Relevant bibliographies by topics / Webpage

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Webpage'

Author: Grafiati
Published: 4 June 2021
Last updated: 15 June 2025

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Journal articles on the topic "Webpage"

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Liu, Jie, Ling Bai, and Xiang Yang Huang. "A Method Shielding the Chinese Game Webpage Based on Ontology." Advanced Materials Research 219-220 (March 2011): 1454–58. http://dx.doi.org/10.4028/www.scientific.net/amr.219-220.1454.

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As online gaming addiction has a serious impact on the healthy growth of young people, this paper presents a method that uses the ontology to shield Chinese game webpage. This method, based on positive example webpages and counter example webpages to calculate weight of feature words, to establish domain feature thesaurus and make ontology; then according to positive example WebPages, calculate weight of ontology elements in all parts of webpage to get ontology element weight database; then intercept webpage from the network application layer, identify candidate webpage (candidate) based on domain feature thesaurus; finally carry out semantic relevancy computing and shielding the game webpages in candidates. Experiments showed the shielding accuracy rate had arrived 98.8%. The principle of the method can be extended to other domains.
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Wang, Dong Mei, Ming Ma, and Yan Sun. "Sensitive Webpage Filter Based on Multiple Filtering." Applied Mechanics and Materials 241-244 (December 2012): 2891–96. http://dx.doi.org/10.4028/www.scientific.net/amm.241-244.2891.

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In order to improve the accuracy and real-time performance of webpage filtering, a sensitive webpage filter based on multiple filtering was designed. Firstly, the URL is gained from IE browser’s address bar by BHO technology; Secondly, match the webpage text with sensitive vocabulary database using SMA algorithm; Finally, use the sensitive image detecting algorithm combing face detection, skin detection, skin text detection and classification to filter sensitive images in the webpage. The Simulation experimental results showed that the sensitive webpage filter can effectively intercept and filter sensitive webpages, meeting the accuracy and the real-time requirement of webpage filtering.
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Yi, WANG, and DENG Jiamin. "A Technical Communication Approach to Website Technical Translation of Chongqing Manufacturing Enterprises: A Case Study of About Us." Asia-Pacific Journal of Humanities and Social Sciences 2, no. 3 (2022): 130–43. http://dx.doi.org/10.53789/j.1653-0465.2022.0203.016.p.

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In the era of globalization and internetization, a growing number of manufacturing enterprises in Chongqing plan to “go global”. The enterprise webpage, the online portal of the enterprise, plays an important role. At present, domestic translators’ understanding of webpage translation is still limited to text translation due to the influence of traditional translation ideas, resulting in poor readability and usability of English webpages of Chongqing manufacturing enterprises. Therefore, this paper compares the English webpages of local manufacturing enterprises in Chongqing with those of well-known foreign manufacturing enterprises. From the perspective of technical communication, taking the About Us as an example, this paper explores the relationship between technical communication and the English webpages of manufacturing enterprises, the presentation of webpage text, the translation of text content and the standard of the logical structure of the text, in order to help translators more accurately understand the task and the process of webpage technical translation.
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Feng, Jian, Yuqiang Qiao, Ou Ye, and Ying Zhang. "Detecting phishing webpages via homology analysis of webpage structure." PeerJ Computer Science 8 (February 1, 2022): e868. http://dx.doi.org/10.7717/peerj-cs.868.

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Phishing webpages are often generated by phishing kits or evolved from existing kits. Therefore, the homology analysis of phishing webpages can help curb the proliferation of phishing webpages from the source. Based on the observation that phishing webpages belonging to the same family have similar page structures, a homology detection method based on webpage clustering according to structural similarity is proposed. The method consists of two stages. The first stage realizes model construction. Firstly, it extracts the structural features and style attributes of webpages through the document structure and vectorizes them, and then assigns different weights to different features, and measures the similarity of webpages and guides webpage clustering by webpage difference index. The second phase completes the detection of webpages to be tested. The fingerprint generation algorithm using double compressions generates fingerprints for the centres of the clusters and the webpages to be tested respectively and accelerates the detection process of the webpages to be tested through bitwise comparison. Experiments show that, compared with the existing methods, the proposed method can accurately locate the family of phishing webpages and can detect phishing webpages efficiently.
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Belfedhal, Alaa Eddine. "Multi-Modal Deep Learning for Effective Malicious Webpage Detection." Revue d'Intelligence Artificielle 37, no. 4 (2023): 1005–13. http://dx.doi.org/10.18280/ria.370422.

