Abstract:
An automatic timeline and topic normalization mechanism is described along with various methods and systems for administering the same. The temporal correction system proposed herein creates fully interpreted and reordered representations of events within and external to a dialog, reducing the amount of time and expensive resources typically required for reading, comprehension, and response to written communications.

Description:
FIELD OF THE DISCLOSURE 
     The present disclosure is generally directed toward communications and more specifically toward contact centers. 
     BACKGROUND 
     Requests coming into contact centers today may take many forms beyond calls on traditional voice channels. Interactions with customers using channels like email, chat, and social media are increasing in frequency and number. New challenges are posed as the channels often contain long dialogs of information that represent a core dump of information. The core dump may be presented in a confusing and unclear jumble of statements. Furthermore, there may be several dialog turns back and forth between an agent, the customer, and others who may weigh in on a problem. There is no guarantee of order, validity, structure, or relevance of the information contained in these interactions. Because of the free form nature of the interactions, a burden falls on the agent or a supervisor to make sense of a conversation flow every time the agent works on a new work item. 
     Typically, contact center agents and supervisors read previous dialogs to understand the back and forth communications between parties. The agent and the supervisor may use timestamps (e.g., hours, days), keys, and other indicators to understand a timeline of events. Key phrases might include time keywords like “before this,” “after that,” and “then we did,” “before that I noticed” and other indicators that serve as relative time references. Manually parsing all of the information can be time consuming and much of the information may be irrelevant. When the agent is required to manually parse and summarize data from the dialogs, time and efficiency are lost. Additionally, manual parsing and summarizing may lead to customer dissatisfaction as it forces the customer to wait while a new agent and/or supervisor gets up to speed on the problem in real time. 
     SUMMARY 
     These and other needs are addressed by the various aspects, embodiments, and/or configurations of the present disclosure. The present disclosure is directed to an automatic timeline and topic normalization mechanism which presents a contact center agent with a clean, ordered problem set derived from written correspondence between a customer and a contact center. The ordered problem set, in some embodiments, enables a contact center agent or other observer of the interaction to quickly and efficiently assess the interaction history as well as address relevant issues within a free-form work item without taking time to parse and summarize existing communications and/or requiring direct questions back to the customer. 
     In some embodiments, the automatic timeline and topic normalization mechanism uses language analysis technologies to solve the problems above with timeline, relevance, and reordering of the events described. Normalization is one process for evaluating and correcting data that is often used as part of speech recognition in conjunction with other analyses. In some embodiments, key components and/or events within an interaction or communication are identified, dependent attributes are defined, and conversion to normal form takes place. Tight analysis can provide a distinct order: X happened, and then Y happened whereas loose analysis may reveal events in order: it vibrated, glowed, smoked, and then caught on fire. An agent might receive a loose analysis, invoke tight analysis, and ask clarifying questions. An additional analysis might include tying the events back to a company or contact center database: a technician came, and then I called in. An optional analysis might include tying outages and issues back to external events that can be used to order events within a communication: tornado hit that day at 6:45 PM. 
     A way to add clarity to a jumble of information is to apply temporal normalization of a customer&#39;s language. When a customer explains his or her problem, the problem may be delivered as a stream of consciousness narrative rather than a linear sequence through the steps that lead to the current state and/or issue. For example, someone might give a long explanation about the steps taken to debug a problem with his service, and subsequently say, “...and before all that we had a power outage.” Presenting the agent with a normalized timeline account of the events described by the customer in concert with other analyses can help the agent quickly understand the current status of a customer&#39;s problem and respond appropriately. 
     The automatic timeline and topic normalization mechanism, in some embodiments, is capable of identifying actionable, past actionable, and irrelevant spans in customer-to-business conversations. This form of summarization can be done by organizing, in time, some or all events and/or steps in a customer-to-business conversation. In addition, the topic normalization mechanism can be adapted to account for the relevance of each event or step to the goal of the agent, supervisor, and/or contact center, highlight important steps, and depreciate and/or omit irrelevant steps in order to allow the agent to focus on information the agent can take action on versus the information that is superfluous and/or irrelevant. Removal of irrelevant items is a part of the temporal reorder through the process of simplification. 
