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Dissertations / Theses on the topic 'Summarization methods'

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Published: 4 June 2021

Last updated: 25 July 2025

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1

Nahnsen, Thade. "Automation of summarization evaluation methods and their application to the summarization process." Thesis, University of Edinburgh, 2011. http://hdl.handle.net/1842/5278.

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Summarization is the process of creating a more compact textual representation of a document or a collection of documents. In view of the vast increase in electronically available information sources in the last decade, filters such as automatically generated summaries are becoming ever more important to facilitate the efficient acquisition and use of required information. Different methods using natural language processing (NLP) techniques are being used to this end. One of the shallowest approaches is the clustering of available documents and the representation of the resulting clusters by o

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Mieskes, Margot. "Exploring methods for the automatic summarization of meetings." kostenfrei, 2009. http://d-nb.info/99460517X/34.

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Le, Thien-Hoa. "Neural Methods for Sentiment Analysis and Text Summarization." Electronic Thesis or Diss., Université de Lorraine, 2020. http://www.theses.fr/2020LORR0037.

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Cette thèse aborde deux questions majeures du traitement automatique du langage naturel liées à l'analyse sémantique des textes : la détection des sentiments, et le résumé automatique. Dans ces deux applications, la nécessité d'analyser le sens du texte de manière précise est primordiale, d'une part pour identifier le sentiment exprimé au travers des mots, et d'autre part pour extraire les informations saillantes d’une phrase complexe et les réécrire de la manière la plus naturelle possible tout en respectant la sémantique du texte d'origine. Nous abordons ces deux questions par des approches

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Nishino, Masaaki. "Numerical Optimization Methods based on Discrete Structure for Text Summarization and Relational Learning." 京都大学 (Kyoto University), 2014. http://hdl.handle.net/2433/192213.

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5

Tylenda, Tomasz [Verfasser], and Gerhard [Akademischer Betreuer] Weikum. "Methods and tools for summarization of entities and facts in knowledge bases / Tomasz Tylenda. Betreuer: Gerhard Weikum." Saarbrücken : Saarländische Universitäts- und Landesbibliothek, 2015. http://d-nb.info/1077211546/34.

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6

Leite, Daniel Saraiva. "Um estudo comparativo de modelos baseados em estatísticas textuais, grafos e aprendizado de máquina para sumarização automática de textos em português." Universidade Federal de São Carlos, 2010. https://repositorio.ufscar.br/handle/ufscar/459.

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Made available in DSpace on 2016-06-02T19:05:48Z (GMT). No. of bitstreams: 1 3512.pdf: 1897835 bytes, checksum: 598f309a846cb201fe8f13be0f2e37da (MD5) Previous issue date: 2010-12-21<br>Automatic text summarization has been of great interest in Natural Language Processing due to the need of processing a huge amount of information in short time, which is usually delivered through distinct media. Thus, large-scale methods are of utmost importance for synthesizing and making access to information simpler. They aim at preserving relevant content of the sources with little or no human interventio

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Balahur, Dobrescu Alexandra. "Methods and resources for sentiment analysis in multilingual documents of different text types." Doctoral thesis, Universidad de Alicante, 2011. http://hdl.handle.net/10045/19437.

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Jakupovic, Edin. "Alternative Information Gathering on Mobile Devices." Thesis, KTH, Skolan för informations- och kommunikationsteknik (ICT), 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-210712.

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Searching and gathering information about specific topics is a time wasting, but vital practise. With the continuous growth and surpassing of desktop devices, the mobile market is becoming a more important area to consider. Due to the portability of mobile devices, certain tasks are more difficult to perform, compared to on a desktop device. Searching for information online is generally slower on mobile devices than on desktop devices, even though the majority of searches are performed on mobile devices. The largest challenges with searching for information online using mobile devices, are the

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Ahmad, Saif. "A temporal pattern identification and summarization method for complex time serial data." Thesis, University of Surrey, 2007. http://epubs.surrey.ac.uk/843297/.

