Fujitsu Corporation

Yusuke Komaba

Akihiro Inomata

Naoki Matsuoka

Isao Namba

Hideki Yamanaka

Yoshinori Yaginuma

Sachiko Onodera

Takashi Yanase

Shinji Hotta

Satoshi Shinpuku

Yuki Sasamoto

An information processing device includes one or more memories; and one or more processors coupled to the one or more memories and the one or more processors configured to acquire allocation data that indicates an allocation result of a plurality of resources for a plurality of allocation destinations, extract data that violates a first condition from the acquired allocation data, classify the extracted data into a plurality of groups, acquire an index value regarding an appearance frequency of an allocation pattern of a resource of the plurality of resources based on data of each of the plurality of classified groups, and generate a second condition for the allocation pattern based on the index value.

Information processing device, information processing method, and storage medium

In a stagnation-judgment device, a work history-acquiring unit acquires work history of actions taken by an operator to handle an enquiry. A correlation-deriving unit derives correlation between actions of the operator and stagnation based on the work history regarding past enquiries. A stagnation-judgment unit judges whether the operator is in a state of stagnation by checking the work history regarding a current enquiry and the correlation derived by the correlation-deriving unit. A warning unit issues a warning when the operator is in the state of stagnation.

Stagnation-judgment device and computer product

A computer-readable recording medium having recorded therein agent training program in which when each agent has been performing an answer, agent identifier, and enquiry contents and contents of the answer are stored in a storage device. An enquiry pattern is extracted from enquiry contents. Respective agents' answers are evaluated, for each enquiry pattern, and by a model contents of the answer extraction section, contents of the answer of an agent with highest evaluation is extracted as model contents of the answer. The contents of the answer of a trainee agent and model contents of the answer are divided into predetermined phases, and corresponding phase of both are mutually compared to calculate ineptitude-degrees in respective phases of trainee agent. By specifying from the model contents of the answer, a range of contents of the answer containing therein at least one of the phases where the ineptitude-degree is high, and lasting predetermined time, and generating teaching material with these contents, teaching material specialized for the inept answers of respective agents is provided, and agent training support performed.

Computer-readable recording medium having recorded therein agent training support program, and agent training support method and agent training support apparatus

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Kawasaki, Japan

Yusuke Komaba