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The pervasive threat of malicious webpages, which can lead to financial loss, data breaches, and malware infections, underscores the need for effective detection methods. Conventional techniques for detecting malicious web content primarily rely on URL-based features or features extracted from various webpage components, employing a single feature vector input into a machine learning model for classifying webpages as benign or malicious. However, these approaches insufficiently address the complexities inherent in malicious webpages. To overcome this limitation, a novel Multi-Modal Deep Learning method for malicious webpage detection is proposed in this study. Three types of automatically extracted features, specifically those derived from the URL, the JavaScript code, and the webpage text, are leveraged. Each feature type is processed by a distinct deep learning model, facilitating a comprehensive analysis of the webpage. The proposed method demonstrates a high degree of effectiveness, achieving an accuracy rate of 97.90% and a false negative rate of a mere 2%. The results highlight the advantages of utilizing multi-modal features and deep learning techniques for detecting malicious webpages. By considering various aspects of web content, the proposed method offers improved accuracy and a more comprehensive understanding of malicious activities, thereby enhancing web user security and effectively mitigating the risks associated with malicious webpages.
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Xu, Shanshan. "The Study of Interpersonal Function of Yellow River Culture Tourism Webpage from the Perspective of the Appraisal Theory." Higher Education and Practice 2, no. 1 (2025): 67–73. https://doi.org/10.62381/h251111.

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With the development of multimedia technology, people’s channels for obtaining tourism information have undergone tremendous changes, and the tourism webpage has become an important window for them to understand Yellow River culture, and it is also the fastest and most convenient information carrier for communication with tourism product sellers. Taking the interpersonal function construction as the perspective, the evaluation theory as the framework, the Yellow River cultural tourism webpage and the foreign cultural tourism webpage as the research object, this paper builds its own corpus, and compare the similarities and differences in the construction of interpersonal functions of Chinese and foreign cultural tourism webpages, so as to reveal the problems existing in the construction of interpersonal functions of Yellow River cultural tourism webpages, and propose corresponding solution strategies based on the interpersonal function construction methods of foreign cultural tourism webpages.
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Wang, Yilin, Siqing Xue, and Jun Song. "A Malicious Webpage Detection Method Based on Graph Convolutional Network." Mathematics 10, no. 19 (2022): 3496. http://dx.doi.org/10.3390/math10193496.

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In recent years, with the rapid development of the Internet and information technology, video websites, shopping websites, and other portals have grown rapidly. However, malicious webpages can disguise themselves as benign websites and steal users’ private information, which seriously threatens network security. Current detection methods for malicious webpages do not fully utilize the syntactic and semantic information in the web source code. In this paper, we propose a GCN-based malicious webpage detection method (GMWD), which constructs a text graph to describe and then a GCN model to learn the syntactic and semantic correlations within and between webpage source codes. We replace word nodes in the text graph with phrase nodes to better maintain the syntactic and semantic integrity of the webpage source code. In addition, we use the URL links appearing in the source code as auxiliary detection information to further improve the detection accuracy. The experiments showed that the proposed method can achieve 99.86% accuracy and a 0.137% false negative rate, achieving a better performance than other related malicious webpage detection methods.
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Yuk, Simun, and Youngho Cho. "A Time-Based Dynamic Operation Model for Webpage Steganography Methods." Electronics 9, no. 12 (2020): 2113. http://dx.doi.org/10.3390/electronics9122113.

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The webpage steganography technique has been used for a covert communication method for various purposes in which a sender embeds a secret message into a plain webpage file like an HTML file by using various steganography methods. With human eyes, it is very difficult to distinguish between the original webpage (cover webpage) and the modified webpage with the secret data (stego webpage) because both are displayed alike in a web browser. In this approach, when two communicating entities want to share a secret message, a sender uploads a stego webpage to a web server or modifies an existing webpage in the web server by using a webpage steganography method, and then a receiver accesses the stego webpage to download and extract the embedded secret data from it. Meanwhile, according to our extensive survey, we observed that most webpage steganography methods focused on proposing or improving steganography algorithms but did not well address how to operate a stego webpage as time passes. However, if a stego webpage is used in a static way such that the stego webpage does not change and is constantly exposed to web clients until the sender removes it, such a static operation approach will limit or badly affect the hiding capacity and undetectability of a webpage steganography method. By this motivation, in this paper, we proposed a time-based dynamic operation model (TDOM) that improves the performance of existing webpage steganography methods in terms of hiding capacity and undetectability by dynamically replacing the stego webpage with other stego webpages or the original webpage. In addition, we designed two time-based dynamic operation algorithms (TDOA-C and TDOA-U), which improve the hiding capacity of existing methods and TDOA-U for improving the undetectability of existing methods, respectively. To validate our model and show the performance of our proposed algorithms, we conducted extensive comparative experiments and numerical analysis by implementing two webpage steganography methods with our TDOM (CCL with TDOA-C and COA with TDOA-C) and tested them in the web environment. According to our experiments and analysis, our proposed algorithms could significantly improve the hiding capacity and undetectability of two existing webpage steganography methods.
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Yuan, Xiao Yan. "Research on Search Sorting Algorithm Based on Multi-Dimensional Matching." Advanced Materials Research 926-930 (May 2014): 3195–99. http://dx.doi.org/10.4028/www.scientific.net/amr.926-930.3195.

