1. A method for classifying a multimedia content, the method comprising steps of: processing, by a processor, a plurality of multimedia content, and wherein the multimedia content includes videos, text and pictures; extracting a plurality of features from metadata obtained from the plurality of multimedia content to obtain a set of extracted features; performing a topic modeling on the set of extracted features associated with the plurality of multimedia content to obtain a set of topic models, and a set of topic keywords, wherein each of the set of topic models comprises a plurality of explicit topics that are associated with the each of the plurality of multimedia content; identifying at least one explicit content topic from the plurality of explicit content topics based on the set of topic keywords, and a set of predetermined words; processing a multimedia content to obtain at least one feature, and metadata associated with the multimedia content; deriving a topic distribution based on the at least one feature and the set of topic models, and wherein the topic distribution comprises a distribution vector of the plurality of explicit content topics associated with the plurality of multimedia content; assigning an ID to each topic and assigning a weight to each topic: creating a validation set and calculating an accuracy of the validation set based on one or more topic models; selecting a topic model based on calculated accuracy value for categorizing one or more multimedia content; and classifying the multimedia content as an explicit multimedia content, or a non-explicit multimedia content based on the at least one explicit content topic, and the topic distribution, and wherein the multimedia content is classified based on a topic weight and explicit content sub-topics.
1. A method for classifying a multimedia content, the method comprising steps of: processing, by a processor, a plurality of multimedia content, and wherein the multimedia content includes videos, text and pictures; extracting a plurality of features from metadata obtained from the plurality of multimedia content to obtain a set of extracted features; performing a topic modeling on the set of extracted features associated with the plurality of multimedia content to obtain a set of topic models, and a set of topic keywords, wherein each of the set of topic models comprises a plurality of explicit topics that are associated with the each of the plurality of multimedia content; identifying at least one explicit content topic from the plurality of explicit content topics based on the set of topic keywords, and a set of predetermined words; processing a multimedia content to obtain at least one feature, and metadata associated with the multimedia content; deriving a topic distribution based on the at least one feature and the set of topic models, and wherein the topic distribution comprises a distribution vector of the plurality of explicit content topics associated with the plurality of multimedia content; assigning an ID to each topic and assigning a weight to each topic: creating a validation set and calculating an accuracy of the validation set based on one or more topic models; selecting a topic model based on calculated accuracy value for categorizing one or more multimedia content; and classifying the multimedia content as an explicit multimedia content, or a non-explicit multimedia content based on the at least one explicit content topic, and the topic distribution, and wherein the multimedia content is classified based on a topic weight and explicit content sub-topics. 3. The method of claim 1 , wherein the weight is assigned to the plurality of explicit content topics based on the topic distribution.