Literatura académica sobre el tema "Web navigation behavior"
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Artículos de revistas sobre el tema "Web navigation behavior"
Jindal, Honey y Neetu Sardana. "An Empirical Analysis of Web Navigation Prediction Techniques". Journal of Cases on Information Technology 19, n.º 1 (enero de 2017): 1–14. http://dx.doi.org/10.4018/jcit.2017010101.
Texto completoNarvekar, Meera y Shaikh Sakina Banu. "Predicting User's Web Navigation Behavior Using Hybrid Approach". Procedia Computer Science 45 (2015): 3–12. http://dx.doi.org/10.1016/j.procs.2015.03.073.
Texto completoRezaee, Esmaeel y S. Alireza Hashemi Golpayegani. "Website user content navigation behavior modeling using time series neural networks". Web Intelligence 17, n.º 3 (16 de agosto de 2019): 259–70. http://dx.doi.org/10.3233/web-190417.
Texto completoHariri, Nadjla, Maryam Asadi y Yazdan Mansourian. "The impact of users’ verbal/imagery cognitive styles on their Web search behavior". Aslib Journal of Information Management 66, n.º 4 (15 de julio de 2014): 401–23. http://dx.doi.org/10.1108/ajim-02-2013-0019.
Texto completoRamanathaiah, Ramakrishnan M., Bhawna Nigam y M. Niranjanamurthy. "Construction of User’s Navigation Sessions from Web Logs for Web Usage Mining". Journal of Computational and Theoretical Nanoscience 17, n.º 9 (1 de julio de 2020): 4432–37. http://dx.doi.org/10.1166/jctn.2020.9091.
Texto completoRichter, Tobias, Johannes Naumann y Stephan Noller. "LOGPAT: A semi-automatic way to analyze hypertext navigation behavior". Swiss Journal of Psychology 62, n.º 2 (junio de 2003): 113–20. http://dx.doi.org/10.1024//1421-0185.62.2.113.
Texto completoArora, Anshu Saxena y Mahesh S. Raisinghani. "Redefining Web Users' Optimal Flow Experiences in Online Environments". International Journal of Web-Based Learning and Teaching Technologies 4, n.º 3 (julio de 2009): 1–21. http://dx.doi.org/10.4018/jwbltt.2009090801.
Texto completoP. G., Om Prakash, Jaya A., Ananthakumaran S. y Ganesh G. "Predicting the user navigation pattern from web logs using weighted support approach". Indonesian Journal of Electrical Engineering and Computer Science 21, n.º 3 (10 de marzo de 2021): 1722. http://dx.doi.org/10.11591/ijeecs.v21.i3.pp1722-1730.
Texto completoPapatheocharous, Efi, Marios Belk, Panagiotis Germanakos y George Samaras. "Towards Implicit User Modeling Based on Artificial Intelligence, Cognitive Styles and Web Interaction Data". International Journal on Artificial Intelligence Tools 23, n.º 02 (abril de 2014): 1440009. http://dx.doi.org/10.1142/s0218213014400090.
Texto completoAbu Al-Khair, Mona M., M. Koutb y H. Kelash. "Building and Evaluating an Adaptive Smart Web Pages". Journal of Communications and Computer Engineering 3, n.º 1 (16 de octubre de 2012): 30. http://dx.doi.org/10.20454/jcce.2013.306.
Texto completoTesis sobre el tema "Web navigation behavior"
Gwizdka, Jacek y Ian Spence. "What Can Searching Behavior Tell Us About the Difficulty of Information Tasks? A Study of Web Navigation". American Society for Information Science and Technology (ASIS&T), 2006. http://hdl.handle.net/10150/106061.
Texto completoBustos, Christian. "Beteendebubblan : En studie om navigationsbeteende på internet med fokus på korta navigationstillfällen". Thesis, Södertörns högskola, Institutionen för naturvetenskap, miljö och teknik, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:sh:diva-26211.
Texto completoBecker, Mélanie. "L’exploration des pages web : de la caractérisation interindividuelle à l’identification de patterns comportementaux". Thesis, Université de Lorraine, 2016. http://www.theses.fr/2016LORR0344/document.