     The use of language analyses to temporally reorder meandering communication from customers to a company or contact center reduces the amount of time and resources required for reading, comprehension, and response to written communications. 
     These and other advantages will be apparent from the disclosure. 
     In some embodiments, a method is provided that generally comprises:
         receiving a message containing a plurality of message elements in a first order;   determining that the plurality of message elements are not in a proper temporal order when in the first order;   in response to determining that the message element are not in a proper temporal order, identifying a second order for the plurality of message elements; and   presenting the plurality of message elements in the second order via a user interface of a communication device.       

     The term “automatic” and variations thereof, as used herein, refers to any process or operation done without material human input when the process or operation is performed. However, a process or operation can be automatic, even though performance of the process or operation uses material or immaterial human input, if input is received before performance of the process or operation. Human input is deemed to be material if such input influences how the process or operation will be performed. Human input that consents to the performance of the process or operation is not deemed to be “material.” 
     The term “computer-readable medium” as used herein refers to any storage and/or transmission medium that participate in providing instructions to a processor for execution. Such a medium is commonly tangible and non-transient and can take many forms, including but not limited to, non-volatile media, volatile media, and transmission media and includes without limitation random access memory (“RAM”), read only memory (“ROM”), and the like. Non-volatile media includes, for example, NVRAM, or magnetic or optical disks. Volatile media includes dynamic memory, such as main memory. Common forms of computer-readable media include, for example, a floppy disk (including without limitation a Bernoulli cartridge, ZIP drive, and JAZ drive), a flexible disk, hard disk, magnetic tape or cassettes, or any other magnetic medium, magneto-optical medium, a digital video disk (such as CD-ROM), any other optical medium, punch cards, paper tape, any other physical medium with patterns of holes, a RAM, a PROM, and EPROM, a FLASH-EPROM, a solid state medium like a memory card, any other memory chip or cartridge, a carrier wave as described hereinafter, or any other medium from which a computer can read. A digital file attachment to e-mail or other self-contained information archive or set of archives is considered a distribution medium equivalent to a tangible storage medium. When the computer-readable media is configured as a database, it is to be understood that the database may be any type of database, such as relational, hierarchical, object-oriented, and/or the like. Accordingly, the disclosure is considered to include a tangible storage medium or distribution medium and prior art-recognized equivalents and successor media, in which the software implementations of the present disclosure are stored. Computer-readable storage medium commonly excludes transient storage media, particularly electrical, magnetic, electromagnetic, optical, magneto-optical signals. 
     The term “customer” or “client” denotes a party patronizing, serviced by, or otherwise doing business with a contact center, business, or enterprise. 
     The term “language” as used herein refers to any form of expression and/or communication that includes words, signs, symbols, and the equivalents thereof. The expression and/or communication may be in any single language or may include a combination of multiple languages. 
     A “database” as used herein refers to an organized set of data held in a computer. The organization schema or model for the data can, for example, be hierarchical, network, relational, entity-relationship, object, document, XML, entity-attribute-value model, star schema, object-relational, associative, multidimensional, multi-value, semantic, and other database designs. 
     The terms “determine,” “calculate,” and “compute,” and variations thereof as used herein, are used interchangeably and include any type of methodology, process, mathematical operation or technique. 
     The term “means” as used herein shall be given its broadest possible interpretation in accordance with 35 U.S.C., Section 112, Paragraph 6. Accordingly, a claim incorporating the term “means” shall cover all structures, materials, or acts set forth herein, and all of the equivalents thereof. Further, the structures, materials or acts and the equivalents thereof shall include all those described in the summary of the invention, brief description of the drawings, detailed description, abstract, and claims themselves. 
     The term “module” as used herein refers to any known or later developed hardware, software, firmware, artificial intelligence, fuzzy logic, or combination of hardware and software that is capable of performing the functionality associated with that element. Also, while the disclosure is presented in terms of exemplary embodiments, it should be appreciated that individual aspects of the disclosure can be separately claimed. 
