Cloud computing scoring systems and methods

Abstract

There is disclosed a computer-implemented cloud computing scoring system. In an embodiment, a parser receives unstructured sentiment data commenting on a scored service. The parser identifies in the unstructured sentiment data a service category of the scored service. The parser selects from the unstructured sentiment data text relating to the service category and matching one or more opinionative words and phrases listed in a keyword dictionary, thereby producing a structured comment associated with the service category. The structured comment is classified as positive or negative according to a list of exemplary sentiment data sets contained in a learning seed file. The exemplary sentiment data sets are manually assigned a positive or a negative polarity. The learning seed file is configured for enhancement by the ongoing addition of structured sentiment data, the structured sentiment data commenting on the scored service and having a polarity classification.

What is claimed is: 
     
         1 . A computer system configured to facilitate improvements in how services provided by a cloud service provider are scored relative to services of other cloud service providers without requiring said cloud service provider to engage in marketing surveys to determine said scoring to thereby enable the cloud service provider to progressively improve its services based on the scoring, said computer system comprising:
 one or more processors; and   one or more computer-readable hardware storage devices having stored thereon computer-executable instructions that are executable by the one or more processors to cause the computer system to at least:
 access unstructured sentiment data directed toward a cloud service provider, the unstructured sentiment data being included in text commentary written about the cloud service provider but lacking an indication regarding which service category of the cloud service provider the unstructured sentiment data is directed toward; 
 determine a keyword domain to which the cloud service provider likely belongs, the keyword domain including domain-specific terms and jargon commonly used to describe characteristics of a cloud computing industry; 
 based on matching words from the unstructured sentiment data and words included in the keyword domain, determine that the unstructured sentiment data is describing a particular service category of the cloud service provider, the particular service category being one of one or more different service categories provided by the cloud service provider; 
 generate a structured comment from the unstructured sentiment data by (i) selecting, from the unstructured sentiment data, specific text identified as being related to the particular service category and (ii) identifying matching correlations between the selected text and one or more opinionative words or phrases listed in the keyword domain to thereby generate the structured comment; and 
 apply a machine learning seed algorithm, which is tuned based on the keyword domain reflective of the cloud computing industry, to the structured comment to determine a sentiment classification of the structured comment. 
   
     
     
         2 . The computer system of  claim 1 , wherein the one or more different service categories include one or more of: an infrastructure category, a security category, a reliability category, a service level category, a customer service category, a usability category, a price category, a performance category, or a technology category. 
     
     
         3 . The computer system of  claim 1 , wherein the one or more different service categories include a plurality of different service categories, the plurality of different service categories including all of the following: an infrastructure category, a security category, a reliability category, a service level category, a customer service category, a usability category, a price category, a performance category, and a technology category. 
     
     
         4 . The computer system of  claim 1 , wherein the sentiment classification includes a positive or negative sentiment polarity classification. 
     
     
         5 . The computer system of  claim 1 , wherein the sentiment classification includes an assignment of a strength value based on a scale between a maximum strength value and a minimum strength value. 
     
     
         6 . The computer system of  claim 5 , wherein the maximum strength value is a positive value and the minimum strength value is a negative value. 
     
     
         7 . The computer system of  claim 6 , wherein the positive value is +10 and the negative value is −10. 
     
     
         8 . The computer system of  claim 1 , wherein the keyword domain includes a crowd-sourced database. 
     
     
         9 . The computer system of  claim 1 , wherein the unstructured sentiment data is opinion data. 
     
     
         10 . The computer system of  claim 1 , wherein a list of commentary specific to the particular service category is provided. 
     
     
         11 . A method for facilitating improvements in how services provided by a cloud service provider are scored relative to services of other cloud service providers without requiring said cloud service provider to engage in marketing surveys to determine said scoring to thereby enable the cloud service provider to progressively improve its services based on the scoring, said method comprising:
 accessing unstructured sentiment data directed toward a cloud service provider, the unstructured sentiment data being included in text commentary written about the cloud service provider but lacking an indication regarding which service category of the cloud service provider the unstructured sentiment data is directed toward;   determining a keyword domain to which the cloud service provider likely belongs, the keyword domain including domain-specific terms and jargon commonly used to describe characteristics of a cloud computing industry;   based on matching words from the unstructured sentiment data and words included in the keyword domain, determining that the unstructured sentiment data is describing a particular service category of the cloud service provider, the particular service category being one of one or more different service categories provided by the cloud service provider;   generating a structured comment from the unstructured sentiment data by (i) selecting, from the unstructured sentiment data, specific text identified as being related to the particular service category and (ii) identifying matching correlations between the selected text and one or more opinionative words or phrases listed in the keyword domain to thereby generate the structured comment; and   applying a machine learning seed algorithm, which is tuned based on the keyword domain reflective of the cloud computing industry, to the structured comment to determine a sentiment classification of the structured comment.   
     
     
         12 . The method of  claim 11 , wherein the method further includes generating a score for the particular service category of the cloud service provider based on the structured comment. 
     
     
         13 . The method of  claim 12 , wherein the score is a normalized score based on analytics data. 
     
     
         14 . The method of  claim 13 , wherein the analytics data includes geographic data such that the normalized score is based on the geographic data. 
     
     
         15 . The method of  claim 13 , wherein the analytics data includes multiple different analytics performance factors. 
     
     
         16 . The method of  claim 15 , wherein each analytics performance factor included in the multiple different analytics performance factors is assigned a weighting factor. 
     
     
         17 . The method of  claim 13 , wherein the method further includes:
 displaying a user interface, said user interface comprising:
 said normalized score; 
 a plurality of normalized scores for other cloud service providers; and 
 options to display the following:
 sentiment data, 
 additional score data, and 
 score trend reports. 
 
   
     
     
         18 . The method of  claim 11 , wherein performance of said method is integrated in a supply chain system. 
     
     
         19 . The method of  claim 11 , wherein the one or more different service categories include a plurality of different service categories, the plurality of different service categories including all of the following: an infrastructure category, a security category, a reliability category, a service level category, a customer service category, a usability category, a price category, a performance category, or a technology category. 
     
     
         20 . One or more hardware storage devices having stored thereon computer-executable instructions that are executable by one or more processors of a computer system to cause the computer system to at least:
 access unstructured sentiment data directed toward a cloud service provider, the unstructured sentiment data being included in text commentary written about the cloud service provider but lacking an indication regarding which service category of the cloud service provider the unstructured sentiment data is directed toward;   determine a keyword domain to which the cloud service provider likely belongs, the keyword domain including domain-specific terms and jargon commonly used to describe characteristics of a cloud computing industry;   based on matching words from the unstructured sentiment data and words included in the keyword domain, determine that the unstructured sentiment data is describing a particular service category of the cloud service provider, the particular service category being one of one or more different service categories provided by the cloud service provider;   generate a structured comment from the unstructured sentiment data by (i) selecting, from the unstructured sentiment data, specific text identified as being related to the particular service category and (ii) identifying matching correlations between the selected text and one or more opinionative words or phrases listed in the keyword domain to thereby generate the structured comment; and   apply a machine learning seed algorithm, which is tuned based on the keyword domain reflective of the cloud computing industry, to the structured comment to determine a sentiment classification of the structured comment.