Academic literature on the topic 'Web page'
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Journal articles on the topic "Web page"
1
Lei, Shi. "Modeling an web community discovery method with web page attraction." Journal of Intelligent & Fuzzy Systems 40, no. 6 (2021): 11159–69. http://dx.doi.org/10.3233/jifs-202366.
Full textAbstract:
An improved Web community discovery algorithm is proposed in this paper based on the attraction between Web pages to effectively reduce the complexity of Web community discovery. The proposed algorithm treats each Web page in the Web pages collection as an individual with attraction based on the theory of universal gravitation, elaborates the discovery and evolution process of Web community from a Web page in the Web pages collection, defines the priority rules of Web community size and Web page similarity, and gives the calculation formula of the change in Web page similarity. Finally, an experimental platform is built to analyze the specific discovery process of the Web community in detail, and the changes in cumulative distribution of Web page similarity are discussed. The results show that the change in the similarity of a new page satisfies the power-law distribution, and the similarity of a new page is proportional to the size of Web community that the new page chooses to join.
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Apandi, Siti Hawa, Jamaludin Sallim, Rozlina Mohamed, and Norkhairi Ahmad. "Automatic Topic-Based Web Page Classification Using Deep Learning." JOIV : International Journal on Informatics Visualization 7, no. 3-2 (2023): 2108. http://dx.doi.org/10.30630/joiv.7.3-2.1616.
Full textAbstract:
The internet is frequently surfed by people by using smartphones, laptops, or computers in order to search information online in the web. The increase of information in the web has made the web pages grow day by day. The automatic topic-based web page classification is used to manage the excessive amount of web pages by classifying them to different categories based on the web page content. Different machine learning algorithms have been employed as web page classifiers to categorise the web pages. However, there is lack of study that review classification of web pages using deep learning. In this study, the automatic topic-based classification of web pages utilising deep learning that has been proposed by many key researchers are reviewed. The relevant research papers are selected from reputable research databases. The review process looked at the dataset, features, algorithm, pre-processing used in classification of web pages, document representation technique and performance of the web page classification model. The document representation technique used to represent the web page features is an important aspect in the classification of web pages as it affects the performance of the web page classification model. The integral web page feature is the textual content. Based on the review, it was found that the image based web page classification showed higher performance compared to the text based web page classification. Due to lack of matrix representation that can effectively handle long web page text content, a new document representation technique which is word cloud image can be used to visualize the words that have been extracted from the text content web page.
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Y., Klushyn, and Zakharchin Y. "INCREASE THE SPEED OF WEB APPLICATIONS." Computer systems and network 2, no. 1 (2017): 33–43. http://dx.doi.org/10.23939/csn2020.01.033.
Full textAbstract:
The article presents a method of creating a web application based on SPA technology (one-page web application), as a method of increasing the speed of web applications based on the use of modern frameworks, tools and tools for developing client and server part of a one-page web application. One-page web applications are web application technologies that consist of a single web page that interacts with the user, dynamically generating the current page rather than downloading entire new pages from the server. Based on this technique, we developed our own web application and based on it we determined the response rate, which is less than the optimal response rate for single-page web applications. An explanation is given as to which solutions increase response speed and performance in a one-page web application, and why creating a multi-page site is not the best idea. Keywords: single-page web application, database, multi-page web application, non-relational database, relational database, Backend technologies, server, JavaScript
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Chen, Yuanchao, Yuliang Lu, Zulie Pan, et al. "APIMiner: Identifying Web Application APIs Based on Web Page States Similarity Analysis." Electronics 13, no. 6 (2024): 1112. http://dx.doi.org/10.3390/electronics13061112.
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Modern web applications offer various APIs for data interaction. However, as the number of these APIs increases, so does the potential for security threats. Essentially, more APIs in an application can lead to more detectable vulnerabilities. Thus, it is crucial to identify APIs as comprehensively as possible in web applications. However, this task faces challenges due to the increasing complexity of web development techniques and the abundance of similar web pages. In this paper, we propose APIMiner, a framework for identifying APIs in web applications by dynamically traversing web pages based on web page state similarity analysis. APIMiner first builds a web page model based on the HTML elements of the current web page. APIMiner then uses this model to represent the state of the page. Then, APIMiner evaluates each element’s similarity in the page model and determines the page state similarity based on these similarity values. From the different states of the page, APIMiner extracts the data interaction APIs on the page. We conduct extensive experiments to evaluate APIMiner’s effectiveness. In the similarity analysis, our method surpasses state-of-the-art methods like NDD and mNDD in accurately distinguishing similar pages. We compare APIMiner with state-of-the-art tools (e.g., Enemy of the State, Crawlergo, and Wapiti3) for API identification. APIMiner excels in the number of identified APIs (average 1136) and code coverage (average 28,470). Relative to these tools, on average, APIMiner identifies 7.96 times more APIs and increases code coverage by 142.72%.
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Apandi, Siti Hawa, Jamaludin Sallim, and Rozlina Mohamed. "A Convolutional Neural Network (CNN) Classification Model for Web Page: A Tool for Improving Web Page Category Detection Accuracy." JITSI : Jurnal Ilmiah Teknologi Sistem Informasi 4, no. 3 (2023): 110–21. http://dx.doi.org/10.30630/jitsi.4.3.181.
