Semantic Concept Discovery Over Event Databases
published: July 10, 2018, recorded: June 2018, views: 754
Slides
Related content
Report a problem or upload files
If you have found a problem with this lecture or would like to send us extra material, articles, exercises, etc., please use our ticket system to describe your request and upload the data.Enter your e-mail into the 'Cc' field, and we will keep you updated with your request's status.
Description
In this paper, we study the problem of identifying certain types of concept (e.g., persons, organizations, topics) for a given analysis question with the goal of assisting a human analyst in writing a deep analysis report. We consider a case where we have a large event database describing events and their associated news articles along with meta-data describing various event attributes such as people and organizations involved and the topic of the event. We describe the use of semantic technologies in question understanding and deep analysis of the event database, and show a detailed evaluation of our proposed concept discovery techniques using reports from Human Rights Watch organization and other sources. Our study finds that combining our neural network based semantic term embeddings over structured data with an index-based method can significantly outperform either method alone.
Link this page
Would you like to put a link to this lecture on your homepage?Go ahead! Copy the HTML snippet !
Write your own review or comment: