Solution recommendation based on incomplete data sets
First Claim
Patent Images
1. A method that provides at least one print solution, wherein the solution is based at least in part upon data received from a software application, web interface, or questionnaire, comprising:
- receiving at least one print process data set that includes at least one of a color requirement, a media characteristic, a print volume, a printer speed, a finishing characteristic, a desired process output, a current process output and a process capacity;
mapping the at least one data set into one or more vectors in a case constraint space to create a case log vector;
mapping the case log vector into a semantic vector with reduced dimensionality via a latent semantic index transformation to eliminate excessive data from the case log vector such that only relevant data remains;
classifying the semantic vector into an existing case cluster whose cluster centroid vector has the largest cosine product with the semantic vector;
returning one or more representative workflows of the existing case cluster as one or more recommended print process workflow solutions; and
storing at least one record of at least one previous case, wherein the at least one record includes one or more print process related constraints, at least one generated print process workflow and at least one interested print process workflow, wherein the at least one generated print process workflow is provided by the recommendation system and the at least one interested print process workflow is selected from one of the generated print process workflows.
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Abstract
In accordance with one aspect of the present exemplary embodiment, a system determines a solution based on received data. An intake component receives an incomplete data set from one or more sources. A recommendation system transforms the incomplete data set into a semantic data set via latent semantic indexing, classifies the semantic data set into an existing cluster and provides one or more solutions of the existing cluster as one or more recommendations.
33 Citations
9 Claims
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1. A method that provides at least one print solution, wherein the solution is based at least in part upon data received from a software application, web interface, or questionnaire, comprising:
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receiving at least one print process data set that includes at least one of a color requirement, a media characteristic, a print volume, a printer speed, a finishing characteristic, a desired process output, a current process output and a process capacity; mapping the at least one data set into one or more vectors in a case constraint space to create a case log vector; mapping the case log vector into a semantic vector with reduced dimensionality via a latent semantic index transformation to eliminate excessive data from the case log vector such that only relevant data remains; classifying the semantic vector into an existing case cluster whose cluster centroid vector has the largest cosine product with the semantic vector; returning one or more representative workflows of the existing case cluster as one or more recommended print process workflow solutions; and storing at least one record of at least one previous case, wherein the at least one record includes one or more print process related constraints, at least one generated print process workflow and at least one interested print process workflow, wherein the at least one generated print process workflow is provided by the recommendation system and the at least one interested print process workflow is selected from one of the generated print process workflows. - View Dependent Claims (2, 3, 4, 5, 6)
where ni denotes the number of vectors in the i th cluster, and it is assumed that the vectors of each cluster satisfy m-dimensional Gaussian distribution, and the mean value μ
i and variance σ
i of the i th cluster'"'"'s probability distribution are known since μ
i is the centroid of the cluster and σ
i is estimated based on the cosine product between the centroid and all vectors of the cluster.
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5. The method of claim 2, further including:
returning the clustering scheme with the best evaluation score.
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6. The method of claim 2, further including:
calculating at least one representative solution for each cluster in the final clustering scheme.
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7. A method for providing representative workflows based at least in part upon one or more case logs and storing those workflows on a computer-readable medium, comprising:
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mapping a new case into a vector in a case constraint space to produce a case log vector; utilizing a latent semantic indexing transformation matrix to map the case log vector into a semantic vector with reduced dimensionality; clustering the semantic vectors into groups based on their mutual correlations, wherein the number of case log vectors is n and the maximum number of case clusters is Kmax, for K=1 to Kmax, the clustering algorithm a) clusters n vectors into K clusters by using K-means algorithm with refined initial centroids, b) evaluates the performance of the K clusters by Bayesian Information Criterion (BIC) scores, and c) stores the above K cluster centroids and their evaluation score as a clustering scheme, wherein the clustering scheme with the best evaluation score is output; classifying the semantic vector into a particular case cluster, which is determined by the case cluster whose cluster centroid vector has the largest cosine product with the semantic vector; and identifying one or more recommended solutions via correlation to one or more predefined data clusters, wherein the solution is a workflow that defines a process automated by at least one automation device. - View Dependent Claims (8, 9)
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Specification