Dynamic and continuous onboarding of service providers in an online expert marketplace
AssigneeTaskhuman, Inc.
InventorsRavi Swaminathan, Kartik Thumbavanam Padmanabhan
Life of this patent
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Abstract
A system to generate and maintain a database of service provider skills and rankings with various categories is disclosed. Skills and rankings are generated from a number of corpus texts as well as service provider content. The database is dynamically updated to reflect changes to the corpus texts and/or service provider content.
Claims16
A method for analyzing skills of a service provider, the method comprising:
- receiving a corpus text comprising a plurality of articles;
- parsing the plurality of articles using text pre-processing, the text pre-processing comprising at least one of a stop-word removal processing, a lemmatization processing, or an entity recognition processing;
- training an online model using the parsed plurality of articles, the online model being trained using at least one of a deep learning training or a doc2vec training and the online model comprising at least one of a deep learning element, an autonomous database element, a Bayesian statistics element, a recommendation system element, or a search relevance element;
- automatically detecting a change to the plurality of articles in the corpus text has occurred;
- automatically parsing the changed plurality of articles using the text pre-processing;
- automatically training the online model using the parsed changed plurality of articles;
- automatically accessing content of the service provider;
- extracting a topic from the content using the online model;
- mapping the topic to a category of a corpus or a spot database as a vector representative of the topic;
- storing the mapped topic as the vector representative of the topic in a topics database;
- selecting the mapped topic from the topics database;
- presenting the selected topic to the service provider via a display;
- receiving user input provided by the service provider, the user input indicating approval of the selected topic;
- updating a skill rating of the service provider in a provider database for the category corresponding to the selected topic based on the approval indicated in the user input;
- determining topics that the service provider currently services based on the vector representative of the topic;
- identifying a topic that is related to the topics that the service provider currently services based on the vector representative of the topic and a vector representative of the topic that is related to the topics that the service provider currently services;
- and
- presenting the topic that is related to the topics that the service provider currently services to the service provider via the display.
A method to find topics of expertise to recommend to a first service provider, the method comprising:
- receiving a corpus text comprising a plurality of articles;
- parsing the plurality of articles using text pre-processing, the text pre-processing comprising at least one of a stop-word removal processing, a lemmatization processing, or an entity recognition process;
- training an online model using the parsed plurality of articles, the online model being trained using at least one of a deep learning training or a doc2vec training and the online model comprising at least one of a deep learning element, an autonomous database element, a Bayesian statistics element, a recommendation system element, or a search relevance element;
- automatically detecting a change to the plurality of articles in the corpus text has occurred;
- automatically parsing the changed plurality of articles using the text pre-processing;
- automatically training the online model using the parsed changed plurality of articles;
- accessing content of the first service provider;
- extracting one or more topics of expertise from the content using the online model;
- finding a topic in a corpus or a spot database similar to but not present in the topic of expertise of the first service provider;
- storing the found topic as a vector representative of the found topic in a topics database;
- selecting the found topic from the topics database;
- notifying the first service provider of the found topic via a display;
- receiving user input provided by the first service provider, the user input indicating approval of the found topic;
- updating a list of expertise of the first service provider in a provider database to include the found topic based on the approval indicated in the user input;
- determining topics that the service provider currently services based on the vector representative of the found topic;
- identifying a topic that is related to the topics that the service provider currently services based on the vector representative of the found topic and a vector representative of the topic that is related to the topics that the service provider currently services;
- and
- presenting the topic that is related to the topics that the service provider currently services to the service provider via the display.
A method to onboard a first service provider in an expert marketplace, the method comprising:
- receiving a corpus text comprising a plurality of articles;
- parsing the plurality of articles using text pre-processing, the text pre-processing comprising at least one of a stop-word removal processing, a lemmatization processing, or an entity recognition process;
- training an online model using the parsed plurality of articles, the online model being trained using at least one of a deep learning training or a doc2vec training and the online model comprising at least one of a deep learning element, an autonomous database element, a Bayesian statistics element, a recommendation system element, or a search relevance element;
- automatically detecting a change to the plurality of articles in the corpus text has occurred;
- automatically parsing the changed plurality of articles using the text pre-processing;
- automatically training the online model using the parsed changed plurality of articles;
- receiving one or more characters of text from the first service provider;
- extracting a topic from the one or more characters of text using the online model;
- generating a category by matching a vector representative of the topic to a corpus or a spot database;
- augmenting the category by searching the corpus or the spot database for a similar category;
- displaying the category and the similar category;
- wherein the corpus or the spot database contains categories created by processing content of a second service provider;
- receiving user input provided by the first service provider, the user input indicating approval at least of the category and the similar category;
- updating a list of categories associated with the first service provider in a provider database based on the approval indicated in the user input;
- determining topics that the service provider currently services based on the vector representative of the topic;
- identifying a topic that is related to the topics that the service provider currently services based on the vector representative of the topic and a vector representative of the topic that is related to the topics that the service provider currently services;
- and
- presenting the topic that is related to the topics that the service provider currently services to the service provider via the display.
Dependencies are inferred from the claim text.