Abstract: The present disclosure provides methods, systems, and media for optimized customer relationship management. A method for identifying subjects for a clinical procedure may comprise (a) retrieving, from a computer database, a first set of subject records, wherein the first set of subject records corresponds to a first set of subjects that are candidates for the clinical procedure; (b) processing the first set of subject records using a trained machine learning algorithm to generate a second set of subject records; and (c) electronically outputting the second set of subject records.

Abstract: This document describes techniques for identifying suggestive intent in social posts. In one or more implementations, a topic is received and social posts to one or more social networks that are related to the topic are collected. Then, one or more suggestive intent posts expressing suggestions towards the topic are identified from the collected social posts. In one or more implementations, a set of related topics are received and social posts to one or more social networks that correspond to the related topics are collected. Then, aspects corresponding to the related topics are identified, and a sentiment score is generated for each aspect of each related topic that can be used to compare aspects of the related topics. In one or more implementations a suggestive intent model, usable to identify social posts expressing suggestive intent, is built from a training corpus of annotated social posts.

Abstract: This document describes techniques for identifying suggestive intent in social posts. In one or more implementations, a topic is received and social posts to one or more social networks that are related to the topic are collected. Then, one or more suggestive intent posts expressing suggestions towards the topic are identified from the collected social posts. In one or more implementations, a set of related topics are received and social posts to one or more social networks that correspond to the related topics are collected. Then, aspects corresponding to the related topics are identified, and a sentiment score is generated for each aspect of each related topic that can be used to compare aspects of the related topics. In one or more implementations a suggestive intent model, usable to identify social posts expressing suggestive intent, is built from a training corpus of annotated social posts.

Abstract: This document describes techniques for identifying purchase intent in social posts. In one or more implementations, a topic is received and social posts to one or more social networks that are related to the topic are collected. Then, one or more purchase intent posts expressing purchase intent towards the topic are identified from the collected social posts. In one or more implementations a purchase intent model, usable to identify social posts expressing purchase intent, is built from a training corpus of annotated social posts.