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Since the current search sorting algorithms cannot find the desirable webpages quickly and accurately, a novel search sorting algorithm based on multi-dimensional matching is proposed in this study. This algorithm computes the semantic similarity of search terms based on ontology concept, and then the relevance of temporal information of those search terms with time of webpage. As a result, the relevance of the search term with the content of the webpage is calculated, hence realizing most appropriate webpage sorting. Finally, several methods are compared in terms of their average precisions and average recall ratios.
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Jayalakshmi, N., P. Padmaja, and G. Jaya Suma. "Webpage Recommendation System Using Interesting Subgraphs and Laplace Based k-Nearest Neighbor." International Journal of Pattern Recognition and Artificial Intelligence 34, no. 03 (2019): 2053003. http://dx.doi.org/10.1142/s0218001420530031.

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An interesting research area that permits the user to mine the significant information, called frequent subgraph, is Graph-Based Data Mining (GBDM). One of the well-known algorithms developed to extract frequent patterns is GASTON algorithm. Retrieving the interesting webpages from the log files contributes heavily to various applications. In this work, a webpage recommendation system has been proposed by introducing Chronological Cuckoo Search (Chronological-CS) algorithm and the Laplace correction based k-Nearest Neighbor (LKNN) to retrieve the useful webpage from the interesting webpage. Initially, W-Gaston algorithm extracts the interesting subgraph from the log files and provides it to the proposed webpage recommendation system. The interesting subgraphs subjected to clustering with the proposed Chronological-CS algorithm, which is developed by integrating the chronological concept into Cuckoo Search (CS) algorithm, provide various cluster groups. Then, the proposed LKNN algorithm recommends the webpage from the clusters. Simulation of the proposed webpage recommendation algorithm is done by utilizing the data from MSNBC and weblog database. The results are compared with various existing webpage recommendation models and analyzed based on precision, recall, and F-measure. The proposed webpage recommendation model achieved better performance than the existing models with the values of 0.9194, 0.8947, and 0.86736, respectively, for the precision, recall, and F-measure.
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Dissertations / Theses on the topic "Webpage"

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Lo, Kwok Chu. "Partial mobile webpage adaptation /." View abstract or full-text, 2007. http://library.ust.hk/cgi/db/thesis.pl?CSED%202007%20LO.

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Deng, Liqiong. "Beyond usability -- affect in web browsing." [College Station, Tex. : Texas A&M University, 2006. http://hdl.handle.net/1969.1/ETD-TAMU-1829.

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Park, Sunyoung. "Webpage design optimization using genetic algorithm driven CSS." [Ames, Iowa : Iowa State University], 2007.

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Van, Trien Do. "Supporting webpage revisiting with history data and visualization." Thesis, University of Leeds, 2013. http://etheses.whiterose.ac.uk/4883/.

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This research addresses the general topic of “keeping found things found” by investigating difficulties people encounter when revisiting webpages. The overall aim of the research is to design, develop and evaluate a web history tool that addresses these difficulties. An empirical study has been conducted. Participants recorded their web navigation for three months using a Firefox add-on. Each participant then took part in a controlled laboratory experiment, to revisit webpages they had visited neither frequently (on only one day) nor recently (1 week or 1 month ago). Ten underlying causes of failure were discovered. Overall, 61% of the failures occurred when the target page: 1) had originally been accessed via search results; 2) was on a topic a participant often looked at; or 3) was on a known but large website. Based on the findings of the empirical study, a new visualization history tool which supports people in revisiting webpages has been designed and developed as an add-on for Firefox. The tool has two main novel aspects. Firstly, by providing different navigation techniques, it enables users to revisit webpages within their long-term web history. Secondly, the visualization presentation is created based on the user’s navigational paths (even crossing different tabs) rather than the chronology which webpages were visited. Evidence about the benefits of the visualization history tool has been provided through a three month field study. The results showed that such a history tool solved the identified causes of failure and helped participants succeed on 96% of revisiting occasions. They particularly used the tool to revisit webpages which had been visited neither frequently and nor recently. Participants often took only 3 steps to revisit a webpage. Overall, they were satisfied with the tool and rated it 4.1/5.0, and 84% of them wanted to keep using the tool after the evaluation.
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Law, Marc Teva. "Distance metric learning for image and webpage comparison." Thesis, Paris 6, 2015. http://www.theses.fr/2015PA066019/document.

