US20050187913A1 - Web-based customer service interface - Google Patents

Abstract

A system and method for processing a web-based query is provided. The system comprises a web server for transmitting a web form having a text field box for entering a natural language query, and a language analysis server for extracting concepts from the natural language query and classifying the natural language query into predefined categories via computed match scores based upon the extracted concepts and information contained within an adaptable knowledge base. In various embodiments, the web server selectively transmits either a resource page or a confirmation page to the client, based upon the match scores. The resource page may comprise at least one suggested response corresponding to at least one predefined category. The language analysis server may adapt the knowledge base in accordance with a communicative action received from the client after the resource page is transmitted.

Description

CROSS-REFERENCE TO RELATED APPLICATION
• This application claims the priority and benefit of U.S. Provisional Patent Application Ser. No. 60/468,576 entitled “Web-Based Customer Service Interface,” filed on May 6, 2003, which is hereby incorporated by reference. This application is related to patent application Ser. No. ______, entitled, “System and Method for Electronic Communication Management,” herein incorporated by reference, filed on an even date herewith.
BACKGROUND OF THE INVENTION
• 1. Field of the Invention
• This invention relates generally to electronic communications and relates more particularly to a system and method for a web-based customer service interface.
• 2. Description of the Background Art
• In a typical organization, communications with customers and others may occur via a variety of different channels. In addition to traditional channels such as letters and telephone calls, customers may also communicate with an organization via electronic mail, facsimile, web-based forms, web-based chat, and wireless communication and voice. An organization will most likely incorporate these and any other newly developed communication channels to allow customers to communicate in a way they find most convenient.
• Many of the communication channels mentioned above contain information that is unstructured in nature, usually expressed in natural language. Different customers may make identical requests each in a unique way, using different communication channels, different words and expressions, or both. Human agents are usually required to review each natural language communication to evaluate the customer's intent, and to determine what information or action would be responsive to that intent.
• Agents typically must look to various sources to gather all of the information required to respond appropriately to a customer communication. The information may be retrieved from a variety of sources, such as legacy systems, databases, back office systems, and front office systems. Each of these sources may store data in a unique structure or format. An agent typically gathers and organizes the required information from one or more of these information sources and uses the information to compose an appropriate content-rich reply that is responsive to the customer's intent.
• Utilizing people to respond to customer communications is often inefficient. In addition, an increase in the number of communications received by an organization typically requires an even larger increase in the number of people required to provide an acceptable level of customer service.
• Several types of automatic systems exist for responding to customer communications. Rule-based systems, keyword-based systems, and statistical systems typically do not perform with the necessary accuracy to substantially automate business processes, such as responding to customer inquiries, and require a large investment in resources to keep them up-to-date. Many learning systems utilize a training set of data that is a poor representation of the system's world, which reduces the accuracy of the system and makes the process of updating the system very cumbersome.
SUMMARY OF THE INVENTION
• The present invention provides a system and method for processing a web-based query. In one embodiment of the invention, the system comprises a web server for transmitting a web form having at least one text field box for entering a natural language query to a client, and a language analysis server for analyzing the natural language query and optional meta-data received from the client to classify the natural language query into at least one predefined category based on information contained within a knowledge base. The web server is further configured to selectively transmit a resource page to the client, where the resource page includes at least one suggested response and optionally other data corresponding to at least one predefined category. In addition, the web server is further configured to receive a communicative action from the client after the resource page is transmitted, wherein the language analysis server may adapt the knowledge base in accordance with the communicative action.
• In one embodiment of the invention, the language analysis server classifies the natural language query into predefined categories based on computed match scores, where each match score corresponds to one of the predefined categories. Furthermore, each match score is representative of a confidence level that the natural language query is relevant to a corresponding predefined category. The language analysis server calculates each match score based upon a comparison of concepts extracted from the natural language query to concepts associated with the predefined categories. Each match score is representative of a statistical likelihood of the natural language query being correctly classified to the corresponding predefined category.
