You will be given a definition of a task first, then some input of the task.
In this task, you are given a part of an article. Your task is to generate headline (title) for this text. Preferred headlines are under fifteen words.

Concept maps can be used to concisely represent important information and bring structure into large document collections. Therefore, we study a variant of multidocument summarization that produces summaries in the form of concept maps. However, suitable evaluation datasets for this task are currently missing. To close this gap, we present a newly created corpus of concept maps that summarize heterogeneous collections of web documents on educational topics. It was created using a novel crowdsourcing approach that allows us to efficiently determine important elements in large document collections. We release the corpus along with a baseline system and proposed evaluation protocol to enable further research on this variant of summarization.
Output:
Connecting the dots: Summarizing and Structuring Large Document Collections Using Concept Maps