SENTENCE ORDERING USING CLUSTER CORRELATION AND PROBABILITY IN MULTI-DOCUMENTS SUMMARIZATION
Abstract: Most of the document
summary are arranged extractive by taking important sentences from the
document. Extractive based summarization often not consider the connection
sentence. A good sentence ordering
should aware about rhetorical relations such as cause-effect relation, topical
relevancy and chronological sequence which exist between the sentences. Based on this problem, we propose a new
method for sentence ordering in multi document summarization using cluster correlation
and probability for English documents. Sentences of multi-documents are grouped
based on similarity into clusters. Sentence extracted from each cluster to be a
summary that will be listed based on cluster correlation and probability. User
evaluation showed that the summary result of proposed method easier to
understanding than the previous method. The result of ROUGE method also shows
increase on sentence arrangement compared to previous method.
Author: I Gusti Agung Socrates
Adi Guna, Suci Nur Fauziah, Wanvy Arifha Saputra
Journal Code: jptkomputergg170007
