{"title":"An integer linear programming model for multi document summarization of learning materials using phrase embedding technique","authors":"K. Sakkaravarthy Iyyappan, S. R. Balasundaram","doi":"10.1007/s13198-024-02299-7","DOIUrl":null,"url":null,"abstract":"<h3>Abstract</h3> <p>Automatic text summarization (ATS) plays a vital role in condensing original text documents while preserving the most crucial information. Its benefits extend to various domains, including e-Learning systems, where educational content can be summarized to facilitate easier access and comprehension. Multi-document summarization (MDS) techniques enable the creation of concise summaries from groups of related text documents. Leveraging MDS for summarizing learning materials opens new avenues, offering students and teachers reference summaries for enhanced learning experiences. This paper introduces a concept-based Integer Linear Programming model for summarizing learning materials, leveraging a phrase embedding technique. Phrases are treated as fundamental and significant semantic building blocks of sentences, facilitating the comprehension and summarization of documents. Embedding techniques are employed to semantically identify related phrases, eliminate redundancy, and enhance coherence through vector representations. Summaries are generated using the ILP technique, selecting key sentences and reducing redundancy with phrase vectors. The paper proposes sentence reordering techniques based on phrases and sentences to further enhance coherence. The resulting summaries are automatically evaluated using ROUGE metrics, demonstrating the superior performance of the proposed approach compared to various benchmark and baseline methods on both the DUC 2004 benchmark dataset and the newly created educational dataset, EduSumm.</p>","PeriodicalId":14463,"journal":{"name":"International Journal of System Assurance Engineering and Management","volume":"80 1","pages":""},"PeriodicalIF":1.6000,"publicationDate":"2024-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of System Assurance Engineering and Management","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1007/s13198-024-02299-7","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
Automatic text summarization (ATS) plays a vital role in condensing original text documents while preserving the most crucial information. Its benefits extend to various domains, including e-Learning systems, where educational content can be summarized to facilitate easier access and comprehension. Multi-document summarization (MDS) techniques enable the creation of concise summaries from groups of related text documents. Leveraging MDS for summarizing learning materials opens new avenues, offering students and teachers reference summaries for enhanced learning experiences. This paper introduces a concept-based Integer Linear Programming model for summarizing learning materials, leveraging a phrase embedding technique. Phrases are treated as fundamental and significant semantic building blocks of sentences, facilitating the comprehension and summarization of documents. Embedding techniques are employed to semantically identify related phrases, eliminate redundancy, and enhance coherence through vector representations. Summaries are generated using the ILP technique, selecting key sentences and reducing redundancy with phrase vectors. The paper proposes sentence reordering techniques based on phrases and sentences to further enhance coherence. The resulting summaries are automatically evaluated using ROUGE metrics, demonstrating the superior performance of the proposed approach compared to various benchmark and baseline methods on both the DUC 2004 benchmark dataset and the newly created educational dataset, EduSumm.
期刊介绍：
This Journal is established with a view to cater to increased awareness for high quality research in the seamless integration of heterogeneous technologies to formulate bankable solutions to the emergent complex engineering problems.
Assurance engineering could be thought of as relating to the provision of higher confidence in the reliable and secure implementation of a system’s critical characteristic features through the espousal of a holistic approach by using a wide variety of cross disciplinary tools and techniques. Successful realization of sustainable and dependable products, systems and services involves an extensive adoption of Reliability, Quality, Safety and Risk related procedures for achieving high assurancelevels of performance; also pivotal are the management issues related to risk and uncertainty that govern the practical constraints encountered in their deployment. It is our intention to provide a platform for the modeling and analysis of large engineering systems, among the other aforementioned allied goals of systems assurance engineering, leading to the enforcement of performance enhancement measures. Achieving a fine balance between theory and practice is the primary focus. The Journal only publishes high quality papers that have passed the rigorous peer review procedure of an archival scientific Journal. The aim is an increasing number of submissions, wide circulation and a high impact factor.
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