• In another embodiment of the invention, the language analysis server routes the natural language query to an agent based upon an analysis of the computed match scores according to a predetermined logic (e.g., if none of the computed match scores meet a predetermined threshold level). In yet another embodiment, the language analysis server transmits a solution page to the client based upon an analysis of the computed match scores according to the predetermined logic (e.g., if at least one match score meets a predetermined high-threshold level).
• In accordance with the invention, the method comprises transmitting a web page having at least one user-interactable element for entering a natural language query and optional meta-data to a client, receiving the natural language query and the optional meta-data, analyzing the natural language query to classify the natural language query into at least one predefined category using information contained within a knowledge base, and selectively transmitting a resource page to the client. The resource page includes at least one suggested response and optionally other data corresponding to at least one predefined category.
BRIEF DESCRIPTION OF THE DRAWINGS
• FIG. 1 is an exemplary block diagram of a customer service network for processing an electronic query, according to one embodiment of the invention;
• FIG. 2 is an exemplary embodiment of the customer service interface illustrated inFIG. 1, according to one embodiment of the invention;
• FIG. 3A illustrates an exemplary embodiment of a contact-us page, according to the invention;
• FIG. 3B illustrates an exemplary embodiment of the drop-down box component illustrated inFIG. 3A, according to one embodiment of the invention;
• FIG. 3C illustrates an exemplary embodiment of the text field box illustrated inFIG. 3A, according to one embodiment of the invention;
• FIG. 4 illustrates one embodiment of the language analysis server illustrated inFIG. 2, according to one embodiment of the invention;
• FIG. 5 illustrates an exemplary communication-flow diagram for processing an electronic query as implemented by the customer service network illustrated inFIG. 1, according to one embodiment of the invention; and
• FIG. 6 illustrates exemplary method steps for processing an electronic query, according to one embodiment of the invention.
DETAILED DESCRIPTION
• FIG. 1 is an exemplary block diagram of acustomer service network100 for processing an electronic query, according to one embodiment of the present invention. Thecustomer service network100 comprises aclient105, a network110 (e.g., the Internet), and acustomer service interface115. Theclient105 may comprise abrowser120 for browsing Internet web sites. According to one embodiment of the invention, thecustomer service interface115 receives, classifies, and automatically responds to electronic queries submitted by theclient105 via thenetwork110. Thecustomer service interface115 is discussed further below in conjunction withFIG. 2.
• FIG. 2 is an exemplary embodiment of thecustomer service interface115 illustrated inFIG. 1, according to one embodiment of the invention. Thecustomer service interface115 comprises aserver205, alanguage analysis server210, and aknowledge base215. In an alternate embodiment, thelanguage analysis server210 and theknowledge base215 may be integrated in a single module. Theserver205 preferably comprises a web-server220 for providing web services to the client105 (FIG. 1). For example, the web-server220 may submit a contact-us page to theclient105. The contact-us page allows a user to address an electronic query to thecustomer service interface115, and is discussed further below in conjunction withFIGS. 3A-3C. In addition, theserver205 utilizes ascript225 for processing communications (i.e., queries) from theclient105. Thescript205 may be any configurable or non-configurable mechanism for routing information between various components of thecustomer service interface115. The communications received by theserver205 contain data or information that is structured and unstructured in nature. For example, the communications typically contain unstructured information expressed in natural language. Each individual client correspondent may compose a communication in a unique way, even when requesting the same type of information from thecustomer service interface115. In addition, the communications may contain structured information, such as meta-data associated with the communication, and queries in which the client correspondent selects structured text displayed in drop-down menu boxes. Meta-data may additionally include, for example, information not explicitly provided by the client correspondent, and information regarding client correspondent attributes accessible to thecustomer service interface115. In one embodiment of the invention, thescript225 parses the received communications, and sends the parsed information to thelanguage analysis server210 for further analysis.
• Thelanguage analysis server210 analyzes and classifies the electronic query comprising any combination of natural language text, structured text, and structured data (e.g., meta-data) into predefined categories stored in theknowledge base215, based upon linguistic modeling rules and concepts associated with the predefined categories. In one embodiment, thelanguage analysis server210 linguistically analyzes the query based upon content and context of the query, and classifies the query to one or more of the predefined categories stored in theknowledge base215 based upon a match score derived from a statistical comparison of concepts extracted from the query to concepts associated with the one or more predefined categories. In another embodiment, thelanguage analysis server210 analyzes the query (i.e., extracts concepts from the query) to match the query to the one or more predefined categories using standard search techniques. Thelanguage analysis server210 is discussed further below in conjunction withFIG. 4.
