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Journal articles on the topic 'News clustering'

Author: Grafiati

Published: 4 June 2021

Last updated: 1 February 2022

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1

Inoua, Sabiou M. "News-Driven Expectations and Volatility Clustering." Journal of Risk and Financial Management 13, no. 1 (2020): 17. http://dx.doi.org/10.3390/jrfm13010017.

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Financial volatility obeys two fascinating empirical regularities that apply to various assets, on various markets, and on various time scales: it is fat-tailed (more precisely power-law distributed) and it tends to be clustered in time. Many interesting models have been proposed to account for these regularities, notably agent-based models, which mimic the two empirical laws through a complex mix of nonlinear mechanisms such as traders switching between trading strategies in highly nonlinear way. This paper explains the two regularities simply in terms of traders’ attitudes towards news, an e

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Azzopardi, Joel, and Christopher Staff. "Incremental Clustering of News Reports." Algorithms 5, no. 3 (2012): 364–78. http://dx.doi.org/10.3390/a5030364.

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Dangre, N., A. Bodke, A. Date, S. Rungta, and S. S. Pathak. "System for Marathi News Clustering." Procedia Computer Science 92 (2016): 18–22. http://dx.doi.org/10.1016/j.procs.2016.07.317.

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Ambarwati, Ambarwati, and Edi Winarko. "Pengelompokan Berita Indonesia Berdasarkan Histogram Kata Menggunakan Self-Organizing Map." IJCCS (Indonesian Journal of Computing and Cybernetics Systems) 8, no. 1 (2014): 101. http://dx.doi.org/10.22146/ijccs.3500.

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AbstrakBerita merupakan sumber informasi yang dinantikan oleh manusia setiap harinya. Manusia membaca berita dengan kategori yang diinginkan. Jika komputer mampu mengelompokkan berita secara otomatis maka tentunya manusia akan lebih mudah membaca berita sesuai dengan kategori yang diinginkan. Pengelompokan berita yang berupa artikel secara otomatis sangatlah menarik karena mengorganisir artikel berita secara manual membutuhkan waktu dan biaya yang tidak sedikit.Tujuan penelitian ini adalah membuat sistem aplikasi untuk pengelompokkan artikel berita dengan menggunakan algoritma Self Organizing

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Liu, Xiaohua. "Translation of news reports related to COVID-19 of Japanese Linguistics based on page link mining." Journal of Intelligent & Fuzzy Systems 39, no. 6 (2020): 8981–88. http://dx.doi.org/10.3233/jifs-189296.

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In the face of the current epidemic situation, news reports are facing the problem of higher accuracy. The speed and accuracy of public emergency news depends on the accuracy of web page links and tags clustering. An improved web page clustering method based on the combination of topic clustering and structure clustering is proposed in this paper. The algorithm takes the result of web page structure clustering as the weight factor. Combined with the web content clustering by K-means algorithm, the basic content that meets the conditions is selected. Through the improved translator of clusterin

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Darvishy, Asghar, Hamidah Ibrahim, Fatimah Sidi, and Aida Mustapha. "A Customized Non-Exclusive Clustering Algorithm for News Recommendation Systems." JOURNAL OF UNIVERSITY OF BABYLON for Pure and Applied Sciences 27, no. 1 (2019): 368–79. http://dx.doi.org/10.29196/jubpas.v27i1.2192.

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Clustering is one of the main tasks in machine learning and data mining and is being utilized in many applications including news recommendation systems. In this paper, we propose a new non-exclusive clustering algorithm named Ordered Clustering (OC) with the aim is to increase the accuracy of news recommendation for online users. The basis of OC is a new initialization technique that groups news items into clusters based on the highest similarities between news items to accommodate news nature in which a news item can belong to different categories. Hence, in OC, multiple memberships in clust

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Blokh, Ilya, and Vassil Alexandrov. "News clustering based on similarity analysis." Procedia Computer Science 122 (2017): 715–19. http://dx.doi.org/10.1016/j.procs.2017.11.428.