     The preceding is a simplified summary of the disclosure to provide an understanding of some aspects of the disclosure. This summary is neither an extensive nor exhaustive overview of the disclosure and its various aspects, embodiments, and/or configurations. It is intended neither to identify key or critical elements of the disclosure nor to delineate the scope of the disclosure but to present selected concepts of the disclosure in a simplified form as an introduction to the more detailed description presented below. As will be appreciated, other aspects, embodiments, and/or configurations of the disclosure are possible utilizing, alone or in combination, one or more of the features set forth above or described in detail below. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG. 1A  is an example of a service chat session in accordance with embodiments of the present disclosure; 
         FIG. 1B  is a reordered and normalized example of a service chat session in accordance with embodiments of the present disclosure; 
         FIG. 2  is a block diagram of a communication system in accordance with embodiments of the present disclosure; 
         FIG. 3  is an example of a service request from a customer through an automatic timeline and topic normalization mechanism in accordance with embodiments of the present disclosure; 
         FIG. 4  is a flow diagram for receiving and manipulating message elements in a dialog in accordance with embodiments of the present disclosure; and 
         FIG. 5  is a data diagram of data that is used by the automatic timeline and topic normalization mechanism in accordance with embodiments of the present disclosure. 
     
    
    
     DETAILED DESCRIPTION 
       FIG. 1A  is an illustrative embodiment of a service chat session in accordance with at least some embodiments of the present disclosure. An automatic timeline and topic normalization mechanism in a communication system receives a work item from a customer. The work item can include several message elements, some of which are important and actionable, and some of which are irrelevant. A temporal correction module is operable to receive a first message element  104 , a second message element  108 , a third message element  112 , and a fourth message element  116 . Each of the message elements  104 ,  108 ,  112 ,  116  could be identified in a first order and one or more of the message elements may comprise a plurality of sub-elements having a first sub-order. 
     In some embodiments, the message elements  104 ,  108 ,  112 ,  116  may require reordering from the first order to a second order to provide enhanced delivery and presentation to an agent. Message elements  104 ,  108 ,  112 ,  116  may include events like “product didn&#39;t work” or “product died” as non-limiting examples that can be reordered based on temporal an analysis performed by a temporal correction module. Additionally, the temporal correction module can remove one or more insignificant or non-actionable message elements  104 ,  108 ,  112 ,  116  for efficient summarization where the presentation of a new order of message elements  104 ,  108 ,  112 ,  116  may or may not include all of the message elements  104 ,  108 ,  112 ,  116  from the work item. 
     In a non-limiting example, customer Tim initiates a customer service chat session with a long, monologue-like explanation that includes the following details: 
     Last week, while I was sitting in on my front porch using my router, my power cable came loose and when I plugged it back in, it wouldn&#39;t turn on. This morning it started to work again, but only for a few minutes, and then it died. Actually the cable came loose a month ago as well when I was visiting my parents. It&#39;s still under warranty and I need a replacement now. 
     While the text above is not structured in exact chronological order, temporal analysis can reorder message elements within the customer&#39;s dialog and produce a timeline summary in dialog  100 A. In addition to construction of the timeline, additional analyses can be performed to help the agent to better understand which of the described message elements are relevant and actionable. 
     When Tim says, I was visiting my parents and the cable came loose, the only portion of that event that is important is that the cable came loose. When Tim explains that the router started to work and then died, both events are relevant, but the fact that the router died may be the only actionable part of that event. When Tim writes that the cable came loose and that he plugged it in and the router didn&#39;t work, the only portion that may be actionable is that the router wouldn&#39;t turn on (no longer functional). The system may determine that Tim needs a replacement based on the actionable events in the dialog  100 A. The system can also run a query to the National Weather Service to see if there was any major weather activity that day which the system could optionally insert that might explain Tim&#39;s router outage. 
       FIG. 1B  shows a reordered and normalized example of a service chat session in accordance with embodiments of the present disclosure. The message elements  104 ,  108 ,  112 ,  116  have been reordered both chronologically and logically to  116 ,  104 ,  112 ,  108 . 