• Theknowledge base215 is a branching network of nodes arranged in a vertically structured hierarchy (i.e., tree hierarchy) that represent the various predefined categories. Logically related predefined categories are associated with a branch, which in turn may be associated with a branch of larger scope. Creation of the hierarchies can be either manual (via a configuration tool or an API), automatic by monitoring feedback received via theclient105 or an agent, or a combination, whereby an automatic tool displays suggestions according to performance of thecustomer service interface115. A user may then create the hierarchies based upon the suggestions. Theknowledge base215 may also include flat hierarchies as a special case of tree hierarchies. An embodiment of thelanguage analysis server210 and theknowledge base215 are discussed in more detail in patent application Ser. No. ______, entitled, “System and Method for Electronic Communication Management,” herein incorporated by reference, filed on an even date herewith.
• FIG. 3A illustrates an exemplary embodiment of a contact-us page310, as composed by the customer service interface115 (FIG. 2) and transmitted to the client105 (FIG. 1) via the network110 (FIG. 1). The contact-us page310 may include aselectable text box320 and atext field box330 for insertion of natural language text. In other embodiments, the contact-us page310 comprises multiple fields.
• FIG. 3B illustrates an exemplary embodiment of theselectable text box320 illustrated inFIG. 3A, according to one embodiment of the invention. Theselectable text box320 may include a plurality of drop-down boxes322 that comprise predefined questions or statements, selectable by a user. For example, if thecustomer service interface115 services a financial institution, then the drop-down boxes322 may include statements corresponding to customer service issues such as loans, new accounts, PIN numbers, monetary transfers, among others.
• FIG. 3C illustrates an exemplary embodiment of thetext field box330 illustrated inFIG. 3A, according to one embodiment of the invention. Thetext field box330 comprises a selectable area in which the user may compose a natural language message to thecustomer service interface115. For example, the user may not be able to access an electronic application for financial aid, partially completed and saved on a server of the financial institution during a previous session. The user may compose a message in thetext field box330, comprising, for example, “A PIN number was sent to me when I electronically applied for financial aid. However, that PIN number does not allow me access to my financial aid account. Could you please rectify the situation?” As described in more detail below in conjunction withFIGS. 5-6, thecustomer service interface115 classifies and responds to the message, either via a list of suggested responses, a direct link to a “solutions page,” or a confirmation page to the client that the query is being routed to an agent for further analysis.
• FIG. 4 illustrates one embodiment of thelanguage analysis server210 as illustrated inFIG. 2, according to one embodiment of the invention. Thelanguage analysis server210 comprises amodeling application410 and alanguage modeling engine415. The modeling application serves as an interface to theserver205 for receiving and transmitting communications. In addition, themodeling application410 may compare match scores (computed by thelanguage modeling engine415 in classifying the query to predefined categories) with various predefined threshold scores to determine the nature of the automated response to theclient105. The basis of the automated response to the client's query is discussed below in further detail in association withFIGS. 5-6.
• Thelanguage modeling engine415 analyzes and classifies natural language text, structured text, and meta-data into predefined categories stored in theknowledge base215. For example, thelanguage modeling engine415 analyzes the text and the meta-data by application of linguistic and morphological models to extract concepts. Thelanguage modeling engine415 then computes match scores based upon a comparison of the extracted concepts with rules and concepts associated with the predefined categories stored in theknowledge base215. The computation of the match scores and further details of theknowledge base215 are discussed below in conjunction withFIGS. 5-6.
• FIG. 5 is an exemplary communication-flow diagram for processing an electronic query as implemented by thecustomer service network100 illustrated inFIG. 1, according to one embodiment of the invention. First, the web-server220 (FIG. 2) serves a contact-us page310 (FIG. 3A) to the client105 (FIG. 1) via acommunication510. Theclient105 responds to the contact-us page310 via acommunication512. For example, theclient105 may respond to the contact-us page310 (hereinafter referred to as a client query, or simply a query) by selecting specific choices displayed in the drop-down boxes322 (FIG. 3B), by composing a natural language text in the text field box330 (FIG. 3C), or both. The web-server220 receives the client query and routes the query to the script225 (FIG. 2). Thescript225 processes the query, and routes the query to the language analysis server210 (FIG. 2) via acommunication514.