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Chen, Dan Wen, Li Qiong Deng, Zhi Min Yuan, and Ling Da Wu. "Combining Multi-Modal Features for News Story Correlation Analysis." Advanced Materials Research 268-270 (July 2011): 1040–45. http://dx.doi.org/10.4028/www.scientific.net/amr.268-270.1040.

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How to combine multi-modal features effectively is a difficult problem in news story correlation analysis, this paper puts forward a new two-stage fusion approach based on visual and textual features fusion to solve this problem. First we use a co-clustering method to get the clustering groups of similar stories with the visual and semantic information of news story. And then, on the base of the result of the first step, we use different weighted strategies to analyze the news story correlation in a further way, which aim at the different type of news story. The methods can get a better result

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9

Rodrigues, David M. S. "Q-analysis Based Clustering of Online News." Interdisciplinary journal of Discontinuity, Nonlinearity, and Complexity 3, no. 3 (2014): 227–36. http://dx.doi.org/10.5890/dnc.2014.09.002.

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10

Kayal, Subhradeep. "Face Clustering Experiments on News Video Images." Journal of Automation and Control Engineering 1, no. 3 (2013): 213–16. http://dx.doi.org/10.12720/joace.1.3.213-216.

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11

Montalvo, Soto, Raquel Martínez, Víctor Fresno, and Agustín Delgado. "Exploiting named entities for bilingual news clustering." Journal of the Association for Information Science and Technology 66, no. 2 (2014): 363–76. http://dx.doi.org/10.1002/asi.23175.

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12

Bouras, Christos, and Vassilis Tsogkas. "Improving news articles recommendations via user clustering." International Journal of Machine Learning and Cybernetics 8, no. 1 (2014): 223–37. http://dx.doi.org/10.1007/s13042-014-0316-3.

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13

Shomanov, A. S., and M. E. Mansurova. "Parallel news clustering and topic modeling approaches." Journal of Physics: Conference Series 1727 (January 2021): 012018. http://dx.doi.org/10.1088/1742-6596/1727/1/012018.

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Arun Manicka Raja, M., and S. Swamynathan. "Hierarchical Stream Clustering Based NEWS Summarization System." Computers, Materials & Continua 70, no. 1 (2022): 1263–80. http://dx.doi.org/10.32604/cmc.2022.019451.

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Al-Augby, Salam, Sebastian Majewski, Agnieszka Majewska, and Kesra Nermend. "A Comparison Of K-Means And Fuzzy C-Means Clustering Methods For A Sample Of Gulf Cooperation Council Stock Markets." Folia Oeconomica Stetinensia 14, no. 2 (2014): 19–36. http://dx.doi.org/10.1515/foli-2015-0001.

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Abstract The main goal of this article is to compare data-mining clustering methods (k-means and fuzzy c-means) based on a sample of banking and energy companies on the Gulf Cooperation Council (GCC) stock markets. We examined these companies for a pattern that reflected the effect of news on the bank sector’s stocks throughout October, November, and December 2012. Correlation coefficients and t-statistics for the good news indicator (GNI) and the bad news indicator (BNI) and financial factors, such as PER, PBV, DY and rate of return, were used as diagnostic variables for the clustering method

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Acharya, Viral V., Peter DeMarzo, and Ilan Kremer. "Endogenous Information Flows and the Clustering of Announcements." American Economic Review 101, no. 7 (2011): 2955–79. http://dx.doi.org/10.1257/aer.101.7.2955.

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We consider the strategic timing of information releases in a dynamic disclosure model. Because investors don't know whether or when the firm is informed, the firm will not necessarily disclose immediately. We show that bad market news can trigger the immediate release of information by firms. Conversely, good market news slows the release of information by firms. Thus, our model generates clustering of negative announcements. Surprisingly, this result holds only when firms can preemptively disclose their own information prior to the arrival of external information. These results have implicat

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Ahdi, A. B., K. R. SW, and A. Herdiani. "Analysis and Implementation of Graph Clustering for Digital News Using Star Clustering Algorithm." Journal of Physics: Conference Series 801 (January 2017): 012061. http://dx.doi.org/10.1088/1742-6596/801/1/012061.

