Abstract: Computer-based generation of information-gathering questions in response to a user query can include parsing the user query using natural language processing and extracting from the user query one or more phrases corresponding to a predetermined category. A knowledge database can be accessed, and entities semantically related to each phrase can be extracted therefrom. A query sub-graph representing a relationship between each of the one or more phrases and the entities extracted from the knowledge database can be generated. An expanded user query can be generated by traversing the query sub-graph. Passages semantically related to the expanded user query can be retrieved from one or more passages databases and ranked. A neural question generator can generate a set of information-gathering questions based on the expanded user query and a group of select passages selected from the plurality of passages in accordance with each selected passage's ranking.

Abstract: The disclosure deals with a system and method for mediating social media platforms automatically for user safety, including in particular for automatically or semi-automatically mediating social media platforms for user safety. People meet on online platforms and discuss a variety of topics. Moderators associated with those platforms play an important role in making the platform convenient and safe to users. This disclosure addresses detecting users who can act as potential moderators of an online group of support seekers and support providers in an online social media platform operating on the Internet. Such users are classified to identify the class of supportive users and class of non-supportive users of an online group. Received suggestions and other acquired data are used to identify a potential moderator for the online group. Acquired data on supportive and non-supportive users, as well as on harmful users, is then automatically supplied to the moderator.

Abstract: Computer-based generation of information-gathering questions in response to a user query can include parsing the user query using natural language processing and extracting from the user query one or more phrases corresponding to a predetermined category. A knowledge database can be accessed, and entities semantically related to each phrase can be extracted therefrom. A query sub-graph representing a relationship between each of the one or more phrases and the entities extracted from the knowledge database can be generated. An expanded user query can be generated by traversing the query sub-graph. Passages semantically related to the expanded user query can be retrieved from one or more passages databases and ranked. A neural question generator can generate a set of information-gathering questions based on the expanded user query and a group of select passages selected from the plurality of passages in accordance with each selected passage's ranking.