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Cette thèse se focalise sur l'apprentissage de distance pour la comparaison d'images ou de pages Web. Les distances (ou métriques) sont exploitées dans divers contextes de l'apprentissage automatique et de la vision artificielle tels que la recherche des k plus proches voisins, le partitionnement, les machines à vecteurs de support, la recherche d'information/images, la visualisation etc. Nous nous intéressons dans cette thèse à l'apprentissage de fonction de distance paramétrée par une matrice symétrique semi-définie positive. Ce modèle, appelé (par abus) apprentissage de distance de Mahalanobis, consiste à apprendre une transformation linéaire des données telle que la distance euclidienne dans l'espace projeté appris satisfasse les contraintes d'apprentissage.Premièrement, nous proposons une méthode basée sur la comparaison de distances relatives qui prend en compte des relations riches entre les données, et exploite des similarités entre quadruplets d'exemples. Nous appliquons cette méthode aux attributs relatifs et à la classification hiérarchique d'images.Deuxièmement, nous proposons une nouvelle méthode de régularisation qui permet de contrôler le rang de la matrice apprise, limitant ainsi le nombre de paramètres indépendants appris et le sur-apprentissage. Nous montrons l'intérêt de notre méthode sur des bases synthétiques et réelles d'identification de visage.Enfin, nous proposons une nouvelle méthode de détection automatique de changement dans les pages Web, dans un contexte d'archivage. Pour cela, nous utilisons les relations de distance temporelle entre différentes versions d'une même page Web. La métrique apprise de façon entièrement non supervisée détecte les régions d'intérêt de la page et ignore le contenu non informatif tel que les menus et publicités. Nous montrons l'intérêt de la méthode sur différents sites Web<br>This thesis focuses on distance metric learning for image and webpage comparison. Distance metrics are used in many machine learning and computer vision contexts such as k-nearest neighbors classification, clustering, support vector machine, information/image retrieval, visualization etc. In this thesis, we focus on Mahalanobis-like distance metric learning where the learned model is parametered by a symmetric positive semidefinite matrix. It learns a linear tranformation such that the Euclidean distance in the induced projected space satisfies learning constraints.First, we propose a method based on comparison between relative distances that takes rich relations between data into account, and exploits similarities between quadruplets of examples. We apply this method on relative attributes and hierarchical image classification. Second, we propose a new regularization method that controls the rank of the learned matrix, limiting the number of independent parameters and overfitting. We show the interest of our method on synthetic and real-world recognition datasets. Eventually, we propose a novel Webpage change detection framework in a context of archiving. For this purpose, we use temporal distance relations between different versions of a same Webpage. The metric learned in a totally unsupervised way detects important regions and ignores unimportant content such as menus and advertisements. We show the interest of our method on different Websites
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Law, Marc Teva. "Distance metric learning for image and webpage comparison." Electronic Thesis or Diss., Paris 6, 2015. http://www.theses.fr/2015PA066019.

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Cette thèse se focalise sur l'apprentissage de distance pour la comparaison d'images ou de pages Web. Les distances (ou métriques) sont exploitées dans divers contextes de l'apprentissage automatique et de la vision artificielle tels que la recherche des k plus proches voisins, le partitionnement, les machines à vecteurs de support, la recherche d'information/images, la visualisation etc. Nous nous intéressons dans cette thèse à l'apprentissage de fonction de distance paramétrée par une matrice symétrique semi-définie positive. Ce modèle, appelé (par abus) apprentissage de distance de Mahalanobis, consiste à apprendre une transformation linéaire des données telle que la distance euclidienne dans l'espace projeté appris satisfasse les contraintes d'apprentissage.Premièrement, nous proposons une méthode basée sur la comparaison de distances relatives qui prend en compte des relations riches entre les données, et exploite des similarités entre quadruplets d'exemples. Nous appliquons cette méthode aux attributs relatifs et à la classification hiérarchique d'images.Deuxièmement, nous proposons une nouvelle méthode de régularisation qui permet de contrôler le rang de la matrice apprise, limitant ainsi le nombre de paramètres indépendants appris et le sur-apprentissage. Nous montrons l'intérêt de notre méthode sur des bases synthétiques et réelles d'identification de visage.Enfin, nous proposons une nouvelle méthode de détection automatique de changement dans les pages Web, dans un contexte d'archivage. Pour cela, nous utilisons les relations de distance temporelle entre différentes versions d'une même page Web. La métrique apprise de façon entièrement non supervisée détecte les régions d'intérêt de la page et ignore le contenu non informatif tel que les menus et publicités. Nous montrons l'intérêt de la méthode sur différents sites Web<br>This thesis focuses on distance metric learning for image and webpage comparison. Distance metrics are used in many machine learning and computer vision contexts such as k-nearest neighbors classification, clustering, support vector machine, information/image retrieval, visualization etc. In this thesis, we focus on Mahalanobis-like distance metric learning where the learned model is parametered by a symmetric positive semidefinite matrix. It learns a linear tranformation such that the Euclidean distance in the induced projected space satisfies learning constraints.First, we propose a method based on comparison between relative distances that takes rich relations between data into account, and exploits similarities between quadruplets of examples. We apply this method on relative attributes and hierarchical image classification. Second, we propose a new regularization method that controls the rank of the learned matrix, limiting the number of independent parameters and overfitting. We show the interest of our method on synthetic and real-world recognition datasets. Eventually, we propose a novel Webpage change detection framework in a context of archiving. For this purpose, we use temporal distance relations between different versions of a same Webpage. The metric learned in a totally unsupervised way detects important regions and ignores unimportant content such as menus and advertisements. We show the interest of our method on different Websites
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Lund, Karen L. "Utilizing a comprehensive webpage to improve science classroom performance." Montana State University, 2011. http://etd.lib.montana.edu/etd/2011/lund/LundK0811.pdf.