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18

Lakkad, Aditya Kamleshbhai, Rushit Dharmendrabhai Bhadaniya, Vraj Nareshkumar Shah, and Lavanya K. "Complex Events Processing on Live News Events Using Apache Kafka and Clustering Techniques." International Journal of Intelligent Information Technologies 17, no. 1 (2021): 39–52. http://dx.doi.org/10.4018/ijiit.2021010103.

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The explosive growth of news and news content generated worldwide, coupled with the expansion through online media and rapid access to data, has made trouble and screening of news tedious. An expanding need for a model that can reprocess, break down, and order main content to extract interpretable information, explicitly recognizing subjects and content-driven groupings of articles. This paper proposed automated analyzing heterogeneous news through complex event processing (CEP) and machine learning (ML) algorithms. Initially, news content streamed using Apache Kafka, stored in Apache Druid, a

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19

Sunita, B., and T. John Peter. "Analysis of Various Multilingual Document Clustering." Journal of Computational and Theoretical Nanoscience 17, no. 9 (2020): 3921–26. http://dx.doi.org/10.1166/jctn.2020.8989.

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Today’s world is heading towards data science era. As the volume of the data is increasing extremely at exponential rate and data is produced and circulated all over the world, not only in English languages but in every regional language too. Since the data’s are in multilingual it is extremely difficult to manage such huge amount of variant data. Hence there is a scope for research work on multilingual document clustering. By document clustering we can retrieve the information of user query. This technique is to divide a given set of documents into a certain number of clusters. The aim is to

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20

Driscoll, Kevin, and Kjerstin Thorson. "Searching and Clustering Methodologies." ANNALS of the American Academy of Political and Social Science 659, no. 1 (2015): 134–48. http://dx.doi.org/10.1177/0002716215570570.

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People create, consume, and share content online in increasingly complex ways, often including multiple news, entertainment, and social media platforms. This article explores methods for tracing political media content across overlapping communication infrastructures. Using the 2011 Occupy Movement protests and 2013 consumer boycotts as cases, we illustrate methods for creating integrated datasets of political event-related social media content by (1) using fixed URLs to link posts across platforms ( URL-based integration) and (2) using semiautomated text clustering to identify similar posts a

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21

Kim, Jeong-Soo, Yuchul Jung, Heung-Seon Oh, Kwangyoung Kim, and Jungsun Yoon. "A Study on Clustering News Articles in Korean." Journal of Engineering and Applied Sciences 14, no. 11 (2019): 3492–97. http://dx.doi.org/10.36478/jeasci.2019.3492.3497.

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22

Bora, Nibir Nayan, Bhabani Shankar Prasad Mishra, and Satchidananda Dehuri. "Heuristic Frequent Term-Based Clustering of News Headlines." Procedia Technology 6 (2012): 436–43. http://dx.doi.org/10.1016/j.protcy.2012.10.052.

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23

Bouras, Christos, and Vassilis Tsogkas. "A clustering technique for news articles using WordNet." Knowledge-Based Systems 36 (December 2012): 115–28. http://dx.doi.org/10.1016/j.knosys.2012.06.015.

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24

Pratama, M. F. E., R. S. W. Kemas, and H. Anisa. "Digital News Graph Clustering using Chinese Whispers Algorithm." Journal of Physics: Conference Series 801 (January 2017): 012062. http://dx.doi.org/10.1088/1742-6596/801/1/012062.

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25

Ji, Ping, Liujuan Cao, Xiguang Zhang, Longfei Zhang, and Weimin Wu. "News videos anchor person detection by shot clustering." Neurocomputing 123 (January 2014): 86–99. http://dx.doi.org/10.1016/j.neucom.2013.06.003.

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26

Jenson, T., and A. S. Girsang. "Performance of news clustering using ant colony optimization." Journal of Physics: Conference Series 1566 (June 2020): 012101. http://dx.doi.org/10.1088/1742-6596/1566/1/012101.