     The temporal correction module may also insert one or more external event indicators into the reordered message element timeline. An external event indicator  120  may include, but is not limited to, agent service notes, information on a weather occurrence, time and details regarding a power outage and/or power interruption, flight time and other flight information, and other message elements from a second message. The work item message elements  104 ,  108 ,  112 ,  116  and the external event indicators  120  may be organized to improve agent understanding and handling of the work item. 
     In addition to producing a reordered version of the message elements  104 ,  108 ,  112 ,  116  within the dialog and optionally adding the external event indicator  120 , the system may also generate a complete and temporally reordered set of events  100 B to display to the agent and/or a manager to allow for issue resolution with a high degree of efficiency and customer satisfaction. 
     In a second non-limiting example, Tim&#39;s chat session is routed to a manager as the system has detected the keyword “died,” and Tim explains the problem: 
     My router that you replaced two months ago is broken. I had problems with it when I was visiting my parents and again when I was sitting on the porch. I′m really getting tired of dealing with the flakiness of this particular router. I haven&#39;t had problems with your stuff in the past, so I′m willing to give you one more try before I move on to something else. 
     The temporal correction module may perform an analysis of the message elements in the chat and on the call. The message elements may be removed or placed in order and put on a timeline, including information like “product is broken” and “product wouldn&#39;t turn on.” The timeline display can be updated with the new reordered set of events  100 B with details, helping the manager to better understand the chain of events leading up to the current inquiry. The manager is able to give Tim a richer service experience by echoing back and confirming some of the background and reassuring Tim that he can send him out a new product right away. 
       FIG. 2  depicts a communication system  200  in accordance with at least some embodiments of the present disclosure. The communication system  200  may be a distributed system and, in some embodiments, comprises a communication network  204  connecting one or more customer communication devices  208  to a work assignment mechanism  216 , which may be owned and operated by an enterprise administering a contact center in which a plurality of resources  212  are distributed to handle incoming work items from the customer communication devices  208 . 
     In accordance with at least some embodiments of the present disclosure, the communication network  204  may comprise any type of known communication medium or collection of communication media and may use any type of protocols to transport messages between endpoints. The communication network  204  may include wired and/or wireless communication technologies. The Internet is an example of the communication network  204  that constitutes an Internet Protocol (IP) network consisting of many computers, computing networks, and other communication devices located all over the world, which are connected through many telephone systems and other means. Other examples of the communication network  204  include, without limitation, a standard Plain Old Telephone System (POTS), an Integrated Services Digital Network (ISDN), the Public Switched Telephone Network (PSTN), a Local Area Network (LAN), a Wide Area Network (WAN), a Voice over Internet Protocol (VoIP) network, a Session Initiation Protocol (SIP) network, a cellular network, and any other type of packet-switched or circuit-switched network known in the art. In addition, it can be appreciated that the communication network  204  need not be limited to any one network type, and instead may be comprised of a number of different networks and/or network types. As one example, embodiments of the present disclosure may be utilized to increase the efficiency of a grid-based contact center. Examples of a grid-based contact center are more fully described in U.S. patent application No. 12/469,523, the entire contents of which are hereby incorporated herein by reference. Moreover, the communication network  204  may comprise a number of different communication media such as coaxial cable, copper cable/wire, fiber-optic cable, antennas for transmitting/receiving wireless messages, and combinations thereof 
     The communication devices  208  may correspond to customer communication devices. In accordance with at least some embodiments of the present disclosure, a customer may utilize their communication device  208  to initiate a work item, which is generally a request for a processing resource  212 . Exemplary work items include, but are not limited to, a contact directed toward and received at a contact center, a web page request directed toward and received at a server farm (e.g., collection of servers), a media request, an application request (e.g., a request for application resources location on a remote application server, such as a SIP application server), and the like. The work item may be in the form of a message or collection of messages transmitted over the communication network  204 . For example, the work item may be transmitted as a telephone call, a packet or collection of packets (e.g., IP packets transmitted over an IP network), an email message, an Instant Message, an SMS message, a fax, and combinations thereof 
     The work assignment mechanism  216  may employ any queue-based or queueless work assignment algorithm. Examples of queue-based work assignment skill-based algorithms include, without limitation, a fairness algorithm, pacing algorithm (which inserts rests into the agents work queue), value-based algorithms, limited algorithms (such as Business Advocate™ by Avaya, Inc.), and outsourcing algorithms. Other algorithms may consider other types of data inputs and/or may treat certain data inputs differently. 
