Abstract:
According to embodiments illustrated herein there is provided a method for determining a psychological type of a user. The method includes determining a first score for the user based on a profile of the user on a social media platform. Further, a second score is determined for the user based on activities of the user on the social media platform. Thereafter, a third score is determined for the user based on context of conversations of the user on the social media platform, which is determined based on a part of speech of each word in the conversations using a context database. Each word is categorized based on at least the part of speech associated with the word. The third score is determined based on the categorization. The psychological type of the user is determined based on the first score, the second score, and the third score.
Abstract:
According to embodiments illustrated herein there is provided a method for determining a psychological type of a user. The method includes determining a first score for the user based on a profile of the user on a social media platform. Further, a second score is determined for the user based on activities of the user on the social media platform. Thereafter, a third score is determined for the user based on context of conversations of the user on the social media platform, which is determined based on a part of speech of each word in the conversations using a context database. Each word is categorized based on at least the part of speech associated with the word. The third score is determined based on the categorization. The psychological type of the user is determined based on the first score, the second score, and the third score.
Abstract:
According to embodiments illustrated herein, a method and a system is provided for screening candidates for job opportunities. The method includes grouping the candidates into batches based on predetermined time duration, a count of the candidates, and a chronology of receiving job applications from the candidates. Each batch comprises a first set of candidates. Thereafter, a sliding window is moved over the batches, to encompass a set of batches at a first time instance. A second set of candidates is identified from the first set of candidates in a batch from the set of batches based on a score assigned to each of the first set of candidates during an interview. Further, a candidate is selected from the second set of candidates obtained from a first batch, encompassed by the sliding window at a second time instance before the first time instance.
Abstract:
The disclosed embodiments illustrate methods and systems for data processing to predict domain knowledge of a user for content recommendation. The method includes extracting a set of features from user data based on at least a domain-of-interest. The method further includes categorizing each feature in each set of the extracted set of features into one of a plurality of categories. The method further includes determining a domain literacy weight of the user for each category of the plurality of categories based on at least an average weight associated with each set of the extracted set of features in each category. The method further includes predicting the domain knowledge of the user based on at least the determined domain literacy weight associated with each category. The predicted domain knowledge is further utilized for the content recommendation to the user.