公开(公告)号：US10692016B2

公开(公告)日：2020-06-23

申请号：US15426959

申请日：2017-02-07

申请人： FMR LLC

发明人： Aravind Chandramouli ,  Nitin Hardeniya ,  Sunil Kumar

IPC分类号： G06N20/00 ,  G06F16/35 ,  G06N5/02

摘要： Methods and apparatuses are described for analyzing unstructured computer text for identification and classification of complaint-specific interactions. A computer data stores unstructured text. A server computing device splits the unstructured text into phrases of words. The server generates a set of tokens from each phrase and removes tokens that are stopwords. The server generates a normalized sentiment score for each set of tokens. The server uses a rules-based classification engine to generate a rules-based complaint score for each set of tokens. The server uses an artificial intelligence machine learning model to generate a model-based complaint score for each set of tokens. The server determines determine whether each set of tokens corresponds to a complaint-specific interaction based upon the rules-based complaint score and the model-based complaint score.

公开(公告)号：US11645660B2

公开(公告)日：2023-05-09

申请号：US16563255

申请日：2019-09-06

申请人： FMR LLC

发明人： Ankush Chopra ,  Abhishek Desai ,  Aravind Chandramouli

IPC分类号： G06F16/9535 ,  G06Q30/016 ,  G06F16/33 ,  G06F16/35 ,  G06F16/332 ,  G06F16/31

CPC分类号： G06Q30/016 ,  G06F16/31 ,  G06F16/3329 ,  G06F16/3344 ,  G06F16/353

摘要： A computerized method of representing customer interactions with an organization includes: receiving, by a computing device, customer web interaction data segments and customer conversation data segments; pre-processing the customer conversation data segments to remove specified types of information; scoring each of the pre-processed customer conversation data segments; pre-processing the customer web data interaction segments; extracting from the pre-processed customer web interaction data segments tokens; combining the pre-processed customer conversation data segments and the pre-processed customer web interaction data segments into a customer data set; parsing the customer data set into one or more windows; assigning, for each window, pre-trained weights to each of the tokens in each window; assigning a transaction theme to each window based on the tokens in each window; and generating, based on the transaction themes, a ranked list of topic keywords reflecting the customer web interaction data segments and customer conversation data segments.

公开(公告)号：US10861022B2

公开(公告)日：2020-12-08

申请号：US16363889

申请日：2019-03-25

申请人： FMR LLC

发明人： Manish Gupta ,  Vijay Goel ,  Aravind Chandramouli ,  Rajib Biswas

IPC分类号： G06F16/00 ,  G06Q30/00 ,  G06F16/28 ,  G06F16/22 ,  G06F16/2457 ,  G06F16/9535 ,  G06F40/166 ,  G06F40/284

摘要： A computerized method of populating one or more structured databases includes performing, by a computing device, the steps of: receiving customer message data from one or more data sources; extracting, from the customer message data, data sets representative of a set of customer questions; pre-processing, the data sets representative of the set of customer questions using one or more filters, thereby producing pre-processed data sets representative of customer questions; extracting, from the pre-processed data sets representative of customer questions, a set of customer expression data sets; grouping, the customer expression data sets into a set of clusters, each cluster representing one customer intent data set, each customer intent data set corresponding to one or more customer expression data sets; and storing, the customer intent data sets and the customer expression data sets in the structured database(s), the structured database(s) in electronic communication with the computing device.

公开(公告)号：US20180225591A1

公开(公告)日：2018-08-09

申请号：US15426959

申请日：2017-02-07

申请人： FMR LLC

发明人： Aravind Chandramouli ,  Nitin Hardeniya ,  Sunil S. Kumar

IPC分类号： G06N99/00 ,  G06F17/30

摘要： Methods and apparatuses are described for analyzing unstructured computer text for identification and classification of complaint-specific interactions. A computer data stores unstructured text. A server computing device splits the unstructured text into phrases of words. The server generates a set of tokens from each phrase and removes tokens that are stopwords. The server generates a normalized sentiment score for each set of tokens. The server uses a rules-based classification engine to generate a rules-based complaint score for each set of tokens. The server uses an artificial intelligence machine learning model to generate a model-based complaint score for each set of tokens. The server determines determine whether each set of tokens corresponds to a complaint-specific interaction based upon the rules-based complaint score and the model-based complaint score.

公开(公告)号：US20200311739A1

公开(公告)日：2020-10-01

申请号：US16563255

申请日：2019-09-06

申请人： FMR LLC

发明人： Ankush Chopra ,  Abhishek Desai ,  Aravind Chandramouli

IPC分类号： G06Q30/00 ,  G06F16/31 ,  G06F16/332 ,  G06F16/35 ,  G06F16/33

摘要： A computerized method of representing customer interactions with an organization includes: receiving, by a computing device, customer web interaction data segments and customer conversation data segments; pre-processing the customer conversation data segments to remove specified types of information; scoring each of the pre-processed customer conversation data segments; pre-processing the customer web data interaction segments; extracting from the pre-processed customer web interaction data segments tokens; combining the pre-processed customer conversation data segments and the pre-processed customer web interaction data segments into a customer data set; parsing the customer data set into one or more windows; assigning, for each window, pre-trained weights to each of the tokens in each window; assigning a transaction theme to each window based on the tokens in each window; and generating, based on the transaction themes, a ranked list of topic keywords reflecting the customer web interaction data segments and customer conversation data segments.

