2 |
A Novel Approach for Semantic Extractive Text Summarization
|
|
|
|
In: Applied Sciences; Volume 12; Issue 9; Pages: 4479 (2022)
|
|
Abstract:
Text summarization is a technique for shortening down or exacting a long text or document. It becomes critical when someone needs a quick and accurate summary of very long content. Manual text summarization can be expensive and time-consuming. While summarizing, some important content, such as information, concepts, and features of the document, can be lost; therefore, the retention ratio, which contains informative sentences, is lost, and if more information is added, then lengthy texts can be produced, increasing the compression ratio. Therefore, there is a tradeoff between two ratios (compression and retention). The model preserves or collects all the informative sentences by taking only the long sentences and removing the short sentences with less of a compression ratio. It tries to balance the retention ratio by avoiding text redundancies and also filters irrelevant information from the text by removing outliers. It generates sentences in chronological order as the sentences are mentioned in the original document. It also uses a heuristic approach for selecting the best cluster or group, which contains more meaningful sentences that are present in the topmost sentences of the summary. Our proposed model extractive summarizer overcomes these deficiencies and tries to balance between compression and retention ratios.
|
|
Keyword:
semantic text extraction; text extraction; text mining; text summarization
|
|
URL: https://doi.org/10.3390/app12094479
|
|
BASE
|
|
Hide details
|
|
3 |
Two New Datasets for Italian-Language Abstractive Text Summarization
|
|
|
|
In: Information; Volume 13; Issue 5; Pages: 228 (2022)
|
|
BASE
|
|
Show details
|
|
4 |
Overview of SimpleText 2021 - CLEF Workshop on Text Simplification for Scientific Information Access
|
|
|
|
In: Experimental IR Meets Multilinguality, Multimodality, and Interaction: 12th International Conference of the CLEF Association, CLEF 2021, Virtual Event, September 21–24, 2021, Proceedings ; ISBN: 978-3-030-85251-1 ; 12th Conference and Labs of the Evaluation Forum (CLEF 2021) ; https://hal.archives-ouvertes.fr/hal-03637807 ; 12th Conference and Labs of the Evaluation Forum (CLEF 2021), Sep 2021, Bucharest, Romania. pp.432-449, ⟨10.1007/978-3-030-85251-1_27⟩ ; http://clef2021.clef-initiative.eu/ (2021)
|
|
BASE
|
|
Show details
|
|
5 |
Rewards with Negative Examples for Reinforced Topic-Focused Abstractive Summarization ...
|
|
|
|
BASE
|
|
Show details
|
|
6 |
Low-Resource Dialogue Summarization with Domain-Agnostic Multi-Source Pretraining ...
|
|
|
|
BASE
|
|
Show details
|
|
7 |
HETFORMER: Heterogeneous Transformer with Sparse Attention for Long-Text Extractive Summarization ...
|
|
|
|
BASE
|
|
Show details
|
|
8 |
CLIFF: Contrastive Learning for Improving Faithfulness and Factuality in Abstractive Summarization ...
|
|
|
|
BASE
|
|
Show details
|
|
9 |
Weakly supervised discourse segmentation for multiparty oral conversations ...
|
|
|
|
BASE
|
|
Show details
|
|
10 |
Vision Guided Generative Pre-trained Language Models for Multimodal Abstractive Summarization ...
|
|
|
|
BASE
|
|
Show details
|
|
11 |
Evaluation of Summarization Systems across Gender, Age, and Race ...
|
|
|
|
BASE
|
|
Show details
|
|
12 |
Controllable Neural Dialogue Summarization with Personal Named Entity Planning ...
|
|
|
|
BASE
|
|
Show details
|
|
13 |
CSDS: A Fine-Grained Chinese Dataset for Customer Service Dialogue Summarization ...
|
|
|
|
BASE
|
|
Show details
|
|
14 |
A Thorough Evaluation of Task-Specific Pretraining for Summarization ...
|
|
|
|
BASE
|
|
Show details
|
|
16 |
Context or No Context? A preliminary exploration of human-in-the-loop approach for Incremental Temporal Summarization in meetings ...
|
|
|
|
BASE
|
|
Show details
|
|
17 |
Exploring Multitask Learning for Low-Resource Abstractive Summarization ...
|
|
|
|
BASE
|
|
Show details
|
|
18 |
Capturing Speaker Incorrectness: Speaker-Focused Post-Correction for Abstractive Dialogue Summarization ...
|
|
|
|
BASE
|
|
Show details
|
|
19 |
Narrative Embedding: Re-Contextualization Through Attention ...
|
|
|
|
BASE
|
|
Show details
|
|
20 |
TWEETSUMM - A Dialog Summarization Dataset for Customer Service ...
|
|
|
|
BASE
|
|
Show details
|
|
|
|