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The purpose of this study was to improve student classroom performance through the use of a detailed chemistry webpage. Students utilized a monthly assignment calendar with links to all classroom materials. Links to additional chemistry resources for review and reinforcement were also available to assist both present as well as absent students in their learning. Results indicate that the treatment increased assessment scores and improved student learning behaviors.
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Keppel, David P. "Adverse advertising : the impact advertisements have on webpage content retention /." Online version of thesis, 2009. http://hdl.handle.net/1850/10850.

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RYDMARK, MIKAEL. "Faster Loading of Websites : Strategies for optimizing loading of webpage components." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-156250.

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When loading a webpage on the Internet it is desirable that it loads as quickly as possible. This master thesis presents several strategies to try and improve the response time of a webpage by optimizing the loading of its component. The tests conducted in this master thesis showedthat using compression will significantly improve the response time of a webpage and using caching for static components will greatly improve the response time for repeated visits of a webpage.<br>När en webbsida laddas på Internet är det önskvärt att det går så fortsom möjligt att ladda sidan. Den här rapporten redovisar flera strategierför att försöka förbättra laddningstiden för en webbsida genom att optimeraladdningen av en webbsidas komponenter. Testen som genomförtsoch redovisas i rapporten visade att man kan minska laddningstidenför en webbsida signifikant genom att tillämpa komprimering. Testenvisade också att man genom att cacha statiska komponenter kan sparamycket tid för återkommande besök av webbsidan.
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Fang, Yu-Lin. "Taiwanese-American computer professionals as facilitators of their children's webpage creation /." The Ohio State University, 2000. http://rave.ohiolink.edu/etdc/view?acc_num=osu1488193665235094.

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Books on the topic "Webpage"

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1970-, Wang Jianmin, ed. Wang ye mei shu she ji: Webpage Design. He bei mei shu chu ban she, 2001.

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Fan, Kuan Liang. developing an interactive webpage with ASP or CGI & Organiser (online organiser). Oxford Brookes University, 2001.

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Bouzid, Mohamed. Webpack for Beginners. Apress, 2020. http://dx.doi.org/10.1007/978-1-4842-5896-5.

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Zotov, Valerij Ûr'evič. Proektirovanie cifrovyh ustrojstv na osnove plis firmy XILINX v SAPR WebPACK ISE. Gorâčaâ liniâ - Telekom, 2003.

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Gifford, Clive. WebPage Design. Hachette Children's Group, 2017.

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BDG. Mastering WebPage 2nd Edition. BDG Publishing Inc., 1998.

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Graduate School FCU: Official webpage. Kriistopher, 2011.

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Bug, De. Static Webpage on S3 II. Independently Published, 2020.

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WebPage Fundamentals with FrontPage '98. Prentice Hall, 1998.

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Inc. Staff Wiley and Sons. Webpage Design for CSC 125. Wiley & Sons, Incorporated, John, 2001.

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Book chapters on the topic "Webpage"

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Rennie, Frank, and Keith Smyth. "Webpage." In Digital Learning: The Key Concepts, 2nd ed. Routledge, 2019. http://dx.doi.org/10.4324/9780429425240-222.

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Shen, Chengyao, and Qi Zhao. "Webpage Saliency." In Computer Vision – ECCV 2014. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-10584-0_3.

