Structuring an unordered text document
This addresses a useful task for text processing applications like summarization and question answering, but it appears incremental as it applies existing methods to a specific domain.
The paper tackled the problem of segmenting unordered text documents into sections by using keywords, and demonstrated that the proposed model effectively structures Wikipedia documents using TextRank and Universal Sentence Encoder.
Segmenting an unordered text document into different sections is a very useful task in many text processing applications like multiple document summarization, question answering, etc. This paper proposes structuring of an unordered text document based on the keywords in the document. We test our approach on Wikipedia documents using both statistical and predictive methods such as the TextRank algorithm and Google's USE (Universal Sentence Encoder). From our experimental results, we show that the proposed model can effectively structure an unordered document into sections.