providing, for example, a prior history of interaction, a user record, or the like. The call waiting queue may be managed directly by the telephony server. In this case, since the caller is waiting, variable latencies due to communications with a separate call management system would generally not interfere with call processing, and therefore may be tolerated. In other instances, an interactive voice response (IVR) system may be employed to gather information from the caller during the wait period.
In some instances, there will be no associated record, or in others, the identification may be ambiguous or incorrect. For example, a call from a PBX wherein an unambiguous caller extension is not provided outside the network, a call from a pay phone, or the like. Therefore, the identity of the caller is then confirmed using voice or promoted DTMF codes, which may include an account number, transaction identifier, or the like, based on the single or ambiguous records.
During the identity confirmation process, the caller is also directed to provide certain details relating to the purpose of the call. For example, the maybe directed to “press one for sales, two for service, three for technical support, four for returns, and five for other”. Each selected choice, for example, could include a further menu, or an interactive voice response, or an option to record information. The call-related information is then coded as a call characteristic vector. This call characteristic is either generated within, or transmitted to, the communications server system. Each agent has a skill profile vector. This vector is developed based on various efficiency or productivity criteria. For example, in a sales position, productivity may be defined as sales volume or gross profits per call or per call minute, customer loyalty of past customers, or other appropriate metrics. In a service call, efficiency may be defined in terms of minutes per call, customer loyalty after the call, customer satisfaction during the call, successful resolution of the problem, or other metrics. These metrics may be absolute values, or normalized for the agent population, or both. The skill profile vector is stored in a table, and the profiles, which may be updated dynamically, of available or soon to be available agents, are accessed from the table (database).
Typically, the table is provided or updated by a high-level call center management system to the communications server system as the staffing assignments change, for example once or more per shift. Intra-shift management, such as scheduling breaks, may be performed at a low or high level.
The optimization entails analysis of various information, which may include the caller characteristics, the call incident characterization, availability of agents, the agent profile(s), and/or various routing principles. According to the present invention, the necessary information is made directly available to the communications server, which performs an optimization to determine a “best” target, e.g., agent selection, for the caller.
For example, if peak instantaneous efficiency is desired, for example when the call center is near capacity, more advanced optimizations may be bypassed and a traditional skill-based call routing algorithm implemented, which optimizes a short-term cost-utility function of the call center. An agent who can “optimally” handle the call is then selected, and the call routed to that agent. The global (e.g., call center) factors may be accounted as a separate set of parameters.
Thus, in order to immediately optimize the call routing, the general principle is to route the call such that the sum of the utility functions of the calls be maximized while the cost of handling those calls be minimized. Other types of optimizations may, of course, be applied. According to one optional aspect of the invention, the various routing principles discussed above explicitly value training as a utility of handling a call, and thus a long-term optimization is implemented. The utility of caller satisfaction is also weighted, and thus the agent selected is generally minimally capable of handling the call. Thus, while the caller may be somewhat burdened by assignment to a trainee agent, the call center utility is maximized over the long term, and call center agents will generally increase in skill rapidly.
For the communications server system to be able to include these advanced factors, they must be expressed in a normalized format, such as a cost factor. As for the cost side of the optimization, the cost of running a call center generally is dependent on required shift staffing, since other costs are generally constant. Accordingly, a preferred type of training algorithm serves to minimize sub-locally optimal call routing during peak load periods, and thus would be expected to have no worse cost performance than traditional call centers. However, as the call center load is reduced, the call routing algorithm routes calls to trainee agents with respect to the call characteristics. This poses two costs. First, since the trainee is less skilled than a fully trained agent, the utility of the call will be reduced. Second, call center agent training generally requires a trainer be available to monitor and coach the trainee.