From web to SMS: A text summarization of Wikipedia pages with character limitation

Abstract

Wikipedia is one of the main sources of information on the Web. But the access to this content may be difficult especially when using a basic telephone without browsing capability and only a GSM network. The only means of text-based communication remains through SMS. Due to the limitation of the number of characters, a Wikipedia page cannot always be sent through SMS. This work raises the issue of text summarization with character limitation. To solve this issue, two extractive approaches have been combined: LSA and TextRank algorithms. Generated summaries have been evaluated using ROUGE metrics. Since ROUGE metrics do not consider character limitation, a new threshold named Threshold of Acceptability for Character-Oriented Summaries (TACOS) has been proposed to appreciate ROUGE metrics. The evaluation showed the relevance of the approach for pages of at most 2000 characters. The system has been tested using the SMS simulator of RapidSMS without a GSM gateway to simulate the deployment in a real environment. To the best of our knowledge, this is the first work tackling text summarization issue with character limitation.

WATS-SMS: A T5-based French Wikipedia Abstractive Text Summarizer for SMS

“…We split the datasets to 80% for the training set and 20% for the test set. The Wikipedia summary section was used as a reference summary as it is done in [24].…”

“…We first compare the results of the proposed summarization model with the results in [24] that defined an approach associating the LSA and Text Rank algorithms for the text summarization of Wikipedia articles. However, the tests carried out in [24] are done on English pages. For a fair comparison, we selected the corresponding French Wikipedia pages of articles in [24].…”

“…However, the tests carried out in [24] are done on English pages. For a fair comparison, we selected the corresponding French Wikipedia pages of articles in [24]. We focused on the results of articles with a size greater than 2,000 characters.…”

“…For instance, the French version of the page on "Kousseri" is 5,797 characters, while the English version is only 1,386 characters. Secondly, from the results in [24], the proposed extractive approach struggles to provide a good result when the length of the page is increasing. So, the idea is to also appreciate the quality of results provided by the abstractive approach over extractive approaches when dealing with quite long documents.…”

“…The first attempt to consider text summarization with character limitation is provided in [24]. Authors used an extractive approach based on the combination of LSA and TextRank algorithms.…”