公开(公告)号：US10445745B1

公开(公告)日：2019-10-15

申请号：US16365309

申请日：2019-03-26

申请人： FMR LLC

发明人： Ankush Chopra ,  Abhishek Desai ,  Aravind Chandramouli

IPC分类号： G06Q30/00 ,  G06F16/33 ,  G06F16/35 ,  G06F16/332 ,  G06F16/31

摘要： A computerized method of representing customer interactions with an organization includes: receiving, by a computing device, customer web interaction data segments and customer conversation data segments; pre-processing the customer conversation data segments to remove specified types of information; scoring each of the pre-processed customer conversation data segments; pre-processing the customer web data interaction segments; extracting from the pre-processed customer web interaction data segments tokens; combining the pre-processed customer conversation data segments and the pre-processed customer web interaction data segments into a customer data set; parsing the customer data set into one or more windows; assigning, for each window, pre-trained weights to each of the tokens in each window; assigning a transaction theme to each window based on the tokens in each window; and generating, based on the transaction themes, a ranked list of topic keywords reflecting the customer web interaction data segments and customer conversation data segments.

公开(公告)号：US20180260873A1

公开(公告)日：2018-09-13

申请号：US15457079

申请日：2017-03-13

申请人： FMR LLC

发明人： Aravind Chandramouli ,  Ankit Patil

IPC分类号： G06Q30/06 ,  G06F17/30

CPC分类号： G06Q30/0625 ,  G06F16/901

摘要： A computerized method is provided for automatically identifying a set of historical issues derived from historical customer interactions with an enterprise. The method includes collecting text-based data corresponding to the historical customer interactions, extracting customer queries from the text-based data, and normalizing and filtering the customer queries to generate the set of historical issues of the customer queries. The method also includes assigning the historical issues to one or more clusters that capture variances among the historical issues. The method further includes generating a legitimacy score for each historical issue and ranking the set of historical issues in accordance with their corresponding legitimacy scores. The method can further include identifying one or more issues in a transcript of unstructured text using the set of historical issues.

公开(公告)号：US10922734B2

公开(公告)日：2021-02-16

申请号：US15457079

申请日：2017-03-13

申请人： FMR LLC

发明人： Aravind Chandramouli ,  Ankit Patil

IPC分类号： G06Q30/06 ,  G06F16/901

摘要： A computerized method is provided for automatically identifying a set of historical issues derived from historical customer interactions with an enterprise. The method includes collecting text-based data corresponding to the historical customer interactions, extracting customer queries from the text-based data, and normalizing and filtering the customer queries to generate the set of historical issues of the customer queries. The method also includes assigning the historical issues to one or more clusters that capture variances among the historical issues. The method further includes generating a legitimacy score for each historical issue and ranking the set of historical issues in accordance with their corresponding legitimacy scores. The method can further include identifying one or more issues in a transcript of unstructured text using the set of historical issues.

公开(公告)号：US20200311738A1

公开(公告)日：2020-10-01

申请号：US16363889

申请日：2019-03-25

申请人： FMR LLC

发明人： Manish Gupta ,  Vijay Goel ,  Aravind Chandramouli ,  Rajib Biswas

IPC分类号： G06Q30/00 ,  G06F16/28 ,  G06F16/22 ,  G06F16/9535 ,  G06F16/2457 ,  G06F17/24 ,  G06F17/27

摘要： A computerized method of populating one or more structured databases includes performing, by a computing device, the steps of: receiving customer message data from one or more data sources; extracting, from the customer message data, data sets representative of a set of customer questions; pre-processing, the data sets representative of the set of customer questions using one or more filters, thereby producing pre-processed data sets representative of customer questions; extracting, from the pre-processed data sets representative of customer questions, a set of customer expression data sets; grouping, the customer expression data sets into a set of clusters, each cluster representing one customer intent data set, each customer intent data set corresponding to one or more customer expression data sets; and storing, the customer intent data sets and the customer expression data sets in the structured database(s), the structured database(s) in electronic communication with the computing device.

公开(公告)号：US10061845B2

公开(公告)日：2018-08-28

申请号：US15047527

申请日：2016-02-18

申请人： FMR LLC

发明人： Aravind Chandramouli ,  Vrushali Karnik ,  Javeed Bani ,  Divik Saxena ,  Madhuri Gupta

IPC分类号： G06F7/00 ,  G06F17/30

CPC分类号： G06F16/3344 ,  G06F16/9535

摘要： Methods and apparatuses are described for analyzing unstructured computer text for theme generation to determine sentiment. A computer store stores unstructured text that is delimited, a searched phrases log, and a phrase click log. A computer server extracts phrases from the unstructured delimited text by splitting each line of the unstructured delimited text into one or more phrases. The computer server generates tokens from the unstructured delimited text, where the tokens comprise segments of the unstructured delimited text. The computer server determines one or more themes present in the unstructured delimited text.