• Journal of Information Processing Systems
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• v.15 no.6
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• pp.1365-1377
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• 2019

Summarizing the differences in Chinese-Vietnamese bilingual news plays an important supporting role in the comparative analysis of news views between China and Vietnam. Aiming at cross-language problems in the analysis of the differences between Chinese and Vietnamese bilingual news, we propose a new method of summarizing the differences based on an undirected graph model. The method extracts elements to represent the sentences, and builds a bridge between different languages based on Wikipedia's multilingual concept description page. Firstly, we calculate the similarity between Chinese and Vietnamese news sentences, and filter the bilingual sentences accordingly. Then we use the filtered sentences as nodes and the similarity grade as the weight of the edge to construct an undirected graph model. Finally, combining the random walk algorithm, the weight of the node is calculated according to the weight of the edge, and sentences with highest weight can be extracted as the difference summary. The experiment results show that our proposed approach achieved the highest score of 0.1837 on the annotated test set, which outperforms the state-of-the-art summarization models.

• International Journal of Computer Science & Network Security
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• v.23 no.3
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• pp.101-109
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• 2023

This paper discusses the use of sentiment analysis and text summarization techniques to extract valuable information from the large volume of user-generated content such as reviews, comments, and feedback on online platforms and social media. The paper highlights the effectiveness of sentiment analysis in identifying positive and negative reviews and the importance of summarizing such text to facilitate comprehension and convey essential findings to readers. The proposed work focuses on summarizing all positive and negative reviews to enhance product quality, and the performance of the generated summaries is measured using ROUGE scores. The results show promising outcomes for the developed methods in summarizing user-generated content.

• 한국HCI학회:학술대회논문집
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• 2006.02a
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• pp.400-405
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• 2006

In this paper, we present effective methods for music summarization which summarize music automatically. It could be used for sample music of on-line digital music provider or some music retrieval technology. When summarizing music, we use different two methods according to music length. First method is for finding sabi or chorus part of music which can be regarded as the most important part of music and the second method is for extracting several parts which are in different structure or have different mood in the music. Our proposed music summarization system is better than conventional system when structure of target music is explicit. The proposed method could generate just one important segment of music or several segments which have different mood in the music. Thus, this scheme will be effective for summarizing music in several applications such as online music streaming service and sample music for Tcommerce.

• Proceedings of the IEEK Conference
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• 2001.06c
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• pp.213-216
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• 2001

Key frame extraction is an important method of summarizing a long video. This paper propose a technique to automatically extract several key frames representative of its content from video. We use the color layout descriptor to select key frames from video. For selection of key frames, we calculate similarity of color layout features extracted from video, and extract key frames using similarity. An important aspect of our algorithm is that does not assume a fixed number of key frames per video; instead, it selects the number of appropriate key frames of summarizing a long video Experimental results show that our method using color layout descriptor can successfully select several key frames from a video, and we confirmed that the processing speed for extracting key frames from video is considerably fast.

• Journal of the Korean Society for Library and Information Science
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• v.46 no.1
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• pp.163-181
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• 2012

We investigated how useful video tags were in summarizing video speech and how valuable positional information was for speech summarization. Furthermore, we examined the similarity among sentences selected for a speech summary to reduce its redundancy. Based on such analysis results, we then designed and evaluated a method for automatically summarizing speech transcripts using a modified Maximum Marginal Relevance model. This model did not only reduce redundancy but it also enabled the use of social tags, title words, and sentence positional information. Finally, we compared the proposed method to the Extractor system in which key sentences of a video speech were chosen using the frequency and location information of speech content words. Results showed that the precision and recall rates of the proposed method were higher than those of the Extractor system, although there was no significant difference in the recall rates.

• Archives of Plastic Surgery
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• v.51 no.4
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• pp.441-444
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• 2024

• ETRI Journal
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• v.24 no.1
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• pp.1-11
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• 2002

A video summary abstracts the gist from an entire video and also enables efficient access to the desired content. In this paper, we propose a novel method for summarizing news video based on multimodal analysis of the content. The proposed method exploits the closed caption data to locate semantically meaningful highlights in a news video and speech signals in an audio stream to align the closed caption data with the video in a time-line. Then, the detected highlights are described using MPEG-7 Summarization Description Scheme, which allows efficient browsing of the content through such functionalities as multi-level abstracts and navigation guidance. Multimodal search and retrieval are also within the proposed framework. By indexing synchronized closed caption data, the video clips are searchable by inputting a text query. Intensive experiments with prototypical systems are presented to demonstrate the validity and reliability of the proposed method in real applications.

• Journal of Convergence Society for SMB
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• v.2 no.1
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• pp.41-50
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• 2012

In this research, we developed a scalable resource monitoring system for large scale scientific computing data centers. Usually, there are limitations and overheads for keeping track of every computing nodes because of the huge number of computing nodes. So, this research proposes a layered summarizing techniques during collection of all system resource information. The technique results in improved scalability by reducing the amount of information at higher layer. Our prototype system which is implemented with web service is applicable with the HTML5 mobile web technology on smart devices.

• Journal of the Korean Society for information Management
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• v.21 no.3
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• pp.289-303
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• 2004

This experimental study proposes a multi-document summarization method that produces optimal summaries in which users can find answers to their queries. In order to identify the most effective method for this purpose, the performance of the three summarization methods were compared. The investigated methods are sentence clustering, passage extraction through spreading activation, and clustering-passage extraction hybrid methods. The effectiveness of each summarizing method was evaluated by two criteria used to measure the accuracy and the redundancy of a summary. The passage extraction method using the sequential bnb search algorithm proved to be most effective in summarizing multiple documents with regard to summarization precision. This study proposes the passage extraction method as the optimal multi-document summarization method.

• Journal of Korean Library and Information Science Society
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• v.49 no.3
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• pp.111-132
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• 2018

The purpose of this study was to identify the structure and pattern of conclusions chapters in research articles selected in four representative journals published in Korean LIS. To analyse the structure and pattern five categories and eleven elements drawn from RA conclusions were used such as 'Drawing Attention', 'Summarizing', 'Discussing', 'Applying' and 'Extending'. The Findings are as follows. 'Conclusions' was the most used title of the chapter, and then 'conclusions and suggestions'. The conclusions sections were consisted averagely 4.2 elements. 'Summary of findings' was the most frequently elements, followed by 'summary of research process', 'suggestion of further research' and 'implication'. Also, 'summary of findings' was the most used in lengths. 'Summarizing' was the highest frequency in five categories, followed by 'Extending', and 'Applying'. The dominant first element begun conclusions sections was 'summary of findings' and the final element closed conclusion was 'suggestion of further research'. 'Summary of research process - summary of findings' order was found in the most frequent pattern of conclusions. 'Summary of findings' and 'summary of research processes' in 'Summarizing' were found as essential functions, while other elements, such as significance, 'application', 'limitations' in 'Applying' and 'Extending' were found as optional functions in the conclusions of Korean LIS research articles.