Texto completoA study by Nielsen (2006), widely cited, indicates that Internet users explore web pages following a "F" shape pattern. This result brought the designers to organize the information of a page according to this behavior, even if no study replicated these results. Although the conclusions of this study concern the visual behavior, the question of the behavioral patterns allowing describing the navigation of the Internet users remains in a more general way. Thus the aim of this thesis was to determine if patterns could be revealed from various indicators. Three studies were conducted. In the first study, 112 participants had to perform four information search tasks on two different websites. The experimental protocol involved an immediate repetition of the same tasks. A clustering method allowed us to identify 4 behavioral patterns, which distinguish themselves in terms of navigation on the homepage, but also in terms of performances. During the repetitions, the classification allowed us to identify 3 patterns out of the 4 previous ones. This implies that the individuals do not repeat necessarily the way they look for the information and this, no matter the task, and the Web site. The second experiment involved 27 persons. They had to come three times, with 48 hour intervals to repeat the same tasks. The repetition of the tasks, whether in short or medium-term, increased the performances of the users, that is the tasks are more quickly realized and in a more efficient way. However, the identified patterns differ between the short and medium-term repetitions. Another observed result is that the strategies or patterns are not peculiar to the individuals. In other words, an individual can present or adopt several patterns from a task to another one, from a site to an other one or from a repetition to the other one. Finally, in our last study, we wondered if the homogeneity of our previous samples could have influenced the patterns. So we conducted an experiment with 47 participants with varied profiles. The individuals tended to distinguish themselves according to 4 same identified patterns. We were able to observe that according to the individuals, the same strategy could lead to the success or to the failure of the task. Furthermore, the learning styles did not seem to be related to the observed patterns. Limits and prospects of this work are discussed
McMillan, Tyson DeShaun. "Web Information Behaviors of Users Interacting with a Metadata Navigator". Thesis, University of North Texas, 2013. https://digital.library.unt.edu/ark:/67531/metadc407784/.
Texto completoChang, Ying-Han y 張映涵. "A Study on Video Navigation Behavior of Web Leisure". Thesis, 2011. http://ndltd.ncl.edu.tw/handle/61946838097812518307.
Texto completo國立臺灣師範大學
圖書資訊學研究所
100
With the rapid development of video technology and web bandwidth, surfing the Internet becomes a daily life activities. However, it is not only work but also web leisure on there. Watching video is a popular and common leisure activity, more and more users go to watch, share, search, and save video by video sharing platforms like YouTube. Under this situation, how these users navigation, exploratory and search the video they want and satisfied their needs become an important study issue. This pilot study aims to investigate the users’ video navigation behavior on video sharing website, also investigate the motivation and need of web video leisure. The research methods include questionnaire, screen log file, diary and interview. This study recruits 16 participants who will watch the YouTube video, 10 participants attended 4 methods, 6 participants only attended questionnaire and interview. The study uses statistics, observation, and interview, tries to further analyze their characteristics of video navigation behavior, and their motivation and need of web video. The results show that participants usually do the web video leisure and other web leisure at the same time, especially Facebook; choose videos which depend on their personal interests, the video contents more than 40% belong to TV programs. In the process of video navigating, they feel attracted by the video thumbnails and titles to keep linking other videos; don’t like to do social activities on video sharing website. While after watching video, they feel good and comfortable in spiritual, however about 11% participants report that they feel tired and exhausted in physical. Finally the findings are compared with TV viewing behavior. Implications for the system design of video sharing website’s interfaces and users’ behavior are discussed.
Su, Chun-pin y 蘇俊斌. "Apply Web Mining Techniques to Analyze the Navigation Behavior of Visitors - Using Online Content Site as Example". Thesis, 2005. http://ndltd.ncl.edu.tw/handle/65829625915742346689.
Texto completo國立臺灣大學
資訊管理學研究所
93
According to the survey report, issued by TWNIC Jan. 2005, Internet popularity had grown to 13,800,000 users, about 4,630,000 home families, approaching 65% of whole families in Taiwan. Therefore, the Internet not only is a powerful media, but also become an important channel to enterprises. All enterprises are eager to find out a useful way to synergize such a powerful channel. They have been trying to analyze the visiting log of the web, and mine the behavior of customers who had contacted the enterprise through the Internet, willing to collect more customer information and provide more personalized services to customers. However, in practicality, there are some difficulties encountered. The First is the web logs are distributed information, which are separated on several servers, and need to be integrated and do lots of processing. Secondary, one of the difficulties is how to extract the key features from the huge logs, and how to solve the scalability issues. The third problem is how to find the suitable mining tools to discover the implicit knowledge from bunch of irrelevant raw data. Our research proposes a novel framework, which integrates most useful public domain resources and some self-developed tools, provides powerful analyzing tools to overcome such difficulties. This thesis also illustrates a novel algorithm to visualize click-stream mining result, named “Click-map”. This presentation is able to assist the web master to discover users’ navigation behaviors from the click path analysis more easily. For examining the availability of the framework and analysis methods, we use online web logs for the period of one month as examples. The logs came from an online content search services site, with 1.26GB data size and over 66 million records, recorded from March to April in 2005. The results proofed our framework to be useful and effective.
Richard, Marie-Odile. "Navigational characteristics effectiveness of pharmaceutical web sites on consumer behavior and pre-purchase intentions". Thesis, 2003. http://spectrum.library.concordia.ca/1972/1/MQ77959.pdf.
Texto completoLibros sobre el tema "Web navigation behavior"
Luna, David. Bilingual consumers and the Web: Moderators of language effects in Website navigation. Cambridge, MA: Marketing Science Institute, 2002.
Buscar texto completoLambertsson Björk, Eva, Jutta Eschenbach y Johanna M. Wagner, eds. Women and Fairness. Navigating an Unfair World. Waxmann Verlag GmbH, 2021. http://dx.doi.org/10.31244/9783830993650.
Texto completoTroisi, Alfonso. Pleasure. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780199393404.003.0002.
Texto completoModir, Shahla y George Munoz, eds. Integrative Addiction and Recovery. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780190275334.001.0001.
Texto completoCapítulos de libros sobre el tema "Web navigation behavior"
Germanakos, Panagiotis, Efi Papatheocharous, Marios Belk y George Samaras. "Data-Driven User Profiling to Support Web Adaptation through Cognitive Styles and Navigation Behavior". En IFIP Advances in Information and Communication Technology, 500–509. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-33412-2_51.
Texto completoBelk, Marios, Efi Papatheocharous, Panagiotis Germanakos y George Samaras. "Investigating the Relation between Users’ Cognitive Style and Web Navigation Behavior with K-means Clustering". En Lecture Notes in Computer Science, 337–46. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-33999-8_40.
Texto completoKhosla, Shivkumar y Varunakshi Bhojane. "Performing Web Log Analysis and Predicting Intelligent Navigation Behavior Based on Student Accessing Distance Education System". En Communications in Computer and Information Science, 70–81. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-36321-4_7.
Texto completoZaïane, Osmar R., Jia Li y Robert Hayward. "Mission-Based Navigational Behaviour Modeling for Web Recommender Systems". En Advances in Web Mining and Web Usage Analysis, 37–55. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11899402_3.
Texto completoJuvina, Ion y Herre van Oostendorp. "Individual Differences and Behavioral Aspects Involved in Modeling Web Navigation". En User-Centered Interaction Paradigms for Universal Access in the Information Society, 77–95. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-30111-0_7.
Texto completoAlgur, Siddu P., Nitin P. Jadhav y N. H. Ayachit. "Web Personalization Based on Short Term Navigational Behaviour and Meta Keywords". En Advances in Intelligent Systems and Computing, 773–86. New Delhi: Springer India, 2013. http://dx.doi.org/10.1007/978-81-322-0740-5_92.
Texto completoGeetharamani, R. y P. Revathy. "Grouping Users Through Pair Wise Sequence Alignment and Graph Traversal Based on Web Page Navigation Behaviour". En Lecture Notes in Electrical Engineering, 1770–91. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-1420-3_182.
Texto completoArora, Anshu Saxena y Mahesh S. Raisinghani. "Redefining Web Users' Optimal Flow Experiences in Online Environments". En Web-Based Education, 1531–49. IGI Global, 2010. http://dx.doi.org/10.4018/978-1-61520-963-7.ch104.
Texto completoKung, Hsiang-Jui y Hui-Lien Tung. "Web Application Classification". En Handbook of Research on Public Information Technology, 520–30. IGI Global, 2008. http://dx.doi.org/10.4018/978-1-59904-857-4.ch048.
Texto completoArora, Anshu Saxena y Mahesh S. Raisinghani. "Redefining Web Users’ Optimal Flow Experiences In Online Environments". En Dynamic Advancements in Teaching and Learning Based Technologies, 181–98. IGI Global, 2011. http://dx.doi.org/10.4018/978-1-60960-153-9.ch010.
Texto completoActas de conferencias sobre el tema "Web navigation behavior"
Xue, Li, Ming Chen, Yun Xiong y Yangyong Zhu. "User Navigation Behavior Mining Using Multiple Data Domain Description". En 2010 IEEE/ACM International Conference on Web Intelligence-Intelligent Agent Technology (WI-IAT). IEEE, 2010. http://dx.doi.org/10.1109/wi-iat.2010.187.
Texto completoPu, Hsiao-Tieh y Yi-Wei Wong. "User navigation behavior of a selective dissemination of web information service". En the 2012 iConference. New York, New York, USA: ACM Press, 2012. http://dx.doi.org/10.1145/2132176.2132245.
Texto completoZhang, Xin-lin, Huai-kou Miao y Hong-wei Zeng. "Modeling and Consistency Checking Based on Category for Web Navigation Behavior". En 2009 International Conference on Computer Modeling and Simulation. ICCMS 2009. IEEE, 2009. http://dx.doi.org/10.1109/iccms.2009.82.
Texto completoGomes, Bruno Guilherme, Pedro H. F. Holanda, Luciana F. Pontelho, Ana Paula Couto da Silva y Olga Goussevskaia. "Characterizing User Behavior in a Music Navigation Application with Real-time Feedback". En Webmedia '17: Brazilian Symposium on Multimedia and the Web. New York, NY, USA: ACM, 2017. http://dx.doi.org/10.1145/3126858.3126875.
Texto completoGhavare, Prajakta y Prashant Ahire. "Big Data Classification of Users Navigation and Behavior Using Web Server Logs". En 2018 Fourth International Conference on Computing Communication Control and Automation (ICCUBEA). IEEE, 2018. http://dx.doi.org/10.1109/iccubea.2018.8697606.
Texto completoYilmaz, Hakan y Pinar Senkul. "Using Ontology and Sequence Information for Extracting Behavior Patterns from Web Navigation Logs". En 2010 IEEE International Conference on Data Mining Workshops (ICDMW). IEEE, 2010. http://dx.doi.org/10.1109/icdmw.2010.44.
Texto completoMangal, Deepak y K. V. Arya. "An efficient approach for web path traversal pattern based on visitor preferences and navigation behavior". En 2014 9th International Conference on Industrial and Information Systems (ICIIS). IEEE, 2014. http://dx.doi.org/10.1109/iciinfs.2014.7036508.
Texto completoBansal, Priti y Sangeeta Sabharwal. "A model based approach to test case generation for testing the navigation behavior of dynamic web applications". En 2013 Sixth International Conference on Contemporary Computing (IC3). IEEE, 2013. http://dx.doi.org/10.1109/ic3.2013.6612192.
Texto completoHayati, Pedram, Vidyasagar Potdar, Kevin Chai y Alex Talevski. "Web Spambot Detection Based on Web Navigation Behaviour". En 2010 24th IEEE International Conference on Advanced Information Networking and Applications. IEEE, 2010. http://dx.doi.org/10.1109/aina.2010.92.
Texto completoLincke, Alisa, David Prieto, Romain Herault, Elin-Sofie Forsgärde y Marcelo Milrad. "Visualizing Learners’ Navigation Behaviour using 360 Degrees Interactive Videos". En 15th International Conference on Web Information Systems and Technologies. SCITEPRESS - Science and Technology Publications, 2019. http://dx.doi.org/10.5220/0008356203580364.
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