• Thelanguage analysis server210 linguistically and/or morphologically analyzes the query based upon content and context of the query, and classifies the query to one or more of the predefined categories stored in the knowledge base215 (FIG. 2) via acommunication516. In one embodiment of the invention, thelanguage analysis server210 classifies the query into the one or more predefined categories based upon a match score derived from a statistical comparison of concepts extracted from the query to concepts associated with the one or more predefined categories. Thelanguage analysis server210 may utilize meta-data in addition to conceptual data extracted from the query to classify the query to the one or more predefined categories. For example, meta-data includes peripheral data not typically associated with content of the query (i.e., with the natural language text and/or drop-down box selections). For example, if the customer service interface115 (FIG. 2) services a financial institution, then the peripheral data may include user name, user account number, or customer service plan afforded the user. In accordance with a preferred embodiment of the invention, thelanguage analysis server210 comprises classification techniques as disclosed in patent application Ser. No. ______, entitled, “System and Method for Electronic Communication Management,” herein incorporated by reference, filed on an even date herewith. However, the scope of the present invention covers standard classification techniques well known in the art.
• In one embodiment of the invention, thelanguage analysis server210 computes, for each predefined category, a match score based upon concepts associated with the predefined categories, concepts extracted from the query, and metadata. In an exemplary embodiment of the invention, suppose that thecustomer service interface115 services a motorcycle parts and equipment distribution house. Additionally, suppose that theknowledge base215 has the following three predefined categories: a first predefined category entitled “new parts order,” a second predefined category entitled “complaints,” and a third predefined category entitled “suggestions.” A client correspondent submits to the server205 a query comprising a natural language text that states, for example, “I am unhappy with the head gasket that you shipped me for my 1955 BMW R50/2. The surface of the replacement gasket is cross-hatched (unlike the original), leading to reduced power and oil leakage. Please either refund my purchase, credit my account or send me the correct gasket.” In response to this query, thelanguage analysis server210 computes a first, a second, and a third match score in classifying the query to the first, the second, and the third predefined categories, respectively, where the second match score is greater than the first match score, and the first match score is greater than the third match score. For example, the second match score may be 95, the first match score may be 42, and the third match score may be 16.
• In one embodiment of the invention, each of the predefined categories has a corresponding resource, or linked suggested response in theknowledge base215, and the relative values of the computed match scores are indicative of a level of confidence of the corresponding suggested responses to answer the query or of the relevancy of the resource to the query. For example, the second match score of 95 (relative to the first and third match scores of 42 and 16, respectively) indicates that the query is more likely to be resolved by the suggested response associated with the second predefined category than the suggested responses associated with the first or third predefined categories.
• Next, thelanguage analysis server210 sends the suggested responses and corresponding match scores to theserver205 via acommunication518. In one embodiment of the invention, thecustomer service interface115 is configured to respond to thecommunication518 via either a first set of communications (i.e.,communications520,522, and524) or a second set of communications initiated by acommunication526, depending upon the corresponding match scores as described below.
• If each of the corresponding match scores is less than a predetermined threshold score (where each predefined category may have a different predetermined threshold score), or based upon an analysis of the match scores according to a predetermined logic, then thecustomer service interface115 responds via the first set of communications. The predetermined logic includes any functional analysis of the match scores, exemplary embodiments of which include, but are not limited to, computations of an average match score, a median match score, a match score standard deviation, or other types of statistical and/or numerical functional analyses. In an exemplary embodiment of the first set of communications, theserver205 sends a confirmation page to theclient105 via acommunication520. The confirmation page informs theclient105 that the query will be routed to an agent for further analysis. Thecommunication520 may comprise additional information such as when theclient105 may expect to receive a reply from the agent, for example. In addition, thelanguage analysis server210 routes the query to the agent for further analysis via acommunication522. The agent may then reply to the client's query, preferably via an electronic message. However the agent may also respond to the query via alternate communication channels, such as a telephone, a Web-based reply, or other means of electronic communication. Optionally, thelanguage analysis server210 may analyze the agent's reply, and, based upon the analysis, update theknowledge base215 via acommunication524.