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27

Zheng, Li, Lei Li, Wenxing Hong, and Tao Li. "PENETRATE: Personalized news recommendation using ensemble hierarchical clustering." Expert Systems with Applications 40, no. 6 (2013): 2127–36. http://dx.doi.org/10.1016/j.eswa.2012.10.029.

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28

Bari, Omar A., and Arvin Agah. "Ensembles of Text and Time-Series Models for Automatic Generation of Financial Trading Signals from Social Media Content." Journal of Intelligent Systems 29, no. 1 (2018): 753–72. http://dx.doi.org/10.1515/jisys-2017-0567.

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Abstract Event studies in finance have focused on traditional news headlines to assess the impact an event has on a traded company. The increased proliferation of news and information produced by social media content has disrupted this trend. Although researchers have begun to identify trading opportunities from social media platforms, such as Twitter, almost all techniques use a general sentiment from large collections of tweets. Though useful, general sentiment does not provide an opportunity to indicate specific events worthy of affecting stock prices. This work presents an event clustering

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29

Zhang, Yong, Rui Fang Liu, and Rui Yang Luo. "Improving Frequent-Term Based Text Clustering with Word Belief Network." Applied Mechanics and Materials 411-414 (September 2013): 207–14. http://dx.doi.org/10.4028/www.scientific.net/amm.411-414.207.

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The algorithm of frequent-term based text clustering (FTC) can be applied to news topic clustering system, in order to help users locate interested topics and articles quickly. But it is difficult to set support threshold for mining association rules. This paper tries to build a word belief network, which satisfies basic rules of small worlds. So we can improve FTC algorithm with characteristics of small worlds and implement text clustering quickly. The paper puts forward an idea that adopts inverted index into this algorithm, which simplifies programming and improves operation efficiency. The

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Toujani, Radhia, and Jalel Akaichi. "Event news detection and citizens community structure for disaster management in social networks." Online Information Review 43, no. 1 (2019): 113–32. http://dx.doi.org/10.1108/oir-03-2018-0091.

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Purpose Nowadays, the event detection is so important in gathering news from social media. Indeed, it is widely employed by journalists to generate early alerts of reported stories. In order to incorporate available data on social media into a news story, journalists must manually process, compile and verify the news content within a very short time span. Despite its utility and importance, this process is time-consuming and labor-intensive for media organizations. Because of the afore-mentioned reason and as social media provides an essential source of data used as a support for professional

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Wang, Chong, Lisa Kim, Grace Bang, et al. "Discovery News: A Generic Framework for Financial News Recommendation." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 08 (2020): 13390–95. http://dx.doi.org/10.1609/aaai.v34i08.7054.

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In the financial services industry, it is crucial for analysts to constantly monitor and stay informed on the latest developments of their portfolio of companies. This ensures that analysts are up-to-date in their analysis and provide highly credible and timely insights. Currently, analysts receive news alerts through manually created news alert subscriptions that are often noisy and difficult to manage. The manual review process is time-consuming and error-prone. We demonstrate Discovery News, a framework for an automated news recommender system for financial analysis at S&P's Global Rati

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Yi, Bo, Yong Wang, Xin Chen, and Ying Wang. "Extracting Hot Topics from Microblogging Based on Keywords Detection and Text Clustering." Applied Mechanics and Materials 303-306 (February 2013): 2289–93. http://dx.doi.org/10.4028/www.scientific.net/amm.303-306.2289.

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Following with news and forums, microblogging becomes the third largest source of Internet public opinion. So it is necessary to do research of microblogging topic discovery. Firstly, we detect hot topics through the the keywords detection algorithm. Secondly, elect most popular microblogging text in the massive microblogging text by combining of keywords weigh and textual information entropy. Finally, using the dynamic clustering algorithm, the microblogging text elected, will form into different news topics by clustering polymerization. According to experimental validation of the true microb

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Kim, Junhoe, Jinwook Bok, Jaeyoung Kim, and Jinwook Seo. "NEWS²: A Visual Analytics System for Debugging Article Clustering Algorithms." KIISE Transactions on Computing Practices 26, no. 2 (2020): 74–80. http://dx.doi.org/10.5626/ktcp.2020.26.2.74.

