Abstract: A content compliance system uses machine learning to generate objective verification that content complies with brand criteria. The content compliance system may force the company to select specific brand criteria listed on a user interface. The selected brand criteria are then readily displayed to the creative agency. The content compliance system then compares the selected brand criteria with content generated by the creative agency. The content compliance system uses machine learning algorithms to generate a compliance score that provides a real-time objective indication of the compliance of the creative content with the selected brand criteria. The creative agency can then modify the creative content and receive a real-time updated compliance score.

Abstract: A dialogue intent analyzer uses a conversation between a user and agent, and intents in the conversation to predict a set of answers that better respond to pending user question. The dialogue intent analyzer understands the context surrounding the pending question by capturing and modeling prior conversation and intents within the conversation. Dialogue intent analyzer also reduces genericness in predicted answers by weighting previously used answers based on their frequency and length. Dialogue intent analyzer also increases diversity of predicted answers by using a diverse beam search.

Abstract: An insight system identifies brands, subjects, attributes, and the sentiment conveyed for those attributes. The insight system pairs the attributes with the subjects and brands and generates metrics based on the sentiments associated with the attributes. The insight system may parse product webpages linked to the content for brand identifiers and associate the brand identifiers with the brands. The insight system provides more granular insight into user sentiment for different features associated with the brands.

Abstract: A dialogue intent analyzer uses a conversation between a user and agent, and intents in the conversation to predict a set of answers that better respond to pending user question. The dialogue intent analyzer understands the context surrounding the pending question by capturing and modeling prior conversation and intents within the conversation. Dialogue intent analyzer also reduces genericness in predicted answers by weighting previously used answers based on their frequency and length. Dialogue intent analyzer also increases diversity of predicted answers by using a diverse beam search.

Abstract: A content compliance system uses machine learning to generate objective verification that content complies with brand criteria. The content compliance system may force the company to select specific brand criteria listed on a user interface. The selected brand criteria are then readily displayed to the creative agency. The content compliance system then compares the selected brand criteria with content generated by the creative agency. The content compliance system uses machine learning algorithms to generate a compliance score that provides a real-time objective indication of the compliance of the creative content with the selected brand criteria. The creative agency can then modify the creative content and receive a real-time updated compliance score.

Abstract: An insight system identifies brands, subjects, attributes, and the sentiment conveyed for those attributes. The insight system pairs the attributes with the subjects and brands and generates metrics based on the sentiments associated with the attributes. The insight system may parse product webpages linked to the content for brand identifiers and associate the brand identifiers with the brands. The insight system provides more granular insight into user sentiment for different features associated with the brands.

Abstract: A mobile “Applications Builder” established on the user's mobile handheld device creates a bucket or container for mobile applications (Apps) and selectively downloads applications that are appropriate to a search initiated by the consumer. The user search inputs are used as a contextualization input to identify the relevant product, service or brand and identify the Apps of companies that fall within the search parameters. The identified Apps are downloaded into a bucket and made available to the user to enable his search using tokens or logos for the products, services and brands he is interested in. Users can perform searches using scanned visual logos or visual tokens scanned. Visual tokens and logos contained within the bucket can be used to reduce the customer's effort during the search, while providing enlarged access to related items for consideration by the user as a marketing tool.