• If, however, at least one of the corresponding match scores received by theserver205 via thecommunication518 is greater than or equal to the predetermined threshold score (also referred to as a predetermined threshold level), then thecustomer service interface115 responds with thecommunication526. In one embodiment of the invention, thecommunication526 comprises a solution page. Thecommunication526 comprises a solution page when at least one of the computed match scores has a very high value. Alternatively, thecustomer service interface115 may respond with thecommunication526 that comprises the solution page based upon an analysis of the match scores according to the predetermined logic as described above. For example, if thecustomer service interface115 services a financial institute, a client correspondent may submit a query to theserver205 via thecommunication512 that recites, “I want to change my password.” If thecustomer service interface115 classifies the query to a “change password” predefined category with a high degree of certainty (e.g., thecustomer service interface115 classifies the query to the “change password” predefined category with a match score the meets a predetermined high-threshold score), then theserver205 sends the client105 a “password changing” web page (i.e., the solution page). In another embodiment, theserver205 re-directs theclient105 to the solution page corresponding to the “password changing” web page. Theclient105 may then utilize the solution page to resolve the query.
• In another embodiment of the invention, thecommunication526 may comprise a resource page. For example, theserver205 sends the resource page to theclient105 comprising the suggested responses having corresponding match scores greater than or equal to the predetermined threshold level via thecommunication526. The resource page may also comprise other data (such as links to web resources) having corresponding match scores greater than or equal to the predetermined threshold level. In one embodiment of the invention, theclient105 may utilize one of several communicative actions (i.e.,communicative actions528,534, or540) to respond to the resource page.
• For example, theclient105 may select a suggested response on the resource page, respond to an embedded form on the resource page, or click on a link to a web resource, via a firstcommunicative action528. The firstcommunicative action528 is received and processed by theserver205, and theserver205 then routes the processed first communicative action to thelanguage analysis server210 for linguistic analysis via acommunication530. Thelanguage analysis server210 may optionally update theknowledge base215 via acommunication532 based upon the linguistic analysis of the firstcommunicative action528.
• Alternatively, theclient105 may respond to the resource page via a secondcommunicative action534. The secondcommunicative action534 comprises a non-response to the resource page. More specifically, theclient105 does not respond to the resource page (i.e., the client is non-responsive). For example, in one embodiment of the invention, if theclient105 does not respond to the resource page within a given time limit, or if theclient105 disconnects from theserver205, for example, the secondcommunicative action534 comprising a non-response is sent to theserver205. Theserver205 then sends acommunication536 to thelanguage analysis server210 indicating the non-response. Thelanguage analysis server210 may update theknowledge base215 based upon the non-responsiveness of theclient105 via anoptional communication538.
• As an additional alternative, theclient105 may respond to the resource page via a thirdcommunicative action540 comprising a communicative escalation. For example, theclient105 may select (e.g., by mouse-clicking) a “request for help” button embedded in the resource page, or request more information regarding a particular suggested response. Theserver205 receives the thirdcommunicative action540 comprising the communicative escalation, and routes the communicative escalation to thelanguage analysis server210 via acommunication542. Thelanguage analysis server210 then sends the communicative escalation to the agent for further analysis via acommunication544. Thelanguage analysis server210 may optionally update theknowledge base215 based upon the agent's reply to the communicative escalation via acommunication546.
• FIG. 6 illustrates exemplary method steps for processing an electronic query, according to one embodiment of the invention. Instep610, the client105 (FIG. 1) submits an electronic query to a web-site. In one embodiment, the query may be in response to a page served to theclient105 by the web-server220 (FIG. 2) associated with the web site. Theclient105 may be running the browser120 (FIG. 1) to view the page served by the web-server220. Next, instep615, the server205 (FIG. 2) intercepts and routes the query. For example, theserver205 may run the script225 (FIG. 2) that processes the query and routes the processed query to the language analysis server210 (FIG. 2).