Full textAbstract:
Game and Online Video Streaming are the most viewed web pages. Users who spend too much time on these types of web pages may suffer from internet addiction. Access to Game and Online Video Streaming web pages should be restricted to combat internet addiction. A tool is required to recognise the category of web pages based on the text content of the web pages. Due to the unavailability of a matrix representation that can handle long web page text content, this study employs a document representation known as word cloud image to visualise the words extracted from the text content web page after data pre-processing. The most popular words are shown in large size and appear in the centre of the word cloud image. The most common words are the words that appear frequently in the text content web page and are related to describing what the web page content is about. The Convolutional Neural Network (CNN) recognises the pattern of words presented in the core portions of the word cloud image to categorise the category to which the web page belongs. The proposed model for web page classification has been compared with the other web page classification models. It shows the good result that achieved an accuracy of 85.6%. It can be used as a tool that helps to make identifying the category of web pages more accurate
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Apandi, Siti Hawa, Jamaludin Sallim, and Rozlina Mohamed. "A Convolutional Neural Network (CNN) Classification Model for Web Page: A Tool for Improving Web Page Category Detection Accuracy." JITSI : Jurnal Ilmiah Teknologi Sistem Informasi 4, no. 3 (2023): 110–21. https://doi.org/10.62527/jitsi.4.3.181.
Full textAbstract:
Game and Online Video Streaming are the most viewed web pages. Users who spend too much time on these types of web pages may suffer from internet addiction. Access to Game and Online Video Streaming web pages should be restricted to combat internet addiction. A tool is required to recognise the category of web pages based on the text content of the web pages. Due to the unavailability of a matrix representation that can handle long web page text content, this study employs a document representation known as word cloud image to visualise the words extracted from the text content web page after data pre-processing. The most popular words are shown in large size and appear in the centre of the word cloud image. The most common words are the words that appear frequently in the text content web page and are related to describing what the web page content is about. The Convolutional Neural Network (CNN) recognises the pattern of words presented in the core portions of the word cloud image to categorise the category to which the web page belongs. The proposed model for web page classification has been compared with the other web page classification models. It shows the good result that achieved an accuracy of 85.6%. It can be used as a tool that helps to make identifying the category of web pages more accurate
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Nandanwar, Amit Kumar, and Jaytrilok Choudhary. "Semantic Features with Contextual Knowledge-Based Web Page Categorization Using the GloVe Model and Stacked BiLSTM." Symmetry 13, no. 10 (2021): 1772. http://dx.doi.org/10.3390/sym13101772.
Full textAbstract:
Internet technologies are emerging very fast nowadays, due to which web pages are generated exponentially. Web page categorization is required for searching and exploring relevant web pages based on users’ queries and is a tedious task. The majority of web page categorization techniques ignore semantic features and the contextual knowledge of the web page. This paper proposes a web page categorization method that categorizes web pages based on semantic features and contextual knowledge. Initially, the GloVe model is applied to capture the semantic features of the web pages. Thereafter, a Stacked Bidirectional long short-term memory (BiLSTM) with symmetric structure is applied to extract the contextual and latent symmetry information from the semantic features for web page categorization. The performance of the proposed model has been evaluated on the publicly available WebKB dataset. The proposed model shows superiority over the existing state-of-the-art machine learning and deep learning methods.
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Limna, Das P., and Sanjeetha.R. "IMPROVING WEB INFORMATION QUALITY BY AGE DETECTION & SECURITY ANALYSIS OF WEB PAGES." International Journal of Advances in Engineering & Scientific Research 1, no. 4 (2014): 28–34. https://doi.org/10.5281/zenodo.10720350.
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<strong><em>Abstract</em></strong><strong> </strong> <em> The Web is evolving very rapidly due to the ease of publishing information. At the same time, the Web is vulnerable to time passage as much new content is created continuously and old content becomes quickly obsolete. It is thus important to distinguish fresh and obsolete content in Web pages. Many web pages contain elements inserted at different time points. Some pages show timestamps or other temporal metadata informing about the creation dates of content elements. The main function of temporal metadata is to inform users about the age of page content. Readers often implicitly utilize this information to better understand the content by correctly locating it on a time scale. It is especially evident in the case of time-sensitive documents. In practice, however, pages often do not offer any clues about the age of their content. The reader has to optimistically think the web page is latest and proceed. In other cases, temporal annotations provided by page authors may sometimes be misleading and should not always be trusted. The web pages that are visited may not be secure as they may contain malicious contents like viruses, worms, spyware, key loggers etc. There has to be some means to find out the security of the web page before using it. In our project, we describe a novel concept for detecting approximate creation dates of content elements in Web pages and measure the security level of the web page visited. To detect the age of a web page we dynamically reconstruct page histories using data extracted from external sources such as Web archives and efficiently search inside them to detect insertion dates of content elements. To measure the security of the web page we check certain security attributes like Security risks, Remote access software, Adware, Spyware, Dialers, Malicious downloads, Drive by downloads, Suspicious browser changes, Phishing attacks, Information stealers, Trojans and Suspicious applications with the help of Security websites that are designed to help users discern safe Web sites from unsafe ones.</em> <strong><em>Keywords</em></strong>—Web Information Quality, trustworthiness of Information on the Web, quality factors, web Archives, Information age, Information Security.
