Techniques for data matching in a contact center system are disclosed. In one particular embodiment, the techniques may be realized as a method for data matching in a contact center system comprising determining, by at least one computer processor communicatively coupled to and configured to operate in the contact center system, an interaction event time associated with a historical contact interaction; determining, by the at least one computer processor, an outcome event time associated with a historical contact interaction outcome; analyzing, by the at least one computer processor, the interaction event time and the outcome event time to determine a correlation; and matching, by the at least one computer processor, the historical contact interaction with the historical contact interaction outcome based on the correlation.

A method, computer program product, and computing system for performing an assessment of initial input information, concerning a communication from a caller, to define an initial fraud-threat-level; if the initial fraud-threat-level is below a defined threat threshold, providing the communication to a recipient so that a conversation may occur between the recipient and the caller; performing an assessment of subsequent input information, concerning the conversation, to define a subsequent fraud-threat-level; and effectuating a targeted response based, at least in part, upon the subsequent fraud-threat-level, wherein the targeted response is intended to refine the subsequent fraud-threat-level.

The inventive concept relates to a spam blocking method, and the spam blocking method includes training a spam determination module using call pattern data of an originator and a recipient secured based on call logs and re-training the spam determination module according to a maneuver of a user for an incoming call received in a recipient terminal, thus enabling spam determination customized for each user.

A method of detecting robocalls includes generating at least one of an identification (ID) spoofing score, a number similarity score, and a call length prediction request for a telephone call request. The method further includes generating a robocall predictor score based at least in part on the call length prediction score and the ID spoofing score, and rejecting the telephone call request when the robocall predictor score indicates the telephone call request is invalid.

Systems, computer program products, and methods are described herein for document presentment and fulfillment based on pattern analytics. The present invention is configured to determine one or more resource transfers executed by one or more users, wherein the one or more resource transfers are executed in response to one or more resource transfer requests; retrieve information associated with the one or more resource transfers executed by the one or more users; initiate one or more machine learning algorithms on the retrieved information; determine a pattern associated with the one or more resource transfers executed by the one or more users based on at least the retrieved information; and re-configure the one or more resource transfer requests based on at least the pattern associated with the one or more resource transfers executed by the one or more users.

A method and systems for identifying communicators as wanted or unwanted based on communications from such communicators, the method comprising determining communications from phone numbers as being unwanted by analyzing communication content features of communications associated with unwanted communicators, identifying telecommunications carriers that acquired the phone numbers, computing scores for the telecommunications carriers based on an amount of the determined unwanted communications from the phone numbers are unwanted, intercepting an inbound communication from a given phone number, identifying the given phone number is associated with a given one of the telecommunications carriers, and configuring handling of communications from the phone number based on a score of the given telecommunications carrier.

The present invention discloses a system, apparatus, and method that obtains audio and metadata information from voice calls, generates textual transcripts from those calls, and makes the resulting data searchable via a user interface. The system converts audio data from one or more sources (such as a telecommunications provider) into searchable usable text transcripts. One use of which is law enforcement and intelligence work. Another use relates to call centers to improve quality and track customer service history. Searches can be performed for callers, callees, keywords, and/or other information in calls across the system. The system can also generate automatic alerts based on callers, callees, keywords, phone numbers, and/or other information. Further the system generates and provides analytic information on the use of the phone system, the semantic content of the calls, and the connections between callers and phone numbers called, which can aid analysts in detecting patterns of behavior, and in looking for patterns of equipment use or failure.

The present invention relates to device, system and method for determining a priority level and/or conversation duration of a call. An improved and adaptive device comprises a signal input (31) for obtaining an image data signal (21) of a user initiating a call, a physiological data extraction unit (32) for extracting physiological data (22) of the user from the obtained image data signal (21), a health condition determination unit (33) for determining the health condition (23) of the user based on the extracted physiological data, and a prioritization unit (34) for determining the priority level and/or conversation duration (24) of the call based on the determined health condition of the user.

Methods and systems for creating demographic profiles of mobile communication network users. A demographic classification system analyzes network traffic, so as to estimate the specific combination of application classes installed on a given terminal, and usage patterns of the applications over time. This combination of application classes and their respective usage patterns are a highly personalized choice made by the user, and is therefore used by the system to deduce the user's demographic profile. The demographic classification system operates on monitored network traffic, as opposed to obtaining explicit and accurate information regarding the installed applications from the terminal. The system then deduces the demographic profile of the user from the list of estimated application classes.

The present disclosure relates to a method for determining node metrics based on node field-value pairs and electronic activities. The method includes identifying a first node profile. The method includes identifying a plurality of electronic activities associated with the first node profile. The method includes identifying a first group of node profiles of a first category with a predetermined event. The method includes selecting a second group of node profiles. The method includes parsing the plurality of electronic activities to identify creation timestamps and participant characteristics of the electronic activities. The method includes generating an input array based on the timestamps and the participant characteristics. The method includes generating, for each of the second group of node profiles, a respective array. The method includes determining a probability score indicating a likelihood that the node profile belongs to the first category.