• Instep620, thelanguage analysis server210 analyzes the query using the language modeling engine415 (FIG. 4) and the knowledge base215 (FIG. 2) to compute match scores and classify the query to predefined categories stored in theknowledge base215 based upon the match scores, where each predefined category is associated with a suggested response. In one embodiment of the invention, theknowledge base215 is configured as a rule-oriented/concept-oriented database. For example, theknowledge base215 may comprise a plurality of nodes configured in a hierarchically structured branching network, where each node is configured as either a rule-oriented or a concept-oriented node. Each concept-oriented node is typically associated with a predefined category. In one embodiment of the invention, thelanguage analysis server210 utilizes a statistical process to compute the match scores. For example, thelanguage modeling engine415 analyzes the natural language text of the query to generate concepts associated with the query. Thelanguage modeling engine415 then statistically compares the query-derived concepts with rules associated with the rule-oriented nodes and with concepts associated with the concept-oriented nodes stored in theknowledge base215. Thelanguage modeling engine415 then computes a match score for one or more concept-oriented nodes (i.e., for one or more predefined categories). In one embodiment, a high match score for a particular predefined category indicates that a suggested response corresponding to the predefined category is more likely to be a correct response than a suggested response corresponding to a predefined category with a low match score. Based upon the computed match scores, the modeling application410 (FIG. 4) determines if the query meets any of the predetermined threshold levels for an automated response.
• For example, if each match score associated with each predefined category is less than a corresponding predetermined threshold level, then instep625, themodeling application410 routes the query to an agent for further analysis. Preferably, the agent is a human agent. However, in alternate embodiments, the agent may be an automated service, such as an automated phone service or an automated computer system. Next, instep630, theserver205 sends the client105 a confirmation page. In one embodiment, the confirmation page comprises a communication confirming that the client's query is being routed to the agent for further analysis. Next, instep635, the agent replies to the query. In one embodiment of the invention, the agent replies to theclient105 via an electronic mail system. However, the scope of the present invention covers alternate agent-reply methods, such as web-based, telephonic, or facsimile methods.
• Next, inoptional step640, thelanguage analysis server210 processes the agent's reply to the client to generate agent-based feedback. Thelanguage analysis server210 may then update theknowledge base215 based upon the agent-based feedback. The agent-based feedback may comprise positive or negative feedback. Thelanguage analysis server210 uses the feedback to modify the knowledge base. For example, thelanguage analysis server210 may modify concepts, add new concepts, eliminate concepts, or modify weights assigned to different concepts associated with concept-oriented nodes. Thelanguage analysis server210 may also modify relationships between nodes, such as structural relationships defined by branching structures, for example. In alternate embodiments, thelanguage analysis server210 may modify classification rules associated with rule-oriented nodes stored in theknowledge base215.
• Referring back to step620, if at least one match score associated with at least one predefined category is greater than or equal to a corresponding predetermined threshold level, then instep645, theserver205 submits a resource page to theclient105. The resource page may comprise a suggested response page, where each suggested response corresponds to a predefined category with an associated match score greater than or equal to the corresponding threshold level. A suggested response may include a message that recites, for example, “no response was found.” Alternatively, if an associated match score is greater than or equal to a corresponding high-threshold level, then the resource page comprises a solution page that provides either a link or a web page to theclient105 that may directly resolve the query. Each predefined category may have different threshold levels and high-threshold levels. Next, instep650, theclient105 responds to the resource page and theserver205 determines whether the client query is resolved based upon the client response. In one embodiment of the invention, the query is not resolved if theclient105 escalates (e.g., theclient105 responds with a request for help), and the process then continues atstep625.
• However, if instep650 the query is resolved, then inoptional step655, thelanguage analysis server210 receives client-based feedback (i.e., feedback based upon the client's response). In one embodiment of the invention, the query is considered resolved if theclient105 selects a suggested response, or if theclient105 does not select any response (i.e., theclient105 is non-responsive).
• Inoptional step655, thelanguage analysis server210 updates theknowledge base215 based upon the client-based feedback. For example, a selection of a suggested response corresponding to a high match score generates a positive client-based feedback that may strengthen the concept-oriented nodes of theknowledge base215 that generated the suggested responses. In one embodiment of the invention, a concept-oriented node may be strengthened by redistributing weights assigned to concepts associated with the node. However, if theclient105 selects a suggested response corresponding to a low match score, then theclient105 generates negative client-based feedback that may modify the concept-oriented nodes and branching structures that generated the selected suggested response.
• The present invention has been described above with reference to exemplary embodiments. Other embodiments will be apparent to those skilled in the art in light of this disclosure. The present invention may readily be implemented using configurations other than those described in the exemplary embodiments above. Therefore, these and other variations upon the exemplary embodiments are covered by the present invention.