     The format of the work item may depend upon the capabilities of the communication device  208  and the format of the communication. In particular, work items are logical representations within a contact center of work to be performed in connection with servicing a communication received at the contact center (and more specifically the work assignment mechanism  216 ). The communication may be received and maintained at the work assignment mechanism  216 , a switch or server connected to the work assignment mechanism  216 , or the like until a resource  212  is assigned to the work item representing that communication at which point the work assignment mechanism  216  passes the work item to a routing engine  224  to connect the communication device  208  to the assigned resource  212 . 
     Although the routing engine  224  is depicted as being separate from the work assignment mechanism  216 , the routing engine  224  may be incorporated into the work assignment mechanism  216  or its functionality may be executed by the work assignment engine  220 . 
     In accordance with at least some embodiments of the present disclosure, the communication devices  208  may comprise any type of known communication equipment or collection of communication equipment. Examples of a suitable communication device  208  include, but are not limited to, a personal computer, laptop, tablet, cellular phone, smartphone, telephone, or combinations thereof. In general, each communication device  208  may be adapted to support video, audio, text, and/or data communications with other communication devices  208  as well as the processing resources  212 . The type of medium used by the communication device  208  to communicate with other communication devices  208  or processing resources  212  may depend upon the communication applications available on the communication device  208 . 
     In accordance with at least some embodiments of the present disclosure, the work item can be sent toward a collection of processing resources  212  via the combined efforts of the work assignment mechanism  216  and routing engine  224 . The resources  212  can either be completely automated resources (e.g., Interactive Voice Response (IVR) units, processors, servers, or the like), human resources utilizing communication devices (e.g., human agents utilizing a computer, telephone, laptop, etc.), or any other resource known to be used in contact centers. 
     As discussed above, the work assignment mechanism  216  and resources  212  may be owned and operated by a common entity in a contact center format. In some embodiments, the work assignment mechanism  216  may be administered by multiple enterprises, each of which has their own dedicated resources  212   a - n  connected to the work assignment mechanism  216 . 
     In some embodiments, the work assignment mechanism  216  comprises a work assignment engine  220  which enables the work assignment mechanism  216  to make intelligent routing decisions for work items. In some embodiments, the work assignment engine  220  may be configured to administer and make work assignment decisions in a queueless contact center, as is described in U.S. patent application Ser. No. 12/882,950, the entire contents of which are hereby incorporated herein by reference. 
     More specifically, the work assignment engine  220  can determine which of the plurality of processing resources  212  is qualified and/or eligible to receive the work item and further determine which of the plurality of processing resources  212  is best suited (or is the optimal processing resource) to handle the processing needs of the work item. In situations of work item surplus, the work assignment engine  220  can also make the opposite determination (i.e., determine optimal assignment of a work item resource to a resource). In some embodiments, the work assignment engine  220  can be configured to achieve true one-to-one matching by utilizing bitmaps/tables and other data structures. 
     The work assignment engine  120  may reside in the work assignment mechanism  116  or in a number of different servers or processing devices. In some embodiments, cloud-based computing architectures can be employed whereby one or more components of the work assignment mechanism  116  are made available in a cloud or network such that they can be shared resources among a plurality of different users. 
