Text Summarization Using Latent Semantic Analysis Model in Mobile Android Platform

摘要

This paper presents the Latent Semantic Analysis (LSA) Model in Automatic Text Summarization (ATS) on single English document in mobile Android platform. Readers are drowned in information while starved of knowledge. Millions of articles are uploaded into the website every day. Quite often, lengthy text are presented in online articles but shorter summarized texts are preferred by readers. There exists research gap as most of the extractive text summarizations are based on syntactic appearance of words. Thus, the objective of this paper is to investigate the LSA Model by examining the semantic relationship between terms and sentences in a document for text summarization. We intend to shift our research paradigm to summarize text to infer the semantic contextual cues using the co-occurrence of terms in text. The input text documents were downloaded from Document Understanding Conference 2002 dataset. The preliminary results show that the LSA model yields an average F-Score of 0.386 in text summarization.