Claims (22)

1. A system for processing a web-based query, comprising:

a web server for transmitting a web form to a client, the web form having at least one user-interactable element by which a user enters a natural language query and optional meta-data;

a language analysis server, coupled to the web server, for analyzing the natural language query and the optional meta-data to classify the natural language query into at least one predefined category based on information contained within a knowledge base; and

the web server selectively transmitting a resource page to the client, the resource page including at least one suggested response and optionally other data corresponding to the at least one predefined category.

2. The system ofclaim 1, wherein the web server is further configured to receive a communicative action from the client after the resource page is transmitted, the language analysis server adapting the knowledge base in accordance with the communicative action.

3. The system ofclaim 1, wherein the language analysis server calculates a set of match scores, each match score of the set of match scores corresponding to one predefined category of a plurality of predefined categories and being representative of a confidence level that the natural language query is relevant to the one predefined category of the plurality of predefined categories, and wherein the language analysis server classifies the natural language query into the at least one predefined category based on a match score associated therewith.

4. The system ofclaim 3, wherein the language analysis server calculates each match score of the set of match scores based upon a comparison of concepts extracted from the natural language query to concepts associated with the plurality of predefined categories, and wherein each match score of the set of match scores is representative of a statistical likelihood of the natural language query being correctly classified to the plurality of predefined categories.

5. The system ofclaim 3, wherein the language analysis server routes the natural language query to an agent if none of the match scores of the set of match scores meet a predetermined threshold level.

6. The system ofclaim 5, wherein the web server transmits to the client a confirmation page confirming that the natural language query has been routed to the agent.

7. The system ofclaim 5, wherein the language analysis server updates the knowledge base based upon the agent's response to the natural language query.

8. The system ofclaim 3, wherein the web server transmits a solution page to the client if at least one match score of the set of match scores meet a predetermined high-threshold level.

9. The system ofclaim 3, wherein the web server transmits a solution page to the client based upon an analysis of the set of match scores according to a predetermined logic.

10. The system ofclaim 1, wherein the other data comprises one or more links to web resources.

11. A method for processing a web-based query, comprising:

transmitting a web page to a client, the web page including at least one user-interactable element for entering a natural language query and optional meta-data;

receiving the natural language query and the optional meta-data;

analyzing the natural language query and the optional meta-data to classify the natural language query into at least one predefined category using information contained within a knowledge base; and

selectively transmitting a resource page to the client, the resource page including at least one suggested response and optionally other data corresponding to the at least one predefined category.

12. The method ofclaim 11, further comprising:

receiving a communicative action from the client; and

adapting. the knowledge base in accordance with the communicative action.

13. The method ofclaim 11, further comprising:

calculating a set of match scores, each match score of the set of match scores corresponding to one of a plurality of predefined categories and being representative of a confidence level that the natural language query is relevant to the one of the plurality of predefined categories; and

classifying the natural language query into the at least one predefined category based on a match score associated therewith.

14. The method ofclaim 13, further comprising routing the natural language query to an agent if none of the match scores of the set of match scores meet a predetermined threshold level.

15. The method ofclaim 13, further comprising routing the natural language query to an agent based upon an analysis of the set of match scores according to a predetermined logic.

16. The method ofclaim 15, further comprising transmitting to the client a confirmation page confirming that the natural language query has been routed to the agent.

17. The method ofclaim 15, further comprising updating the knowledge base according to the agent's response to the natural language query.

18. The method ofclaim 13, further comprising transmitting a solution page to the client if at least one match score of the set of match scores meet a predetermined high-threshold level.

19. The method ofclaim 13, further comprising transmitting a solution page to the client based upon an analysis of the set of match scores according to a predetermined logic.

20. The method ofclaim 11, wherein the other data comprises one or more links to web resources.

21. An electronic-readable medium having embodied thereon a program, the program being executable by a machine to perform a method for processing a web-based query, the method comprising:

transmitting a web page to a client, the web page including at least one user-interactable element for entering a natural language query and optional meta-data;

receiving the natural language query and the optional meta-data;

analyzing the natural language query and the optional meta-data to classify the natural language query into at least one predefined category using information contained within a knowledge base; and

selectively transmitting a resource page to the client, the resource page including at least one suggested response and optionally other data corresponding to the at least one predefined category.

22. A method for processing a web-based query, comprising:

means for transmitting a web page to a client, the web page including at least one user-interactable element for entering a natural language query and optional meta-data;

means for receiving the natural language query and the optional meta-data;

means for analyzing the natural language query and the optional meta-data to classify the natural language query into at least one predefined category using information contained within a knowledge base; and

means for selectively transmitting a resource page to the client, the resource page including at least one suggested response and optionally other data corresponding to the at least one predefined category.

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