     In accordance with at least some embodiments of the present disclosure, a temporal correction module  228  comprises a web-based user interface that provides the resource  212  with a reordered and summarized and/or normalized rich display for efficient assistance when working on customer issues and/or work items. More specifically, the temporal correction module  228  can evaluate a dialog  100 A containing message elements  104 ,  108 ,  112 ,  116  received as a work item from the communication network  204  from the customer communication device  208 . Results of analyses, reordered timelines, additional external event indicators, and displays provided by the temporal correction module  228  can be used by the work assignment engine  220  to assist resources  212  as dialogs are received and routed to agents and/or supervisors. 
       FIG. 3  illustrates an example of a request from a customer to a website that may make use of the temporal correction module  228 . The request process  300  may include, in some embodiments, a customer  304  with a communication device  208  connected via the Internet to one or more web servers  308 , which may be owned and operated by an enterprise administering a contact center. The customer  304  sends a request  320  to the web server  308 . The request might be a query or a response to a query in a chat session, a post on a social media site managed by or for a company or contact center, a browser request from a web page, or other type of written communication. In the communication system  200 , a temporal correction module  228 , a work assignment mechanism  216 , a routing engine  224 , a database server  312 , and a database  316  may be operable to set up a session to handle the incoming request and/or query from the customer  304  through the customer communication device  208 . 
     Additionally, the communication system  200  can pull or receive information regarding external events, known as indicators, as they are fixed in time and can be used as references when analyzing a dialog. The external event indicators may also give clues as to outages or other service issues, depending on the time and date of the outage and/or issue. The information from the external event indicators may be provided by an event feed  328  that may pull information from RSS feeds. The event feed  328  may also provide information collected from agent service notes, weather reporting services, power company status changes, airline flight information, message elements from a second message, and other public and privately available internal, local, national, and global sources. All event data may be managed by an event server  312 , pulling and pushing data used by the communication system  200  and stored in the company and/or contact center&#39;s database  316 . All relevant message elements within the work item and external event data may be analyzed, reordered, and presented to the agent  324  via an agent workstation  332 . 
     With reference now to  FIG. 4 , aspects of a method  400  for receiving and reordering message elements in dialogs in accordance with embodiments of the present disclosure are depicted. Generally, the method  400  begins with a start operation  404  and terminates with an end operation  430 . While a general order for the steps of the method  400  are shown in  FIG. 4 , the method  400  can include more or fewer steps or the order of the steps can be arranged differently than those shown in  FIG. 4 . The method  400  can be executed as a set of computer-executable instructions executed by a computer system and encoded or stored on a computer readable medium. Further, the method may also be embodied by a set of gates or other structures in an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA), or other configurable hardware component, module, or system. Hereinafter, the method  400  shall be explained with reference to the systems, components, modules, software, data structures, etc. described in conjunction with  FIGS. 1-3 . 
     Typically, the process idles at step  404  until a dialog  100 A has been received, in step  408 . In step  412 , the temporal correction module  228  may run an analysis on the dialog  100 A which may contain multiple message elements  104 ,  108 ,  112 ,  116 . Once the message elements  104 ,  108 ,  112 ,  116  of the dialog  100 A have been established, the temporal correction module  228  may determine if the message elements  104 ,  108 ,  112 ,  116  presented in the dialog  100 A are in sequential order. The temporal correction module  228  may determine if the message elements  104 ,  108 ,  112 ,  116  can benefit from being reordered, in step  416 . If the answer to the question is that the dialog  100 A does need to be reordered, the dialog  100 A may be analyzed and manipulated by the temporal correction module  228  to automatically put the message elements  104 ,  108 ,  112 ,  116  in order, remove unnecessary message elements  104 ,  108 ,  112 ,  116 , and/or optionally add one or more external event indicators  120  into a second dialog  100 B, in step  420 . The analysis and manipulation by the temporal correction module  228  in step  420  may include execution of one or more algorithms to provide speech analysis, sentence structure tagging, intent matching, normalization of time-based entities, and other predictive, expressive, tense, aspect, explicit, and implicit object and attribute analyses and mechanisms. 