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Most real-world time series data is produced by complex systems. For example, the economy is a social system which produces time series of stocks, bonds, and foreign exchange rates whereas the human body is a biological system which produces time series of heart rate variations, brain activity, and rate of blood circulation. Complex systems exhibit great variety and complexity and so does the time series emanating from these systems. However, universal principles and tools seem to govern our understanding of highly complex phenomena, processes, and dynamics. It has been argued that one of the

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Cahuina, Edward Jorge Yuri Cayllahua. "A new method for static video summarization using visual words and video temporal segmentation." reponame:Repositório Institucional da UFOP, 2013. http://www.repositorio.ufop.br/handle/123456789/4216.

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Programa de Pós-Graduação em Ciência da Computação. Departamento de Ciência da Computação, Instituto de Ciências Exatas e Biológicas, Universidade Federal de Ouro Preto.<br>Submitted by Oliveira Flávia (flavia@sisbin.ufop.br) on 2015-01-06T17:24:34Z No. of bitstreams: 2 license_rdf: 22190 bytes, checksum: 19e8a2b57ef43c09f4d7071d2153c97d (MD5) DISSERTAÇÃO_NewMethodStatic.pdf: 22958602 bytes, checksum: 14bbececbfb78222b4cef2be60a1d93d (MD5)<br>Approved for entry into archive by Gracilene Carvalho (gracilene@sisbin.ufop.br) on 2015-01-15T17:23:20Z (GMT) No. of bitstreams: 2 license_rdf: 22190 b

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Abid, Nahla Jamal. "Automatic Generation and Assessment of Source-code Method Summaries." Kent State University / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=kent1492993506814839.

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12

Monsen, Julius. "Building high-quality datasets for abstractive text summarization : A filtering‐based method applied on Swedish news articles." Thesis, Linköpings universitet, Institutionen för datavetenskap, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-176352.

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With an increasing amount of information on the internet, automatic text summarization could potentially make content more readily available for a larger variety of people. Training and evaluating text summarization models require datasets of sufficient size and quality. Today, most such datasets are in English, and for minor languages such as Swedish, it is not easy to obtain corresponding datasets with handwritten summaries. This thesis proposes methods for compiling high-quality datasets suitable for abstractive summarization from a large amount of noisy data through characterization and fi

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13

Matsubara, Shigeki, Yoshihide Kato, and Seiji Egawa. "Sentence Compression by Removing Recursive Structure from Parse Tree." Springer, 2008. http://hdl.handle.net/2237/15113.

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Pantin, Jérémie. "Détection et caractérisation sémantique de données textuelles aberrantes." Electronic Thesis or Diss., Sorbonne université, 2023. https://accesdistant.sorbonne-universite.fr/login?url=https://theses-intra.sorbonne-universite.fr/2023SORUS347.pdf.

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L'apprentissage automatique répond au problème du traitement de tâches spécifiques pour une grande variété de données. Ces algorithmes peuvent être simples ou difficiles à mettre en place, et c'est par ailleurs le même constat qui peut être fait pour les données. Les données de faible dimension (2 ou 3 dimensions) avec une représentation intuitive (ex. moyenne du prix des baguette par années) sont plus faciles à interpréter/expliquer pour un humain que les données avec des milliers de dimensions. Pour les données à faible dimension, une donnée aberrantes conduit souvent à un décalage conséquen

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MATSUBARA, Shigeki, Yoshihide KATO, Seiji EGAWA, 茂樹松原, 芳秀加藤 та 誠二江川. "構文木からの再帰構造の除去による文圧縮". 一般社団法人情報処理学会, 2008. http://hdl.handle.net/2237/15072.

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16

Hsu, Hen-Yao, and 許恒耀. "Design and Implementation of the Topic Generation Methods for Document Summarization." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/38102566931806279773.

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碩士<br>國立成功大學<br>電腦與通信工程研究所<br>96<br>In recently years, more and more Internet users rely on the search engines to help them find the information they need. However, the information they often consists of a large amount of irrelevant parts. It would often spend Internet users much time to achieve the correct information users need. To help Internet users find the information they are looking for quickly, an efficient algorithm for automatically building the summaries of a collection of documents found by a search engine in response to a user query, called DiSco (Distribution Scoring), is propos

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Kedzie, Christopher. "Salience Estimation and Faithful Generation: Modeling Methods for Text Summarization and Generation." Thesis, 2021. https://doi.org/10.7916/d8-61n8-mg23.

