Abstract: The subject matter discloses a method for detection and analysis of first contact resolution failures comprising: obtaining a first plurality of digital representations, each digital representation of the first plurality is associated with a contact center interaction; determining a pair of digital representations that represent a pair of contact center interactions determined from the first plurality of digital representations according to metadata associated with the pair of contact center interactions; determining topics of each interaction of the determined pair of contact center interactions represented by the pair of digital representations; classifying the pair of contact center interactions as first contact resolution failure or first contact resolution interactions pair.

Abstract: A system and method for adapting a language model to a specific environment by receiving interactions captured the specific environment, generating a collection of documents from documents retrieved from external resources, detecting in the collection of documents terms related to the environment that are not included in an initial language model and adapting the initial language model to include the terms detected.

Abstract: A system and method for identifying an author of a social media interaction. A social media profile may be received for a user interacting in a social media interaction in a social media environment. The social media profile may include identification parameter(s) defining personal information registered to the user in the social media environment and content parameter(s) defining content of the user's social media interaction. For each of a plurality of customers registered in a contact center environment, a contact center profile may be received for the customer including identification parameter(s) defining personal information registered to the customer in the contact center environment and content parameter(s) defining content of the customer's past contact center interactions. The user's social media profile and customer's contact center profile may be compared to determine if the social media user and contact center customer have the same identity.

Abstract: The subject matter discloses a method for vehicle parking spaces management using image processing, comprising: obtaining one or more images of a plurality of parking spaces; segmenting the image of the one or more images to represent a parking space per segmented image; detecting parked vehicles in the segmented image using image processing; obtaining data from one or more additional sources related to the occupancy status of the plurality of parking spaces; and evaluating the occupancy status of the parking space of the plurality of parking spaces based on the parking vehicle detection and the obtained data from the one or more additional sources.

Abstract: A computerized method for sales optimization including receiving at a computer server a digital representation of a portion of an interaction between a customer and an organization representative, the portion of an interaction comprises a speech signal of the customer and a speech signal of the organization representative; analyzing the speech signal of the organization representative; analyzing the speech signal of the customer; determining a distance vector between the speech signal of the organization representative and the speech signal of the customer; and predicting a sale success probability score for the captured speech signal portion.

Abstract: A method and apparatus for automatically sectioning an interaction into sections, in order to get more insight into interactions. The method and apparatus include training, in which a model is generated upon training interactions and available tagging information, and run-time in which the model is used towards sectioning further interactions. The method and apparatus operate on context units within the interaction, wherein each context unit is characterized by a feature vector relate to textual, acoustic or other characteristics of the context unit.

Abstract: The subject matter discloses a method for detection and analysis of first contact resolution failures comprising: obtaining a first plurality of digital representations, each digital representation of the first plurality is associated with a contact center interaction; determining a pair of digital representations that represent a pair of contact center interactions determined from the first plurality of digital representations according to metadata associated with the pair of contact center interactions; determining topics of each interaction of the determined pair of contact center interactions represented by the pair of digital representations; classifying the pair of contact center interactions as first contact resolution failure or first contact resolution interactions pair.

Abstract: The subject matter discloses a computerized method for sales optimization comprising: receiving at a computer server a digital representation of a portion of an interaction between a customer and an organization representative, the portion of an interaction comprises a speech signal of the customer and a speech signal of the organization representative; analyzing the speech signal of the organization representative; analyzing the speech signal of the customer; determining a distance vector between the speech signal of the organization representative and the speech signal of the customer; and predicting a sale success probability score for the captured speech signal portion.

Abstract: A system and method for adapting a language model to a specific environment by receiving interactions captured the specific environment, generating a collection of documents from documents retrieved from external resources, detecting in the collection of documents terms related to the environment that are not included in an initial language model and adapting the initial language model to include the terms detected.

Abstract: A system and method for identifying an author of a social media interaction. A social media profile may be received for a user interacting in a social media interaction in a social media environment. The social media profile may include identification parameter(s) defining personal information registered to the user in the social media environment and content parameter(s) defining content of the user's social media interaction. For each of a plurality of customers registered in a contact center environment, a contact center profile may be received for the customer including identification parameter(s) defining personal information registered to the customer in the contact center environment and content parameter(s) defining content of the customer's past contact center interactions. The user's social media profile and customer's contact center profile may be compared to determine if the social media user and contact center customer have the same identity.

