Comparing fbeta-optimal with distance based merge functions

Merge functions informally combine information from a certain universe into a solution over that same universe. This typically results in a, preferably optimal, summarization. In previous research, merge functions over sets have been looked into extensively. A specic case concerns sets that allow elements to appear more than once, multisets. In this paper we compare two types of merge functions over multisets against each other. We examine both general properties as practical usability in a real world application

Automatically generating multi-document summarizations

This paper describes the News Summarization or NEWSUM algorithm designed to automatically generate multi-document summarizations, hereby focusing on textual documents that concern news items. The NEWSUM algorithm has been implemented and tested in several ways. An overview of both the implementation and the test results are covered in this document

Concept identification in constructing multi-document summarizations

This paper describes a way to influence the content identification process in automatically generating multi-document summarizations of a cluster of documents regarding the same topic. The proposed method uses the weighted harmonic mean between precision and recall and results in a multiset of concepts that we consider to be defining for a cluster. These concepts can be used for selecting the proper sentences from the original cluster of documents and thus generating the multi-document summarization