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Fan, Xiangyu, Jilong Yang, Wei Zhao, Jincheng Deng, and Fangming Liu. "Webpage Tampering Detection Method Based on BiGRU-CRF-RCNN." In Communications in Computer and Information Science. Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-8285-9_8.

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AbstractWith the development of the Internet, cyber security events occur frequently, especially webpage tampering events account for a high proportion. In response to this phenomenon, this paper constructs a webpage tampering detection framework BCR. Based on the webpage to be detected, the webpage text data is segmented and extracted according to the webpage structure, the text features are extracted by using BiGRU model combined with context dependence, and then combined with the CRF to learn sequence state labeling named entities, the word vector is constructed by the extracted named entity and brought into the RCNN model for tampering detection. The experiment results show that the framework has achieved 95.37% precision, 95.35% recall and 95.34% F1-Score in webpage tampering detection, which is better than Textrank RCNN framework in webpage tampering detection. In practical application, it also achieved 95.13% precision and 93.25% recall.
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Elbers, Willem, and Theo van der Weide. "Optimizing WebPage Interest." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-04417-5_33.

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Skula, Ivan, and Marek Kvet. "Phishing Webpage Longevity." In Lecture Notes in Networks and Systems. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-60328-0_21.

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Krishna, Kushagra, Jaytrilok Choudhary, and Dhirendra Pratap Singh. "Malicious Webpage Classification." In Advances in Intelligent Systems and Computing. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-76736-5_36.

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Plaut, Ethan. "Vandalize a Webpage." In The Routledge Handbook of Remix Studies and Digital Humanities. Routledge, 2021. http://dx.doi.org/10.4324/9780429355875-23.

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Klein, David C., and Steven L. Coon. "The Pineal Transcriptome Webpage." In Melatonin. Springer US, 2022. http://dx.doi.org/10.1007/978-1-0716-2593-4_17.

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Zheng, Quanlong, Jianbo Jiao, Ying Cao, and Rynson W. H. Lau. "Task-Driven Webpage Saliency." In Computer Vision – ECCV 2018. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-01264-9_18.

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Deng, Qiong, Huajun Huang, Liangmin Pan, Shuang Pang, and Jiaohua Qin. "A Phishing Webpage Detecting Algorithm Using Webpage Noise and N-Gram." In Cloud Computing and Security. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-48671-0_15.

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Conference papers on the topic "Webpage"

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Yagi, Kota, Katsuki Isobe, Daishi Kondo, and Hideki Tode. "Impact of DANE on Webpage Load Time." In 2024 20th International Conference on Network and Service Management (CNSM). IEEE, 2024. https://doi.org/10.23919/cnsm62983.2024.10814301.

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Miniukovich, Aliaksei, and Antonella De Angeli. "Webpage Aesthetics." In NordiCHI '16: 9th Nordic Conference on Human-Computer Interaction. ACM, 2016. http://dx.doi.org/10.1145/2971485.2971544.

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Zhu, Jun, Bo Zhang, Zaiqing Nie, Ji-Rong Wen, and Hsiao-Wuen Hon. "Webpage understanding." In the 13th ACM SIGKDD international conference. ACM Press, 2007. http://dx.doi.org/10.1145/1281192.1281288.

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Dong-Liang Lee, Sheng-Yuan Yang, and Chun-Liang Hsu. "Ontology-Supported Webpage Classifier for Scholar’s Webpages in Ubiquitous Information Environment." In 2008 First IEEE International Conference on Ubi-media Computing (U-Media 2008). IEEE, 2008. http://dx.doi.org/10.1109/umedia.2008.4570947.

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Thirumaran, M., R. P. Karthikeyan, and V. Rathaamani. "Phishing Website Detection Using Natural Language Processing and Deep Learning Algorithm." In International Research Conference on IOT, Cloud and Data Science. Trans Tech Publications Ltd, 2023. http://dx.doi.org/10.4028/p-4oja18.

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Due to rapid growth of the internet most of the people started using internet through mobile and web apps to satisfy their needs. Such as online shopping and banking. Under OWSAP top 10 vulnerabilities, sensitive data exposure is one of the common threats that is identified in recent years and phishing is found to be a key source. Sensitive data exposure is majorly occurring in the internet using various phishing techniques and phishing is found to be a key sources of data stealing. Attackers, not only targeted the financial sectors and e-commerce industries, also in the field of defense and security . To detect the phishing attacks in webpages, many software was used. Some of the method of detection the phishing is, by using the URL of the webpage and by using contents of the webpage. Still, there is no robust and accurate software solution to detect the phishing attacks. The purpose of the research is to use both URL and contents of the webpage to identify the phishing. The proposed work is to build an automated and hybrid model using Random Forest (RF) algorithm in Machine learning with the Convolutional Neural network algorithm (CNN) in Deep Learning is applied to detect and classify the phishing in URL and web page contents in an automated manner .
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Tate, Ryan, Gregory Conti, and Edward Sobiesk. "Automated webpage evaluation." In the 2nd annual conference. ACM Press, 2013. http://dx.doi.org/10.1145/2512209.2512220.