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Li, Xin Li. "Web Page Ranking Algorithm Based on the Meta-Information." Applied Mechanics and Materials 596 (July 2014): 292–96. http://dx.doi.org/10.4028/www.scientific.net/amm.596.292.
Full textAbstract:
PageRank algorithms only consider hyperlink information, without other page information such as page hits frequency, page update time and web page category. Therefore, the algorithms rank a lot of advertising pages and old pages pretty high and can’t meet the users' needs. This paper further studies the page meta-information such as category, page hits frequency and page update time. The Web page with high hits frequency and with smaller age should get a high rank, while the above two factors are more or less dependent on page category. Experimental results show that the algorithm has good results.
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Zhao, Wenjuan, and Zhongbao Liu. "Research on Web Page Classification Method based on Newton’s Law of Universal Gravitation and HITS Algorithm." Advances in Engineering Technology Research 13, no. 1 (2025): 856. https://doi.org/10.56028/aetr.13.1.856.2025.
Full textAbstract:
Web page classification is one of the most important methods in web mining. In recent years, numerous classifiers are proposed and used for web page classification. Though these classifiers perform well in practice, they don't pay enough attention to the link connections between web pages, and therefore, their classification efficiencies can’t be greatly improved. We propose a web page classification method based on Newton’s Law of Universal Gravitation and HITS (Hypertext-Induced Topic Search) algorithm (WPCM), based on which, we constructs the web page classification system. In this system, web pages are firstly collected and pro-processed; Web pages are represented as the document-term frequency matrix and Modified Discriminant Analysis based on Fisher Criterion and Manifold Learning (MDA) is used to feature extraction; Web pages are classified by WPCM; At last, the performance of WPCM is evaluated by the criterions of Accuracy and F-measure. We use PKU collection, containing 13897 web pages and 11 categories, in our experiments. The comparative experiments with the traditional classifiers, such as SVM and KNN, demonstrate that the proposed system based on the classifier WPCM performs better than SVM and KNN.Inspired by Newton’s Law of Universal Gravitation, we proposed a new web page classification method WPCM, in which the research object is transformed from the object in the universe to the web page and the importance representation is transformed from the mass of the object to the weight of the web page. The above research route can broaden related research horizon and may cause the researcher's interest.
Dissertations / Theses on the topic "Web page"
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Krupp, Brian. "Exploration of Dynamic Web Page Partitioning for Increased Web Page Delivery Performance." Cleveland State University / OhioLINK, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=csu1290629377.
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Chiew, Thiam Kian. "Web page performance analysis." Thesis, University of Glasgow, 2009. http://theses.gla.ac.uk/658/.
Full textAbstract:
Computer systems play an increasingly crucial and ubiquitous role in human endeavour by carrying out or facilitating tasks and providing information and services. How much work these systems can accomplish, within a certain amount of time, using a certain amount of resources, characterises the systems’ performance, which is a major concern when the systems are planned, designed, implemented, deployed, and evolve. As one of the most popular computer systems, the Web is inevitably scrutinised in terms of performance analysis that deals with its speed, capacity, resource utilisation, and availability. Performance analyses for the Web are normally done from the perspective of the Web servers and the underlying network (the Internet). This research, on the other hand, approaches Web performance analysis from the perspective of Web pages. The performance metric of interest here is response time. Response time is studied as an attribute of Web pages, instead of being considered purely a result of network and server conditions. A framework that consists of measurement, modelling, and monitoring (3Ms) of Web pages that revolves around response time is adopted to support the performance analysis activity. The measurement module enables Web page response time to be measured and is used to support the modelling module, which in turn provides references for the monitoring module. The monitoring module estimates response time. The three modules are used in the software development lifecycle to ensure that developed Web pages deliver at worst satisfactory response time (within a maximum acceptable time), or preferably much better response time, thereby maximising the efficiency of the pages. The framework proposes a systematic way to understand response time as it is related to specific characteristics of Web pages and explains how individual Web page response time can be examined and improved.
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Sanoja, Vargas Andrés. "Segmentation de pages web, évaluation et applications." Thesis, Paris 6, 2015. http://www.theses.fr/2015PA066004/document.