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Jo, Tae-Ho. "Table based Single Pass Algorithm for Clustering News Articles." International Journal of Fuzzy Logic and Intelligent Systems 8, no. 3 (2008): 231–37. http://dx.doi.org/10.5391/ijfis.2008.8.3.231.

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Montalvo, Soto, Raquel Martínez, and Víctor Fresno. "Quality prediction of multilingual news clustering: An experimental study." Journal of Information Science 41, no. 4 (2015): 518–30. http://dx.doi.org/10.1177/0165551515586671.

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Utomo, Vincent, and Jenq-Shiou Leu. "Automatic news-roundup generation using clustering, extraction, and presentation." Multimedia Systems 26, no. 2 (2019): 201–21. http://dx.doi.org/10.1007/s00530-019-00638-4.

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Budiarto, Arif, Reza Rahutomo, Hendra Novyantara Putra, Tjeng Wawan Cenggoro, Muhamad Fitra Kacamarga, and Bens Pardamean. "Unsupervised News Topic Modelling with Doc2Vec and Spherical Clustering." Procedia Computer Science 179 (2021): 40–46. http://dx.doi.org/10.1016/j.procs.2020.12.007.

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Liang, Buyun, Na Li, Zheng He, Zhongyuan Wang, Youming Fu, and Tao Lu. "News Video Summarization Combining SURF and Color Histogram Features." Entropy 23, no. 8 (2021): 982. http://dx.doi.org/10.3390/e23080982.

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Because the data volume of news videos is increasing exponentially, a way to quickly browse a sketch of the video is important in various applications, such as news media, archives and publicity. This paper proposes a news video summarization method based on SURF features and an improved clustering algorithm, to overcome the defects in existing algorithms that fail to account for changes in shot complexity. Firstly, we extracted SURF features from the video sequences and matched the features between adjacent frames, and then detected the abrupt and gradual boundaries of the shot by calculating

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Hong, Xudong, Zhengtao Yu, Moming Tang, and Yantuan Xian. "Cross-lingual event-centered news clustering based on elements semantic correlations of different news." Multimedia Tools and Applications 76, no. 23 (2017): 25129–43. http://dx.doi.org/10.1007/s11042-017-4838-z.

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Nadamoto, Akiyo, and Keigo Sakai. "Detecting and presenting welcome-news for tourists from user reviews." International Journal of Web Information Systems 13, no. 4 (2017): 354–69. http://dx.doi.org/10.1108/ijwis-04-2017-0033.

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Purpose Recently, people usually use the internet to obtain travel information, when they plan their travel. They especially want to obtain sightseeing spot information from reviews, but there are huge amounts of reviews of sightseeing spots. Users therefore cannot obtain important information from the reviews easily. As described herein, this paper aims to propose a system that automatically extracts and presents welcome news for sightseeing spots from reviews. This proposed Welcome-news is a “useful information” and “unexpected information” related to travel. Design/methodology/approach The

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41

Li, Bo, Yibin Liao, and Zheng Qin. "Precomputed Clustering for Movie Recommendation System in Real Time." Journal of Applied Mathematics 2014 (2014): 1–9. http://dx.doi.org/10.1155/2014/742341.

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A recommendation system delivers customized data (articles, news, images, music, movies, etc.) to its users. As the interest of recommendation systems grows, we started working on the movie recommendation systems. Most research efforts in the fields of movie recommendation system are focusing on discovering the most relevant features from users, or seeking out users who share same tastes as that of the given user as well as recommending the movies according to the liking of these sought users or seeking out users who share a connection with other people (friends, classmates, colleagues, etc.)

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Bisandu, Desmond Bala, Rajesh Prasad, and Musa Muhammad Liman. "Clustering news articles using efficient similarity measure and N-grams." International Journal of Knowledge Engineering and Data Mining 5, no. 4 (2018): 333. http://dx.doi.org/10.1504/ijkedm.2018.095525.

