Abstract: The proposed systems and methods improve the generation of delivery plans by creating one or more predictive models that can evaluate the likelihood of success of delivery plans based on notable historic delivery plans. The predictive models can be applied on already clustered delivery objects, or the clustering can be applied to results of the predictive models. The output of this stage is a set of clusters of delivery objects that are the initial delivery plans. After this stage refining process(es) can be applied to the initial delivery plans to determine a final set of delivery plan candidates. By learning from successful past outcomes, the predictive models can generate initial delivery plans that have a high likelihood of successful execution. By applying refining techniques, the initial delivery plans can be narrowed down to final delivery plans that are tailored to the delivery needs of the current situation.

Abstract: This disclosure relates to systems and methods for discovering intents from multimedia conversations. In an implementation, the system may obtain an optimal parameter configuration based on a topic relevance quantifier. The system may extract topics from the audio calls based on the optimal parameter configuration. The system may determine respective context metrics for each of the topics. The system may select a relevant topic with respect to the intent discovery from the extracted topic based on the respective context metrics. The system may obtain documents associated with the relevant topic from the corpus of documents. The system may display information of the documents associated with the relevant topic via a user interface. The system may receive a feedback data with respect to the relevant topic. The system may determine intent information associated with the relevant topic based on the feedback data.

Abstract: This disclosure relates to systems and methods for discovering intents from multimedia conversations. In an implementation, the system may obtain an optimal parameter configuration based on a topic relevance quantifier. The system may extract topics from the audio calls based on the optimal parameter configuration. The system may determine respective context metrics for each of the topics. The system may select a relevant topic with respect to the intent discovery from the extracted topic based on the respective context metrics. The system may obtain documents associated with the relevant topic from the corpus of documents. The system may display information of the documents associated with the relevant topic via a user interface. The system may receive a feedback data with respect to the relevant topic. The system may determine intent information associated with the relevant topic based on the feedback data.