Rebecca Mason's scientific contributions
What is this page?
This page lists the scientific contributions of an author, who either does not have a ResearchGate profile, or has not yet added these contributions to their profile.
It was automatically created by ResearchGate to create a record of this author's body of work. We create such pages to advance our goal of creating and maintaining the most comprehensive scientific repository possible. In doing so, we process publicly available (personal) data relating to the author as a member of the scientific community.
If you're a ResearchGate member, you can follow this page to keep up with this author's work.
If you are this author, and you don't want us to display this page anymore, please let us know.
It was automatically created by ResearchGate to create a record of this author's body of work. We create such pages to advance our goal of creating and maintaining the most comprehensive scientific repository possible. In doing so, we process publicly available (personal) data relating to the author as a member of the scientific community.
If you're a ResearchGate member, you can follow this page to keep up with this author's work.
If you are this author, and you don't want us to display this page anymore, please let us know.
Publication (1)
1. ABSTRACT As the amount of text available from electronic sources continues to increase, the study of automatic text summarization is more important now than it has ever been. Automatically generated summaries should be clear and concise without giving unimportant or redundant information. The process of extractive text summarization involves det...
Citations
... The main algorithm that has been used in this section is greedy algorithm together with applying NLP techniques for preprocessing the data that should be summarized. Butterfield, et al [20] described the main steps for the greedy algorithm which have been modified and extended to include the following: 1. Construct the first paragraph from combining sentences that are retrieved from multiple records EMR in the DB. 2. Apply Natural Language Pre-processing: a. Stopword Filtering. b. ...