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Prasad, Rajesh, Desmond Bisandu, and Musa Liman. "Clustering News Articles using Efficient Similarity Measure and N-grams." International Journal of Knowledge Engineering and Data Mining 5, no. 1 (2018): 1. http://dx.doi.org/10.1504/ijkedm.2018.10016103.

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Yang, Peng, Wenhan Li, and Guangzhen Zhao. "Language Model-Driven Topic Clustering and Summarization for News Articles." IEEE Access 7 (2019): 185506–19. http://dx.doi.org/10.1109/access.2019.2960538.

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Wu, Xiao, Chong-Wah Ngo, and Alexander G. Hauptmann. "Multimodal News Story Clustering With Pairwise Visual Near-Duplicate Constraint." IEEE Transactions on Multimedia 10, no. 2 (2008): 188–99. http://dx.doi.org/10.1109/tmm.2007.911778.

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Phillips, David P., and Lundie L. Carstensen. "Clustering of Teenage Suicides after Television News Stories about Suicide." New England Journal of Medicine 315, no. 11 (1986): 685–89. http://dx.doi.org/10.1056/nejm198609113151106.

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Pourvali, Mohsen, and Salvatore Orlando. "Enriching Documents by Linking Salient Entities and Lexical-Semantic Expansion." Journal of Intelligent Systems 29, no. 1 (2018): 1109–21. http://dx.doi.org/10.1515/jisys-2018-0098.

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Abstract This paper explores a multi-strategy technique that aims at enriching text documents for improving clustering quality. We use a combination of entity linking and document summarization in order to determine the identity of the most salient entities mentioned in texts. To effectively enrich documents without introducing noise, we limit ourselves to the text fragments mentioning the salient entities, in turn, belonging to a knowledge base like Wikipedia, while the actual enrichment of text fragments is carried out using WordNet. To feed clustering algorithms, we investigate different do

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Sato, Shosuke, Toru Okamoto, and Shunichi Koshimura. "Text-Data Reduction Method to Grasp the Sequence of a Disaster Situation: Case Study of Web News Analysis of the 2015 Typhoons 17 and 18." Journal of Disaster Research 12, no. 2 (2017): 329–34. http://dx.doi.org/10.20965/jdr.2017.p0329.

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This study aims to compress web news, delivered as a big-data source after disasters. In this paper, article clustering, which is a combination of conventional means and an algorithm that selects the representative articles of each cluster, is designed and adopted. Experiments are conducted by evaluators. The proposed algorithm is in accord with the evaluators for 50s% of the clustering and for about 30s% to 40s% of the representative-article selection.

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Hegazi, Aya, Ahmed Taha, and Mazen Mohamed Selim. "Copy-Move Forgery Detection Based on Automatic Threshold Estimation." International Journal of Sociotechnology and Knowledge Development 12, no. 1 (2020): 1–23. http://dx.doi.org/10.4018/ijskd.2020010101.

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Recently, users and news followers across websites face many fabricated images. Moreover, it goes far beyond that to the point of defaming or imprisoning a person. Hence, image authentication has become a significant issue. One of the most common tampering techniques is copy-move. Keypoint-based methods are considered as an effective method for detecting copy-move forgeries. In such methods, the feature extraction process is followed by applying a clustering technique to group spatially close keypoints. Most clustering techniques highly depend on the existence of a specific threshold to termin

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Grapă, Teodora-Elena. "Joker in News Media Discourse." Studia Universitatis Babeș-Bolyai Ephemerides 65, no. 2 (2020): 41–65. http://dx.doi.org/10.24193/subbeph.2020.2.03.

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"The entertainment media often delivers cultural symbols, which occasionally inform news media discourse. Such is the case of the “Joker” being used as a symbol of chaos. Since the character’s existence and popularity generated a pool of possibilities for political associations, the latest Joker film by director Todd Phillips, which premiered in 2019, caused controversy on many levels: “The real threat of Joker is hiding in plain sight” (The New York Times 2019); “Joker isn’t an ode to the far right – it’s a warning against austerity” (The Guardian 2019). The polemical aspect of the discourse

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