Recommending a Next Step to Take in a Case
A flow model of an activity flow that is based on cases is provided. The flow model is annotated with information from the cases. A matching step in the activity flow that matches a given step of a particular case is identified, and a next step is recommended based on the matching step in the activity flow of the flow model.
1 . A method comprising:
providing, by a system having a processor, a flow model of an activity flow relating to cases that have been processed, wherein the flow model is annotated with information from the cases; and
matching, by the system, a given step of a particular case to a respective matching step in the activity flow of the flow model, wherein the matching is based on the annotated information; and
recommending at least one next step to take in the particular case based on identifying at least one next step from the matching step in the flow model.
2 . The method of claim 1 , wherein recommending the at least one next step comprises recommending an ordered collection of next steps from the matching step.
3 . The method of claim 1 , further comprising recommending an expert to process the particular step, wherein the recommended expert is based on information relating to participants in the annotated information.
4 . The method of claim 1 , wherein providing the flow model comprises learning the flow model based on the cases that have been processed.
5 . The method of claim 1 , wherein the matching comprises:
identifying candidate paths in the flow model leading to respective candidate steps in the flow model;
determining similarity of a path to the given step in the particular case to each of the identified candidate paths; and
selecting one of the candidate steps as the matching step based on the determined similarities of the candidate paths.
6 . The method of claim 5 , wherein selecting one of the candidate steps as the matching step comprise selecting the one candidate step that is associated with a corresponding one of the candidate paths that is most similar to the path to the given step in the particular case.
7 . The method of claim 1 , wherein the given step of the particular case is a current step of a partial activity flow of the particular case.
8 . The method of claim 1 , wherein recommending the at least one next step comprises selecting one of plural candidate next steps that proceed from the matching step in the flow model, according to a selection criterion that favors a candidate next step having shorter resolution path.
9 . The method of claim 1 , wherein the annotated information includes statistical metadata associated with transitions between nodes in the flow model.
10 . A system comprising:
a storage medium to store a flow model of an activity flow that is based on past cases that have already been processed; and
at least one processor to:
annotate the flow model with information based on attributes of the past cases;
find a matching step in the activity flow that matches a current step of a particular case that is being processed; and
recommend at least one next step based on the matching step in the activity flow of the flow model.
11 . The system of claim 10 , wherein the past cases include past information technology (IT) support cases, and the particular case is a current IT support case.
12 . The system of claim 10 , wherein the at least one processor is to find the matching step by considering candidate steps in the activity flow of the flow model, and selecting one of the candidate steps according to at least one predefined criterion.
13 . The system of claim 12 , wherein the at least one predefined criterion selects one of the candidate steps associated with a path that is most similar to a path leading to the current step of the particular case.
14 . The system of claim 10 , wherein the at least one processor is to recommend an expert to process the current step, wherein the recommended expert is based on information relating to participants in the annotated information.
15 . An article comprising at least one machine-readable storage medium storing instructions that upon execution cause a system to:
access a flow model of an activity flow that is based on past cases that have already been processed, where the flow model is annotated with information based on attributes of the past cases;
find a matching step in the activity flow of the flow model that matches a current step of a particular case that is being processed; and
recommend at least one next step based on the matching step in the activity flow of the flow model.