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Dai, Yimeng, Rui Zhang, and Jianzhong Qi. "Automatic Webpage Briefing." In 2021 IEEE 37th International Conference on Data Engineering (ICDE). IEEE, 2021. http://dx.doi.org/10.1109/icde51399.2021.00152.

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Liu, Lijuan. "Research on Webpage Text Extraction Integrating Webpage Structure and Role." In ACAI 2022: 2022 5th International Conference on Algorithms, Computing and Artificial Intelligence. ACM, 2022. http://dx.doi.org/10.1145/3579654.3579761.

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Wang, Chong, Achir Kalra, Cristian Borcea, and Yi Chen. "Revenue-Optimized Webpage Recommendation." In 2015 IEEE International Conference on Data Mining Workshop (ICDMW). IEEE, 2015. http://dx.doi.org/10.1109/icdmw.2015.215.

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Van Acker, Steven, Daniel Hausknecht, and Andrei Sabelfeld. "Measuring login webpage security." In SAC 2017: Symposium on Applied Computing. ACM, 2017. http://dx.doi.org/10.1145/3019612.3019798.

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Reports on the topic "Webpage"

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Lee, Hye Young. LASNCE webpage document. Office of Scientific and Technical Information (OSTI), 2019. http://dx.doi.org/10.2172/1544652.

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Mu, Ruihui, and Xiaoqin Zeng. Improved Webpage Classification Technology Based on Feedforward Backpropagation Neural Network. "Prof. Marin Drinov" Publishing House of Bulgarian Academy of Sciences, 2018. http://dx.doi.org/10.7546/crabs.2018.09.11.

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LaForce, Tara, Jens Bartol, Dirk-Alexander Becker, et al. DECOVALEX-2023 Task F2-Salt Final Report for DECOVALEX webpage. Office of Scientific and Technical Information (OSTI), 2024. http://dx.doi.org/10.2172/2430083.

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Maddux, Gary A. MRDEC Webpage Operation and Maintenance Services for the Purpose of Data Distribution of Missile Technology and Analyses. Defense Technical Information Center, 1999. http://dx.doi.org/10.21236/ada368505.

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Junghans, A., S. S. Westerdale, and P. Dimitriou. (alpha,n) Nuclear Data Evaluations and Data Needs. IAEA Nuclear Data Section, 2024. http://dx.doi.org/10.61092/iaea.d2d0-encd.

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The second IAEA Technical Meeting addressing (α,n) data needs for applications spanning reactor operation and safeguards, nonproliferation and spent fuel management, low-background experiments, and nuclear astrophysics was organized by the IAEA from 27 November to 1 December 2023. Fifty-six participants from thirteen Member States attended the virtual event. Participants reviewed the progress in (α,n) measurements, models, codes and evaluated libraries since the previous meeting of 2021. A summary of the presentations, technical discussions and recommendations is given in this report. The presentations are available from the meeting webpage: https://conferences.iaea.org/event/366/.
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Westerdale, S. S., A. Junghans, R. J. deBoer, M. Pigni, and P. Dimitriou. Summary Report of the Technical Meeting on (alpha,n) Nuclear Data Evaluations and Data Needs. IAEA Nuclear Data Section, 2022. http://dx.doi.org/10.61092/iaea.vdj4-pakp.

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A Technical Meeting addressing (α,n) data needs for applications spanning reactor operation and safeguards, nonproliferation and spent fuel management, low-background experiments, and nuclear astrophysics was organised by the IAEA from 8 to 12 November 2021. Over 60 participants from fifteen Member States attended the virtual event. Participants reviewed the status of (α,n) measurements, models, codes and evaluated libraries with a view to identifying the gaps in the above areas and proposing the necessary actions to address them and produce reliable (α,n) data for the applications. A summary of the presentations, technical discussions and recommendations is given in this report. The presentations are available from the meeting webpage: https://conferences.iaea.org/event/283/.
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Kaffenberger, Michelle, and Jason Silberstein. Descriptive Learning Trajectories and Policy Simulations Using MICS6 Data. Research on Improving Systems of Education (RISE), 2022. http://dx.doi.org/10.35489/bsgrise-misc_2022/05.