Abstract: A transaction verification system and method may include receiving an interaction record describing communications between parties regarding a transaction event. The interaction record may include interactions having multiple communication formats. Transaction data describing transaction parameters input into a trading system during the transaction even may be compared to the interaction record. A matching score may be calculated that indicates a level of similarity between the interaction record and the transaction data. The matching score may be calculated for multiple of transaction events in an interaction log, and an interaction log score may be calculated.

Abstract: A system and method for searching data, such as, text data, using a processing component. A query including one or more terms may be received. At least one term may be automatically added to the query to generate an expanded query set. Entries from one or more information sources, such as, Internet posts, may be retrieved. The retrieved entries may include terms that match terms in the expanded query set. The relevancy of each retrieved entry to the query may be automatically determined. A search result may be provided including a subset of the retrieved entries that are determined to have sufficient relevancy to the query. An output device may display the search result to a client or user.

Abstract: Retrieving data from audio interactions associated with an organization. Retrieving the data comprises: receiving a corpus containing interactions; performing natural language processing on a text document representing an interaction from the corpus; extracting at least one keyphrase from the text document; assigning a rank to the at least one keyphrase; modeling relations between at least two keyphrases using the rank; and identifying topics relevant for the organization from the relations.

Abstract: Obtaining information from audio interactions associated with an organization. The information may comprise entities, relations or events. The method comprises: receiving a corpus comprising audio interactions; performing audio analysis on audio interactions of the corpus to obtain text documents; performing linguistic analysis of the text documents; matching the text documents with one or more rules to obtain one or more matches; and unifying or filtering the matches.

Abstract: Methods and apparatus for the enhancement of speech to text engines, by providing indications to the correctness of the found words, based on additional sources besides the internal indication provided by the STT engine. The enhanced indications comprise sources of data such as acoustic features, CTI features, phonetic search and others. The apparatus and methods also enable the detection of important or significant keywords found in audio files, thus enabling more efficient usages, such as further processing or transfer of interactions to relevant agents, escalation of issues, or the like. The methods and apparatus employ a training phase in which word model and key phrase model are generated for determining an enhanced correctness indication for a word and an enhanced importance indication for a key phrase, based on the additional features.

Abstract: A computerized method of predicting customer churn from an organization, including: receiving at a computer server a recorded customer interaction with an agent of the organization; analyzing the received customer interaction to extract basic features that provide an indication regarding the churn probability of the customer; extracting the entity information of the customer from the recorded interaction; retrieving from a database accessible by the server previous interactions for the same entity and extracting advanced features that provide an indication regarding the churn probability of the customer by comparing multiple interactions of the same entity; predicting a churn probability for the received interaction by applying a statistical customer churn model to the extracted basic features and extracted advanced features; and wherein the interaction and the previous interactions are recordable from more than one type of communication channel by which the customer can communicate with the organization.

Abstract: A method and apparatus for automatically sectioning an interaction into sections, in order to get more insight into interactions. The method and apparatus include training, in which a model is generated upon training interactions and available tagging information, and run-time in which the model is used towards sectioning further interactions. The method and apparatus operate on context units within the interaction, wherein each context unit is characterized by a feature vector relate to textual, acoustic or other characteristics of the context unit.

Abstract: Methods and apparatus for the enhancement of speech to text engines, by providing indications to the correctness of the found words, based on additional sources besides the internal indication provided by the STT engine. The enhanced indications comprise sources of data such as acoustic features, CTI features, phonetic search and others. The apparatus and methods also enable the detection of important or significant keywords found in audio files, thus enabling more efficient usages, such as further processing or transfer of interactions to relevant agents, escalation of issues, or the like. The methods and apparatus employ a training phase in which word model and key phrase model are generated for determining an enhanced correctness indication for a word and an enhanced importance indication for a key phrase, based on the additional features.