Language independent extractive summarization (original) (raw)
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Proceedings of the ACL 2005 on Interactive poster and demonstration sessions - ACL '05, 2005
Presentation Summarizer: A Full-Fledged NLP Service
IRJET, 2022
With the latest advancements in Computational Linguistics, complex Natural Language Processing tasks such as Text Summarization, Language Translation, Text Classification, Question Answering, Grammar Error Correction, etc. have become very feasible. Automatic text summarization on various types of transcripts has proved to be a useful way that best describes the content. However, the traditional methods rely on simpler extractive summarizationbased technique. In recent years, Transformers have proved to achieve groundbreaking results, especially for Abstractive summarization task typically known to be involuted. Another application where Computational Linguistics has enhanced significantly is Automatic Speech Recognition (ASR), Allowing computers to understand human speech.
Proceedings of the ACL 2005 on Interactive poster and demonstration sessions - ACL '05, 2005
Proceedings of the ACL 2005 on Interactive poster and demonstration sessions - ACL '05, 2005
Evaluating Interactive Summarization: an Expansion-Based Framework
2020
Allowing users to interact with multi-document summarizers is a promising direction towards improving and customizing summary results. Different ideas for interactive summarization have been proposed in previous work but these solutions are highly divergent and incomparable. In this paper, we develop an end-to-end evaluation framework for expansion-based interactive summarization, which considers the accumulating information along an interactive session. Our framework includes a procedure of collecting real user sessions and evaluation measures relying on standards, but adapted to reflect interaction. All of our solutions are intended to be released publicly as a benchmark, allowing comparison of future developments in interactive summarization. We demonstrate the use of our framework by evaluating and comparing baseline implementations that we developed for this purpose, which will serve as part of our benchmark. Our extensive experimentation and analysis of these systems motivate ...