Full textAbstract:
Les pages web sont devenues plus complexes que jamais, principalement parce qu'elles sont générées par des systèmes de gestion de contenu (CMS). Il est donc difficile de les analyser, c'est-à-dire d'identifier et classifier automatiquement les différents éléments qui les composent. La segmentation de pages web est une des solutions à ce problème. Elle consiste à décomposer une page web en segments, visuellement et sémantiquement cohérents, appelés blocs. La qualité d'une segmentation est mesurée par sa correction et sa généricité, c'est-à-dire sa capacité à traiter des pages web de différents types. Notre recherche se concentre sur l'amélioration de la segmentation et sur une mesure fiable et équitable de la qualité des segmenteurs. Nous proposons un modèle pour la segmentation ainsi que notre segmenteur Block-o-Matic (BoM). Nous définissons un modèle d'évaluation qui prend en compte le contenu ainsi que la géométrie des blocs pour mesurer la correction d'un segmenteur par rapport à une vérité de terrain. Ce modèle est générique, il permet de tester tout algorithme de segmentation et observer ses performances sur différents types de page. Nous l'avons testé sur quatre segmenteurs et quatre types de pages. Les résultats montrent que BOM surpasse ses concurrents en général et que la performance relative d'un segmenteur dépend du type de page. Enfin, nous présentons deux applications développées au dessus de BOM. Pagelyzer compare deux versions de pages web et décide si elles sont similaires ou pas. C'est la principale contribution de notre équipe au projet européen Scape (FP7-IP). Nous avons aussi développé un outil de migration de pages HTML4 vers le nouveau format HTML5<br>Web pages are becoming more complex than ever, as they are generated by Content Management Systems (CMS). Thus, analyzing them, i.e. automatically identifying and classifying different elements from Web pages, such as main content, menus, among others, becomes difficult. A solution to this issue is provided by Web page segmentation which refers to the process of dividing a Web page into visually and semantically coherent segments called blocks.The quality of a Web page segmenter is measured by its correctness and its genericity, i.e. the variety of Web page types it is able to segment. Our research focuses on enhancing this quality and measuring it in a fair and accurate way. We first propose a conceptual model for segmentation, as well as Block-o-Matic (BoM), our Web page segmenter. We propose an evaluation model that takes the content as well as the geometry of blocks into account in order to measure the correctness of a segmentation algorithm according to a predefined ground truth. The quality of four state of the art algorithms is experimentally tested on four types of pages. Our evaluation framework allows testing any segmenter, i.e. measuring their quality. The results show that BoM presents the best performance among the four segmentation algorithms tested, and also that the performance of segmenters depends on the type of page to segment.We present two applications of BoM. Pagelyzer uses BoM for comparing two Web pages versions and decides if they are similar or not. It is the main contribution of our team to the European project Scape (FP7-IP). We also developed a migration tool of Web pages from HTML4 format to HTML5 format in the context of Web archives
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SOUZA, CRISTON PEREIRA DE. "EFFICIENT WEB PAGE REFRESH POLICIES." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2010. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=15893@1.
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CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO<br>Uma máquina de busca precisa constantemente revisitar páginas Web
para manter seu repositório local atualizado. Uma política de revisitação
deve ser empregada para construir um escalonamento de revisitações que
mantenha o repositório o mais atualizado possível utilizando os recursos
disponíveis. Para evitar sobrecarga de servidores Web, a política de
revisitação deve respeitar um tempo mínimo entre requisições consecutivas
a um mesmo servidor. Esta regra é chamada restrição de politeness. Devido
ao porte do problema, consideramos que uma política de revisitação é
eficiente se o tempo médio para escalonar uma revisitação é sublinear no
número de páginas do repositório. Neste sentido, quando a restrição de
politeness é considerada, não conhecemos política eficiente com garantia
teórica de qualidade. Nesta pesquisa investigamos três políticas eficientes
que respeitam a restrição de politeness, chamadas MERGE, RANDOM e
DELAYED. Fornecemos fatores de aproximação para o nível de atualização
do repositório quando empregamos as política MERGE ou RANDOM.
Demonstramos que 0,77 é um limite inferior para este fator de aproximação
quando empregamos a política RANDOM, e apresentamos uma conjectura
de que 0,927 é um limite inferior para este fator de aproximação quando
empregamos a política MERGE. As políticas também são avaliadas através
da simulação da execução destas políticas para manter o nível de atualização
de um repositório contendo 14,5 milhões de páginas Web. Um repositório
contendo artigos da Wikipedia também é utilizado nos experimentos, onde
podemos observar que a política MERGE apresenta melhores resultados que
uma estratégia gulosa natural para este repositório. A principal conclusão
desta pesquisa é que existem políticas simples e eficientes para o problema
de revisitação de páginas Web, que perdem pouco em termos do nível
de atualização do repositório mesmo quando consideramos a restrição de
politeness.<br>A search engine needs to continuously revisit web pages in order to
keep its local repository up-to-date. A page revisiting schedule must be
defined to keep the repository up-to-date using the available resources.
In order to avoid web server overload, the revisiting policy must respect
a minimum amount of time between consecutive requests to the same
server. This rule is called politeness constraint. Due to the large number
of web pages, we consider that a revisiting policy is efficient when the
mean time to schedule a revisit is sublinear on the number of pages in the
repository. Therefore, when the politeness constraint is considered, there
are no existing efficient policies with theoretical quality guarantees. We
investigate three efficient policies that respect the politeness constraint,
called MERGE, RANDOM and DELAYED. We provide approximation
factors for the repository’s up-to-date level for the MERGE and RANDOM
policies. Based on these approximation factors, we devise a 0.77 lower bound
for the approximation factor provided by the RANDOM policy and we
present a conjecture that 0.927 is a lower bound for the approximation
factor provided by the MERGE policy. We evaluate these policies through
simulation experiments which try to keep a repository with 14.5 million
web pages up-to-date. Additional experiments based on a repository with
Wikipedia’s articles concluded that the MERGE policy provides better
results than a natural greedy strategy. The main conclusion of this research
is that there are simple and efficient policies that can be applied to this
problem, even when the politeness constraint must be respected, resulting
in a small loss of repository’s up-to-date level.
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Hou, Jingyu. "Discovering web page communities for web-based data management." University of Southern Queensland, Faculty of Sciences, 2002. http://eprints.usq.edu.au/archive/00001447/.
Full textAbstract:
The World Wide Web is a rich source of information and continues to expand in size and complexity. Mainly because the data on the web is lack of rigid and uniform data models or schemas, how to effectively and efficiently manage web data and retrieve information is becoming a challenge problem. Discovering web page communities, which capture the features of the web and web-based data to find intrinsic relationships among the data, is one of the effective ways to solve this problem. A web page community is a set of web pages that has its own logical and semantic structures. In this work, we concentrate on the web data in web page format and exploit hyperlink information to discover (construct) web page communities. Three main web page communities are studied in this work: the first one is consisted of hub and authority pages, the second one is composed of relevant web pages with respect to a given page (URL), and the last one is the community with hierarchical cluster structures. For analysing hyperlinks, we establish a mathematical framework, especially the matrix-based framework, to model hyperlinks. Within this mathematical framework, hyperlink analysis is placed on a solid mathematic base and the results are reliable. For the web page community that is consisted of hub and authority pages, we focus on eliminating noise pages from the concerned page source to obtain another good quality page source, and in turn improve the quality of web page communities. We propose an innovative noise page elimination algorithm based on the hyperlink matrix model and mathematic operations, especially the singular value decomposition (SVD) of matrix. The proposed algorithm exploits hyperlink information among the web pages, reveals page relationships at a deeper level, and numerically defines thresholds for noise page elimination. The experiment results show the effectiveness and feasibility of the algorithm. This algorithm could also be used solely for web-based data management systems to filter unnecessary web pages and reduce the management cost. In order to construct a web page community that is consisted of relevant pages with respect to a given page (URL), we propose two hyperlink based relevant page finding algorithms. The first algorithm comes from the extended co-citation analysis of web pages. It is intuitive and easy to be implemented. The second one takes advantage of linear algebra theories to reveal deeper relationships among the web pages and identify relevant pages more precisely and effectively. The corresponding page source construction for these two algorithms can prevent the results from being affected by malicious hyperlinks on the web. The experiment results show the feasibility and effectiveness of the algorithms. The research results could be used to enhance web search by caching the relevant pages for certain searched pages. For the purpose of clustering web pages to construct a community with its hierarchical cluster structures, we propose an innovative web page similarity measurement that incorporates hyperlink transitivity and page importance (weight).Based on this similarity measurement, two types of hierarchical web page clustering algorithms are proposed. The first one is the improvement of the conventional K-mean algorithms. It is effective in improving page clustering, but is sensitive to the predefined similarity thresholds for clustering. Another type is the matrix-based hierarchical algorithm. Two algorithms of this type are proposed in this work. One takes cluster-overlapping into consideration, another one does not. The matrix-based algorithms do not require predefined similarity thresholds for clustering, are independent of the order in which the pages are presented, and produce stable clustering results. The matrix-based algorithms exploit intrinsic relationships among web pages within a uniform matrix framework, avoid much influence of human interference in the clustering procedure, and are easy to be implemented for applications. The experiments show the effectiveness of the new similarity measurement and the proposed algorithms in web page clustering improvement. For applying above mathematical algorithms better in practice, we generalize the web page discovering as a special case of information retrieval and present a visualization system prototype, as well as technical details on visualization algorithm design, to support information retrieval based on linear algebra. The visualization algorithms could be smoothly applied to web applications. XML is a new standard for data representation and exchange on the Internet. In order to extend our research to cover this important web data, we propose an object representation model (ORM) for XML data. A set of transformation rules and algorithms are established to transform XML data (DTD and XML documents with DTD or without DTD) into this model. This model capsulizes elements of XML data and data manipulation methods. DTD-Tree is also defined to describe the logical structure of DTD. It also can be used as an application program interface (API) for processing DTD, such as transforming a DTD document into the ORM. With this data model, semantic meanings of the tags (elements) in XML data can be used for further research in XML data management and information retrieval, such as community construction for XML data.
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Myers, Paul Thomas. "The Cucamonga Middle School web page: Using parent input to redesign an existing school web page." CSUSB ScholarWorks, 2001. https://scholarworks.lib.csusb.edu/etd-project/2008.
Full textAbstract:
This project focused on the enhancement of an existing school web page. Schools have jumped on the bandwagon in record numbers in the past couple of years publishing web pages about their schools. Cucamonga Middle School is no exception, having first published a web site in 1995. Utilizing information gathered from a survey, the author/webmaster created a redesign of the existing school webpage. The wants and needs of parents, as noted in the survey were the driving force behind the redesign.
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Sanoja, Vargas Andrés. "Segmentation de pages web, évaluation et applications." Electronic Thesis or Diss., Paris 6, 2015. http://www.theses.fr/2015PA066004.