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This thesis is focused on a particular text-to-text generation problem, automatic summarization, where the goal is to map a large input text to a much shorter summary text. The research presented aims to both understand and tame existing machine learning models, hopefully paving the way for more reliable text-to-text generation algorithms. Somewhat against the prevailing trends, we eschew end-to-end training of an abstractive summarization model, and instead break down the text summarization problem into its constituent tasks. At a high level, we divide these tasks into two categories: content

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18

Huang, Yen-bo, and 黃彥博. "The Comparative Study of Three Automatic Scoring Methods for the Summarization of Scientific Articles." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/22013247686834026650.

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碩士<br>國立臺南大學<br>測驗統計研究所<br>96<br>Summarization demonstrates a great potential for improving students’ reading, learning, and writing. Unfortunately, it is largely neglected throughout children’s academic training. The automatic scoring method can provide students with extensive summarization practice without increasing the teacher’s workload. The purpose of this study is to compare the automatic scoring methods with human rating results. Due to school application consideration, three automatic methods are included for comparisons: concept similarity (CS), latent semantic analysis (LSA) and key

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Chen, Liang-Pu, and 陳良圃. "A Chinese-Korean Cross-language Media Retrieval and Summarization System Based on Wikipedia and Pattern Translation Methods." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/16829301079217355896.

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碩士<br>元智大學<br>資訊工程學系<br>98<br>In recent years, Korean dramas in Chinese-speaking regions have become immensely popular. They have raised people''s curiosity with the film and entertainment information of South Korea and have also increased the search for film and entertainment information related to the demand for multimedia. As most users use named entities as keywords for the query, they construct a platform that can supply useful and correct translations of named entities will become an important research topic. In this paper, we propose a method that can be applied to cross-langu

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20

Mieskes, Margot [Verfasser]. "Exploring methods for the automatic summarization of meetings = Eine Untersuchung von Methoden für die automatische Zusammenfassung von Besprechungen / vorgelegt von Margot Mieskes." 2008. http://d-nb.info/99460517X/34.

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21

Zhang, Lei. "New data analytics and visualization methods in personal data mining, cancer data analysis and sports data visualization." 2017. http://scholarworks.gsu.edu/cs_diss/126.

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In this dissertation, we discuss a reading profiling system, a biological data visualization system and a sports visualization system. Self-tracking is getting increasingly popular in the field of personal informatics. Reading profiling can be used as a personal data collection method. We present UUAT, an unintrusive user attention tracking system. In UUAT, we used user interaction data to develop technologies that help to pinpoint a users reading region (RR). Based on computed RR and user interaction data, UUAT can identify a readers reading struggle or interest. A biomarker is a measurable s

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22

Darling, William Michael. "Generalized Probabilistic Topic and Syntax Models for Natural Language Processing." Thesis, 2012. http://hdl.handle.net/10214/4001.

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This thesis proposes a generalized probabilistic approach to modelling document collections along the combined axes of both semantics and syntax. Probabilistic topic (or semantic) models view documents as random mixtures of unobserved latent topics which are themselves represented as probabilistic distributions over words. They have grown immensely in popularity since the introduction of the original topic model, Latent Dirichlet Allocation (LDA), in 2004, and have seen successes in computational linguistics, bioinformatics, political science, and many other fields. Furthermore, the modular na

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23

Zeng, Shih-Chang, and 曾士昌. "A Sentences-Based Text Summarization Method." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/69039256186158365327.

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碩士<br>國立屏東商業技術學院<br>資訊管理系(所)<br>99<br>Due to the prevalence of digital documents on the Internet, Text Summarization has been one of the important issues in many applications, like information retrieval, briefings generation, and text categorization. Traditional methods for generating summary for a single document rely heavily on term-by-sentence matrix, which is less intuitive. The semantic unit for human discourse is a sentence rather than a term. Therefore, in this thesis we proposed using sentence-by-paragraph matrix to conduct probabilistic latent semantic analysis to generate summary for

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24

Lin, Li-Tsen, and 林栗岑. "Applying semantic clustering of words on multiple documents summarization method." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/9u49np.