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In recent years, scholars associated with the RISE Programme have analysed learning trajectories using a variety of global datasets to shed light on the global learning crisis and diagnose what might help address it (Crouch, Kaffenberger, and Savage, 2021). For those who may want to build and analyse learning trajectories, this note acts as a methodological guide for doing so using an important new dataset on foundational learning, the Multiple Indicator Cluster Surveys Round 6 (MICS6). We have applied the methods described in this note and, in partnership with the Global Education Monitoring Report (GEMR), developed a tool to showcase the results. The resulting “Learning Trajectories” webpage serves as an interactive introduction to learning trajectories and related policy simulations, and features a flexible data explorer for those who want to conveniently build, analyse, and apply learning trajectories and policy simulations to their own work and context.
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Kaffenberger, Michelle, and Jason Silberstein. Descriptive Learning Trajectories and Policy Simulations Using MICS6 Data. Research on Improving Systems of Education (RISE), 2022. http://dx.doi.org/10.35489/bsg-rise-misc_2022/05.

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In recent years, scholars associated with the RISE Programme have analysed learning trajectories using a variety of global datasets to shed light on the global learning crisis and diagnose what might help address it (Crouch, Kaffenberger, and Savage, 2021). For those who may want to build and analyse learning trajectories, this note acts as a methodological guide for doing so using an important new dataset on foundational learning, the Multiple Indicator Cluster Surveys Round 6 (MICS6). We have applied the methods described in this note and, in partnership with the Global Education Monitoring Report (GEMR), developed a tool to showcase the results. The resulting “Learning Trajectories” webpage serves as an interactive introduction to learning trajectories and related policy simulations, and features a flexible data explorer for those who want to conveniently build, analyse, and apply learning trajectories and policy simulations to their own work and context.
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Harbitz, Mia Elisabeth. The Civil Registry: A Neglected Dimension of International Development. Inter-American Development Bank, 2013. http://dx.doi.org/10.18235/0009117.

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The right to a name and nationality is not only one of the most fundamental human rights but also a requirement to access to basic and essential services such as health and education. This right is exercised through an effective and universal civil registration. It also allows for reliable vital statistics and higher levels of transparency and efficacy that provides the foundation for inclusive public policies, especially social programs. Thus civil registry, legal identity and identity management (Id-M) are central elements for social and economic development. On the international stage, the creation and dissemination of knowledge around the civil registration and legal identity field has evolved from a single paper produced by UNICEF in 2000, to several knowledge sharing initiatives where the IDB has played a pivotal role. The launching of a webpage (http://iadb.libguides.com/registros) in 2011 that provides access to all IDB publications and projects on the topic is just one example of it. Birth under-registration rates has dropped from 18 percent to 9 percent in Latin America and the Caribbean (LAC) since the IDB, through its legal identity and registry team took on the topic in 2002 . Though the Bank cannot claim the exclusive credit for this achievement, the fact that a development bank took on the issue is of major consequence.
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Gregory, Elizabeth. Field Epidemiology Training Program (FETP) — Frontline 3.0: Using a One Health Approach. National Center for Health Statistics (U.S.), 2025. https://doi.org/10.15620/cdc/175829.

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"From the letter by Dr. Benjamin Park: “On behalf of the U.S. Centers for Disease Control and Prevention (CDC), it is our privilege to present the third version of the Field Epidemiology Training Program (FETP)—Frontline 3.0. This document reflects our shared commitment to strengthening public health systems worldwide by building the capacity of frontline health workers to rapidly detect, respond to, and contain health threats, now with an increased emphasis on a One Health approach. One Health is a collaborative, multisectoral, and transdisciplinary approach—working at the local, regional, national, and global levels—with the goal of achieving optimal health outcomes recognizing the interconnection between people, animals, plants, and their shared environment…. “FETP–Frontline 3.0 emphasizes real-world, hands-on training, equipping participants with practical skills to conduct surveillance, analyze data, and implement timely interventions. We recognize that each country brings unique strengths and faces distinct challenges. The guidelines provided here aim to support the seamless integration of FETP–Frontline 3.0 into your existing public health frameworks, tailoring it to your specific needs and priorities while fostering cross-sectoral collaboration inherent to the One Health approach. We encourage you to use this resource as a roadmap, adapting it to optimize outcomes for building safer communities….” All of the FETP 3.0 materials are contained in a single Zip folder named “FETP_Frontline_3_One_Health_Approach_20250123.zip”, found under the “Supporting Files” header, near the bottom of this webpage. The zip folder contains the following folders and materials: Welcome to FETP 3.0 Letter from Dr. Benjamin Park; FETP-Frontline 3.0 Implementation and Curriculum Guide; Field Intervals Guide for Mentors; folder a. Assessments; folder b. Workshop 1; folder c. Field Interval 1; folder d. Workshop 2; folder e. Field Interval 2; and folder f. Workshop 3. These folders contain various curriculum slide decks and documents."
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