     Once the dialog manipulation in step  420  has been completed, the newly analyzed, reordered, and externally event anchored dialog  100 B may be assigned to an agent  212 , in step  424 . Alternatively, if the answer to the question is that the dialog does not need to be reordered, the dialog may be assigned without manipulation to the agent  212 , in step  424 . The original dialog  100 A and/or the new dialog  100 B may be displayed to the agent  324  at the agent workstation  332 , in step  428 . The method  400  for receiving, analyzing, reordering, anchoring, and displaying message elements and external indicators in dialogs ends, at step  432 . The process may begin again when a new dialog is received (step  408 ). 
     In an additional embodiment, the data presented may also be used by a management system to generate and provide responsiveness reports and performance metrics for agents, skills, and groups to a manager and/or a contact center administrator. 
     An embodiment of dialog reorder data  500  is shown in  FIG. 5 . The phrase “dialog reorder data,” as used herein, refers to a collection of information from message elements  104 ,  108 ,  112 ,  116  and external event indicators  120  in a dialog that may have been analyzed, normalized, summarized, simplified, and stored by an organization and displayed upon request. Dialog reorder data can include, but is not limited to, customer identification information, an account number, raw data from a post on a web site or on a social media site, a reordered, summarized, and/or richly developed display of a post, a service and/or transaction history, and external event indicators that might have been considered and/or used for temporal correction and optimized for use by the agent  324 . 
     The dialog reorder data  500  may include specific information from interactions with a third party, a direct customer of the contact center, employees of the contact center, news organizations, weather reporting organizations, RSS feeds, emergency agencies, power companies, or other users of automatic timeline and topic normalization mechanism through a browser or other system interface. 
     The dialog reorder data  500  may include metadata. The metadata may include information on the user  504 . User information may include name, age, gender, first language, location, contact information, contact preference, profile data, and other customer identifying attributes and/or details. It may also include an account number  508  that may be associated with a user. 
     The database information may include the actual post  512  from the social media or web site. The raw post information may be presented to the agent  324  at the agent workstation  332  when the work item is assigned. In addition to the raw post data, the analyzed and potentially manipulated post may be presented to the agent  324 , in field  516  which can include a richly ordered post, a summarization of the post, the original post, the original post and external information, or some combination produced by the temporal correction module  228 . The historical data  520  may include any form of application, orders, returns, product preferences, searches, correspondence, and/or other types of user history. The external event indicator field  524  may include information about outside events, including natural disasters, major weather events, terrorist attacks, flight information, and other large-scale events that may influence the ability of the company to provide service or that prevent or disrupt services to the users. The event information may be used during dialog analysis, including but not limited to an external event indicator insertion on the timeline and/or as an alert sent to the agent  324 . 
     Information from the database  316  may also include additional data that has been collected in response to multiple interactions with a company or a contact center. While there are only six input fields  504 ,  508 ,  512 ,  516 ,  520 , and  524  as shown in  FIG. 5 , there may be more or fewer data fields associated with data structure  500 . 
     Although the present disclosure describes components and functions implemented in the aspects, embodiments, and/or configurations with reference to particular standards and protocols, the aspects, embodiments, and/or configurations are not limited to such standards and protocols. Other similar standards and protocols not mentioned herein are in existence and are considered to be included in the present disclosure. Moreover, the standards and protocols mentioned herein and other similar standards and protocols not mentioned herein are periodically superseded by faster or more effective equivalents having essentially the same functions. Such replacement standards and protocols having the same functions are considered equivalents included in the present disclosure. 
     The foregoing discussion has been presented for purposes of illustration and description. The foregoing is not intended to limit the disclosure to the form or forms disclosed herein. In the foregoing Detailed Description for example, various features of the disclosure are grouped together in one or more aspects, embodiments, and/or configurations for the purpose of streamlining the disclosure. The features of the aspects, embodiments, and/or configurations of the disclosure may be combined in alternate aspects, embodiments, and/or configurations other than those discussed above. This method of disclosure is not to be interpreted as reflecting an intention that the claims require more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive aspects lie in less than all features of a single foregoing disclosed aspect, embodiment, and/or configuration. Thus, the following claims are hereby incorporated into this Detailed Description, with each claim standing on its own as a separate preferred embodiment of the disclosure.