Full textAbstract:
Les pages web sont devenues plus complexes que jamais, principalement parce qu'elles sont générées par des systèmes de gestion de contenu (CMS). Il est donc difficile de les analyser, c'est-à-dire d'identifier et classifier automatiquement les différents éléments qui les composent. La segmentation de pages web est une des solutions à ce problème. Elle consiste à décomposer une page web en segments, visuellement et sémantiquement cohérents, appelés blocs. La qualité d'une segmentation est mesurée par sa correction et sa généricité, c'est-à-dire sa capacité à traiter des pages web de différents types. Notre recherche se concentre sur l'amélioration de la segmentation et sur une mesure fiable et équitable de la qualité des segmenteurs. Nous proposons un modèle pour la segmentation ainsi que notre segmenteur Block-o-Matic (BoM). Nous définissons un modèle d'évaluation qui prend en compte le contenu ainsi que la géométrie des blocs pour mesurer la correction d'un segmenteur par rapport à une vérité de terrain. Ce modèle est générique, il permet de tester tout algorithme de segmentation et observer ses performances sur différents types de page. Nous l'avons testé sur quatre segmenteurs et quatre types de pages. Les résultats montrent que BOM surpasse ses concurrents en général et que la performance relative d'un segmenteur dépend du type de page. Enfin, nous présentons deux applications développées au dessus de BOM. Pagelyzer compare deux versions de pages web et décide si elles sont similaires ou pas. C'est la principale contribution de notre équipe au projet européen Scape (FP7-IP). Nous avons aussi développé un outil de migration de pages HTML4 vers le nouveau format HTML5<br>Web pages are becoming more complex than ever, as they are generated by Content Management Systems (CMS). Thus, analyzing them, i.e. automatically identifying and classifying different elements from Web pages, such as main content, menus, among others, becomes difficult. A solution to this issue is provided by Web page segmentation which refers to the process of dividing a Web page into visually and semantically coherent segments called blocks.The quality of a Web page segmenter is measured by its correctness and its genericity, i.e. the variety of Web page types it is able to segment. Our research focuses on enhancing this quality and measuring it in a fair and accurate way. We first propose a conceptual model for segmentation, as well as Block-o-Matic (BoM), our Web page segmenter. We propose an evaluation model that takes the content as well as the geometry of blocks into account in order to measure the correctness of a segmentation algorithm according to a predefined ground truth. The quality of four state of the art algorithms is experimentally tested on four types of pages. Our evaluation framework allows testing any segmenter, i.e. measuring their quality. The results show that BoM presents the best performance among the four segmentation algorithms tested, and also that the performance of segmenters depends on the type of page to segment.We present two applications of BoM. Pagelyzer uses BoM for comparing two Web pages versions and decides if they are similar or not. It is the main contribution of our team to the European project Scape (FP7-IP). We also developed a migration tool of Web pages from HTML4 format to HTML5 format in the context of Web archives
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Metikurke, Seema Sreenivasamurthy. "Grid-Enabled Automatic Web Page Classification." Digital Archive @ GSU, 2006. http://digitalarchive.gsu.edu/cs_theses/23.
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Much research has been conducted on the retrieval and classification of web-based information. A big challenge is the performance issue, especially for a classification algorithm returning results for a large set of data that is typical when accessing the Web. This thesis describes a grid-enabled approach for automatic web page classification. The basic approach is first described that uses a vector space model (VSM). An enhancement of the approach through the use of a genetic algorithm (GA) is then described. The enhanced approach can efficiently process candidate web pages from a number of web sites and classify them. A prototype is implemented and empirical studies are conducted. The contributions of this thesis are: 1) Application of grid computing to improve performance of both VSM and GA using VSM based web page classification; 2) Improvement of the VSM classification algorithm by applying GA that uniquely discovers a set of training web pages while also generating a near optimal parameter values set for VSM.
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Khalil, Faten. "Combining web data mining techniques for web page access prediction." University of Southern Queensland, Faculty of Sciences, 2008. http://eprints.usq.edu.au/archive/00004341/.
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[Abstract]: Web page access prediction gained its importance from the ever increasing number of e-commerce Web information systems and e-businesses. Web page prediction, that involves personalising the Web users’ browsing experiences, assists Web masters in the improvement of the Web site structure and helps Web users in navigating the site and accessing the information they need. The most widely used approach for this purpose is the pattern discovery process of Web usage mining that entails many techniques like Markov model, association rules and clustering. Implementing pattern discovery techniques as such helps predict the next page tobe accessed by theWeb user based on the user’s previous browsing patterns. However, each of the aforementioned techniques has its own limitations, especiallywhen it comes to accuracy and space complexity. This dissertation achieves better accuracy as well as less state space complexity and rules generated by performingthe following combinations. First, we combine low-order Markov model and association rules. Markov model analysis are performed on the data sets. If the Markov model prediction results in a tie or no state, association rules are used for prediction. The outcome of this integration is better accuracy, less Markov model state space complexity and less number of generated rules than using each of the methods individually. Second, we integrate low-order Markov model and clustering. The data sets are clustered and Markov model analysis are performed oneach cluster instead of the whole data sets. The outcome of the integration is better accuracy than the first combination with less state space complexity than higherorder Markov model. The last integration model involves combining all three techniques together: clustering, association rules and low-order Markov model. The data sets are clustered and Markov model analysis are performed on each cluster. If the Markov model prediction results in close accuracies for the same item, association rules are used for prediction. This integration model achievesbetter Web page access prediction accuracy, less Markov model state space complexity and less number of rules generated than the previous two models.
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Eriksson, Tobias. "Automatic web page categorizationusing text classication methods." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-142424.
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Over the last few years, the Web has virtually exploded with an enormous amount of web pages of dierent types of content. With the current size of Web, it has become cumbersome to try and manually index and categorize all of its content. Evidently, there is a need for automatic web page categorization. This study explores the use of automatic text classication methods for categorization of web pages. The results in this paper is shown to be comparable to results in other papers on automatic web page categorization, however not as good as results on pure text classication.<br>Under de senaste åren så har Webben exploderat i storlek, med miljontals webbsidor av vitt skilda innehåll. Den enorma storleken av Webben gör att det blir ohanterligt att manuellt indexera och kategorisera allt detta innehåll. Uppenbarligen behövs det automatiska metoder för att kategorisera webbsidor. Denna studie undersöker hur metoder för automatiskt textklassicering kan användas för kategorisering av hemsidor. De uppnådda resultatet i denna rapport är jämförbara med resultat i annan litteratur på samma område, men når ej upp till resultatet i studier på ren textklassicering.
