Abstract: Approaches presented herein enable assignment of translated work to an agent in a support environment based on a confidence factor that measures accuracy of translation and an agent's language skill. Specifically, agent proficiencies in a set of natural languages are measured and scored. An incoming communication is translated into one or more natural languages and each language translation is assigned a translation score based on a confidence of translation. The skill score and translation score are utilized to calculate a confidence factor for each language. In one approach, the communication is assigned to an agent that has a confidence factor greater than a predetermined threshold confidence factor. In another approach, the communication is only assigned if a rule optimizing agent availability and risk of constrained resources is satisfied.

Abstract: Approaches presented herein enable assignment of translated work to an agent in a customer support environment based on a confidence factor that measures accuracy of translation and an agent's language skill. Specifically, agent proficiencies in a set of natural languages are measured and scored. An incoming customer communication is translated into one or more natural languages and each language translation is assigned a translation score based on a confidence of translation. The skill score and translation score are utilized to calculate a confidence factor for each language. In one approach, the customer communication is assigned to an agent that has a confidence factor greater than a predetermined threshold confidence factor. In another approach, the communication is only assigned if a rule optimizing agent availability and risk of constrained resources is satisfied.

Abstract: Approaches presented herein enable assignment of translated work to an agent in a support environment based on a confidence factor that measures accuracy of translation and an agent's language skill. Specifically, agent proficiencies in a set of natural languages are measured and scored. An incoming communication is translated into one or more natural languages and each language translation is assigned a translation score based on a confidence of translation. The skill score and translation score are utilized to calculate a confidence factor for each language. In one approach, the communication is assigned to an agent that has a confidence factor greater than a predetermined threshold confidence factor. In another approach, the communication is only assigned if a rule optimizing agent availability and risk of constrained resources is satisfied.

Abstract: Approaches presented herein enable assignment of translated work to an agent in a customer support environment based on a confidence factor that measures accuracy of translation and an agent's language skill. Specifically, agent proficiencies in a set of natural languages are measured and scored. An incoming customer communication is translated into one or more natural languages and each language translation is assigned a translation score based on a confidence of translation. The skill score and translation score are utilized to calculate a confidence factor for each language. In one approach, the customer communication is assigned to an agent that has a confidence factor greater than a predetermined threshold confidence factor. In another approach, the communication is only assigned if a rule optimizing agent availability and risk of constrained resources is satisfied.

Abstract: Approaches presented herein enable assignment of translated work to an agent in a customer support environment based on a confidence factor that measures accuracy of translation and an agent's language skill. Specifically, agent proficiencies in a set of natural languages are measured and scored. An incoming customer communication is translated into one or more natural languages and each language translation is assigned a translation score based on a confidence of translation. The skill score and translation score are utilized to calculate a confidence factor for each language. In one approach, the customer communication is assigned to an agent that has a confidence factor greater than a predetermined threshold confidence factor. In another approach, the communication is only assigned if a rule optimizing agent availability and risk of constrained resources is satisfied.

Abstract: Approaches presented herein enable assignment of translated work to an agent in a customer support environment based on a confidence factor that measures accuracy of translation and an agent's language skill. Specifically, agent proficiencies in a set of natural languages are measured and scored. An incoming customer communication is translated into one or more natural languages and each language translation is assigned a translation score based on a confidence of translation. The skill score and translation score are utilized to calculate a confidence factor for each language. In one approach, the customer communication is assigned to an agent that has a confidence factor greater than a predetermined threshold confidence factor. In another approach, the communication is only assigned if a rule optimizing agent availability and risk of constrained resources is satisfied.

Abstract: A case-based reasoning system is disclosed that includes a case database and a search engine. The case database is capable of storing a plurality of cases that each include one or more attributes that each have an associated match weight. Match weights of attributes in different cases are separately specified. In response to receipt of an incident including one or more input terms, the search engine scores the relative closeness of a selected case to the incident utilizing the match weights of attributes in the selected case that match input terms in the incident.

Abstract: A case-based reasoning system is disclosed that includes a case database and a search engine. The case database is capable of storing a plurality of cases that each include one or more attributes that each have an associated match weight. Match weights of attributes in different cases are separately specified. In response to receipt of an incident including one or more input terms, the search engine scores the relative closeness of a selected case to the incident utilizing the match weights of attributes in the selected case that match input terms in the incident.