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碩士<br>國立中央大學<br>資訊管理學系<br>105<br>The popularity of internet has made the spread of information quickly and easier. However it also generates a lot of problems. People cannot find the information they need efficiently when they face huge amounts of information. Therefore, we apply semantic clustering of words on multiple documents summarization method, which can automatically identify the important content of the documents and provide readers a quick review of the news. In general, a document usually covers many topics, so we use WordNet to calculate the semantic relationship between words, and

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Hao-TseCheng and 鄭皓澤. "Variable-Length Abstractive Summarization using Two-stage Transformer-based Method." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/d3hsp2.

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碩士<br>國立成功大學<br>資訊工程學系<br>107<br>Due to the rapid growth of information available, how to efficiently process and utilize these text-based resources has become an increasingly crucial challenge to address. Such a problem can be solved with an automatic summarization system. Most summarization systems are divided into two types: extractive methods and abstractive methods. Extractive methods form the summary by extracting segments of text from the document. Abstractive methods process the document and then generate a text summary. The former can allow the user to specify the length of the summar

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Wei-FenHuang and 黃微芬. "Developing a Summarization Method by Improving Entity Identification and Feature Extraction." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/amkg4j.

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Shang, Tsung-Cheng, and 尚宗承. "Applying Summarization System and Information Distance Method to Biomedical Question Answering System." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/76259362842150385968.

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碩士<br>國立臺灣師範大學<br>資訊工程學系<br>102<br>The study takes Alzheimer’s disease as a subject to implement a biomedical question answering system. The purpose in the thesis is to employ both the properties of a summarization system and an information distance method to the question answering system. The machine learning techniques are also applied, attempting to find out a correct answer from the related literature and background knowledge. 　　The test data is composed of four sets of test documents. Each set includes one document, ten questions and five answer options per question. For each question, th

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28

Chen, Chao-long, and 陳朝龍. "A Text Categorization Method Based on Term Distributional Clustering and Automatic Summarization." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/73204557664150148160.

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碩士<br>國立屏東商業技術學院<br>資訊管理系<br>96<br>Owing to the exponential growth of electronic documents, research on automatic summarization is flourishing in the last decade. This is evident from the fact that Computational Linguistics (Vo. 28, No. 4, 2002) and Information Processing & Processing (Vol. 43, No. 6, 2007) both have published a special issue on automatic summarization. However, the summaries generated by these sophisticated methods have little uses except for affording document searchers a glimpse of what the document is about. Therefore, this study proposes to use the automatic summarization

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Ravindra, G. "Information Theoretic Approach To Extractive Text Summarization." Thesis, 2006. https://etd.iisc.ac.in/handle/2005/452.

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Automatic text summarization techniques, which can reduce a source text to a summary text by content generalization or selection have assumed signifi- cance in recent times due to the ever expanding information explosion created by the World Wide Web. Summaries generated by generalization of information are called abstracts and those generated by selection of portions of text (sentences, phrases etc.) are called extracts. Further, summaries could for each document separately or multiple documents could be summarized together to produce a single summary. The challenges in making machines genera

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Ravindra, G. "Information Theoretic Approach To Extractive Text Summarization." Thesis, 2006. http://hdl.handle.net/2005/452.

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Automatic text summarization techniques, which can reduce a source text to a summary text by content generalization or selection have assumed signifi- cance in recent times due to the ever expanding information explosion created by the World Wide Web. Summaries generated by generalization of information are called abstracts and those generated by selection of portions of text (sentences, phrases etc.) are called extracts. Further, summaries could for each document separately or multiple documents could be summarized together to produce a single summary. The challenges in making machines genera

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31

Huang, Yao-Ching, and 黃耀慶. "Summarization of Multi-view Surveillance Videos by an Object-Based Key Frame Extraction Method." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/06942591994137463963.

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碩士<br>輔仁大學<br>電機工程學系<br>99<br>Video summarization is an important technique which has been an interested subject in many research fields which generates a short summary of a video for the presentation to users with browsing and navigation. Multi-view development is also beneficial to video surveillance, since the vast public security area installed a lot of cameras need to filter of huge non-important information. In this paper, we propose a multi-view video summarization approach that extracts semantic-level key frames by object information from multiple cameras. Our main goal is to avoid the

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