Books on the topic "Web page"
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L, Jones David, and Cutts Dominique C, eds. Web site engineering: Beyond Web page design. Prentice Hall PTR, 1998.
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Matharu, Baldeep Singh. Web page construction tool. University of Manchester, Department of Computer Science, 1997.
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Gündüz-Ögüdücü, Şule. Web Page Recommendation Models. Springer International Publishing, 2011. http://dx.doi.org/10.1007/978-3-031-01842-8.
Full textBook chapters on the topic "Web page"
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Häßler, Ulrike. "Nichts Geht Ohne Web." In Edition Page. Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/978-3-642-98015-2_8.
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Filipe, Francisco, and António Jorge Gouveia. "Page Inspector - Web Page Analyser." In Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-32029-3_11.
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Beacham, Sally, and Ron Lacey. "Web Page Interface." In Paint Shop Pro 8 Zero to Hero. Apress, 2003. http://dx.doi.org/10.1007/978-1-4302-1117-4_12.
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Mohapatra, Sanjay. "Web Page Hosting." In Springer Texts in Business and Economics. Springer US, 2012. http://dx.doi.org/10.1007/978-1-4614-4142-7_3.
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Choi, B., and Z. Yao. "Web Page Classification*." In Foundations and Advances in Data Mining. Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11362197_9.
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Grannell, Craig, Victor Sumner, and Dionysios Synodinos. "Web Page Essentials." In The Essential Guide to HTML5 and CSS3 Web Design. Apress, 2012. http://dx.doi.org/10.1007/978-1-4302-3787-7_2.
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Mladenić, Dunja, and Marko Grobelnik. "Mapping Documents onto Web Page Ontology." In Web Mining: From Web to Semantic Web. Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-30123-3_5.
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Gündüz-Ögüdücü, Şule. "Introduction to Web Page Recommender Systems." In Web Page Recommendation Models. Springer International Publishing, 2011. http://dx.doi.org/10.1007/978-3-031-01842-8_1.
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Gündüz-Ögüdücü, Şule. "Evaluation Metrics." In Web Page Recommendation Models. Springer International Publishing, 2011. http://dx.doi.org/10.1007/978-3-031-01842-8_4.
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Gündüz-Ögüdücü, Şule. "Pattern Extraction." In Web Page Recommendation Models. Springer International Publishing, 2011. http://dx.doi.org/10.1007/978-3-031-01842-8_3.
Full textConference papers on the topic "Web page"
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Trkman, Peter, and Jaka Lindic. "Evaluation of Web Pages as a Tool in Public Relations." In InSITE 2004: Informing Science + IT Education Conference. Informing Science Institute, 2004. http://dx.doi.org/10.28945/2771.
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The paper deals with the question, how the efficiency and successfulness of web pages in information dissemination can be measured. The paper concentrates on the use of a corporate web page in public relations with different interest groups. Basic principles of public relations theory are summarized. The importance of web-page credibility is emphasized and different factors that can have influence on it are identified. Obviously, reliability, punctuality and quality of published information are of utmost importance. However other factors that can affect credibility (such as technical quality, page structure etc.), are also studied. Special attention is paid to another important topic in public relations theory - how can a web page be used to build and flourish dialogue relationships between the company and different interest groups that affect company’s performance. The newly developed model CUT (Content, Usability, Technology) for evaluation of web pages is presented. The model includes evaluation of web pages from different perspectives. While accurate, complete and up-to-date information is certainly crucial, other factors from usability and technology perspective are also emphasized. The model use is demonstrated on a case study of companies from different countries and industry branches.
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Kan, Min-Yen. "Web page classification without the web page." In the 13th international World Wide Web conference. ACM Press, 2004. http://dx.doi.org/10.1145/1013367.1013426.
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"Copyright Page." In 2009 Latin American Web Congress (LA-WEB). IEEE, 2009. http://dx.doi.org/10.1109/la-web.2009.3.
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"Title Page i." In 2009 Latin American Web Congress (LA-WEB). IEEE, 2009. http://dx.doi.org/10.1109/la-web.2009.1.
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"Title Page iii." In 2009 Latin American Web Congress (LA-WEB). IEEE, 2009. http://dx.doi.org/10.1109/la-web.2009.2.
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"[Title page i]." In 2012 Latin American Web Congress (LA-WEB). IEEE, 2012. http://dx.doi.org/10.1109/la-web.2012.1.
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"Blank page." In LA-Web 2004. IEEE, 2004. http://dx.doi.org/10.1109/webmed.2004.1348129.
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"[Title page iii]." In 2012 Eighth Latin American Web Congress (LA-WEB). IEEE, 2012. http://dx.doi.org/10.1109/la-web.2012.2.
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Xu, Zihan, and Yu Sun. "Listing2Speak: A Data-Driven Analytical System to Evaluate the E-Commerce Product Listing using Artificial Intelligence and Big Data Analysis." In 11th International Conference on Signal & Image Processing (SIP 2022). Academy and Industry Research Collaboration Center (AIRCC), 2022. http://dx.doi.org/10.5121/csit.2022.121713.
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In e-commerce, product pages are important to the success of a website [4]. The ultimate goal of an e-commerce site is sales and it takes a great product page to achieve that. However, today, e-commerce entrepreneurs are confused about how to make their product page more attractive [5]. This paper designs a data-driven analytical system to analyze the relationship between different web page features with sales, in order to give users feedback on how to improve their product web pages [6].
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"Roster Page." In 2008 Latin American Web Conference. IEEE, 2008. http://dx.doi.org/10.1109/la-web.2008.28.
Full textReports on the topic "Web page"
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Johnson, Randall P., and Juan C. Fernandez. Trident Web page. Office of Scientific and Technical Information (OSTI), 2012. http://dx.doi.org/10.2172/1044848.
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Gibson, John, Ben Wellner, and Susan Lubar. Adaptive Web-page Content Identification. Defense Technical Information Center, 2007. http://dx.doi.org/10.21236/ada470494.
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Bekkerman, Ron, Shlomo Zilberstein, and James Allan. Web Page Clustering using Heuristic Search in the Web Graph. Defense Technical Information Center, 2006. http://dx.doi.org/10.21236/ada457111.
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Deshpande, Mukund, and George Karypis. Selective Markov Models for Predicting Web-Page Accesses. Defense Technical Information Center, 2000. http://dx.doi.org/10.21236/ada439247.
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Hoffman, P., ed. Publishing the "Tao of the IETF" as a Web Page. RFC Editor, 2012. http://dx.doi.org/10.17487/rfc6722.
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Demott, Daniel L. Contracting Integration Within the Air Force Battlelabs (A Web Page Design). Defense Technical Information Center, 1999. http://dx.doi.org/10.21236/ada389047.
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Ginoza, S. List of Internet Official Protocol Standards: Replaced by a Web Page. RFC Editor, 2013. http://dx.doi.org/10.17487/rfc7101.
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Davison, BH. ''Green'' Biopolymers for Improved Decontamination of Metals from Surfaces: Sorptive Characterization and Coating Properties.. Annual report to be submitted to DOE Program Managers for posting on web page. Office of Scientific and Technical Information (OSTI), 2001. http://dx.doi.org/10.2172/814620.
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ตั้งมณี, ชัชพงศ์, та อัษฎาพร ทรัพย์สมบูรณ์. การเปรียบเทียบการโฆษณาบนอินเตอร์เนตด้วยแบนเนอร์ เมื่อลักษณะการนำเสนอและรูปแบบของเวปเพจที่แสดงแบนเนอร์แตกต่างกัน : รายงานการวิจัย. คณะพาณิชยศาสตร์และการบัญชี จุฬาลงกรณ์มหาวิทยาลัย, 2004. https://doi.org/10.58837/chula.res.2004.22.
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A significant drawback of implementing Internet banners is the small number of clicks (or often referred to as clickthroughs ) on the banners. Several factors have been altered so as to attract more web site visitors and then they would ultimately click on the banners. Two factors of this study’s interest are banner styles and banner presentations. A review of previous literature found no published work on comparison of clickthrough rates among these three banner styles (i.e., embedded, popup and layered styles) or between these two banner presentations (i.e., the presentations on a web page with and without animated background). This study hopes to fill this gap and offers insights into these two factor’s interaction effect on the clickthrough rate. This study recorded the clickthrough rate based on a field experiment in which banners with the three different styles were placed for 56 days on homepages of two sites: www.mbachula.info and it.acc.chula.ac.th. The former characterizes the presentation, of which the background is animated and the latter corresponds to the presentation, of which the background is not animated. Since the collected clickthrough rates are not normally distributed, the analysis had to be nonparametric. The result indicated that the embedded banner received the lowest clickthrough rate. While the difference of these rates on popup and on layered banners are not statistically different; it is however, significantly higher than the rate on the embedded banner. Regarding the clickthrough rates of banners on web pages with and without animated background, the difference was not statistically significant. Finally, because the analysis was not parametric, the test of interaction effect to the three banner styles and the two types of web pages on the clickthrough rate could not be statistically verified. Nevertheless, the exploration indicated a trace of the interaction effect. This study ‘s findings could extend understanding on this multidisciplinary knowledge of advertising and information technology. Practitioners may also apply the findings so as to maximize outcomes from their online campaigns.
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Комарова, Олена Володимирівна, and Альберт Армаїсович Азарян. Computer Simulation of Biological Processes at the High School. CEUR Workshop Proceedings (CEUR-WS.org), 2018. http://dx.doi.org/10.31812/123456789/2695.
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Abstract. Research goals: the necessity of study in high school of the law of Hardy – Weinberg as one of the fundamental genetic laws was justified. The peculiarities of using the method of model experiment in the study of the genetic and evolutionary processes in populations with the use of computer technology. Object of research: computer simulation of population genetic structure. Subject of research: computer simulation of genetic and evolutionary processes in ideal and real populations. Research methods: pedagogical experiment (survey), analysis of scientific publications on the use of the high school method of modelling genetic and evolutionary processes in populations, computer simulation. Results of the research: a web page for processing by the pupils of the modelling results of genetic and evolutionary processes in populations was created.