Relevant bibliographies by topics / Web navigation behavior

Contents

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

Academic literature on the topic 'Web navigation behavior'

Author: Grafiati
Published: 4 June 2021
Last updated: 1 February 2022

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Journal articles on the topic "Web navigation behavior"

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Jindal, Honey, and Neetu Sardana. "An Empirical Analysis of Web Navigation Prediction Techniques." Journal of Cases on Information Technology 19, no. 1 (January 2017): 1–14. http://dx.doi.org/10.4018/jcit.2017010101.

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With the advancement of Information Technology, web is growing rapidly and it has became necessary part of our daily lives. It is mandate to study the navigation behavior of the user to improve the quality of web site design for personalization and further recommendation. Analysis of web navigation behavior heavily relies on navigational models. This paper is an effort to give insights of current state-of-the-art techniques used for web navigation prediction. These navigation models are broadly classified into three categories: sequential mining, classification and clustering. Analytical analysis is performed on all the categories used in web navigation prediction. Further empirical analysis is performed on popular techniques of each category Markov Model (sequential mining), Support vector machine (classification) and K-means (clustering) on the common platform to measure the effectiveness of these techniques.
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Narvekar, Meera, and 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.

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Rezaee, Esmaeel, and S. Alireza Hashemi Golpayegani. "Website user content navigation behavior modeling using time series neural networks." Web Intelligence 17, no. 3 (August 16, 2019): 259–70. http://dx.doi.org/10.3233/web-190417.

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Hariri, Nadjla, Maryam Asadi, and Yazdan Mansourian. "The impact of users’ verbal/imagery cognitive styles on their Web search behavior." Aslib Journal of Information Management 66, no. 4 (July 15, 2014): 401–23. http://dx.doi.org/10.1108/ajim-02-2013-0019.

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Purpose – The purpose of this paper is to investigate the effects of verbal-imagery cognitive styles of information searching behavior of users in using the Web. Design/methodology/approach – In all, 44 participants were recruited for this study. The participants’ cognitive styles were measured by using Riding's Cognitive Style Analysis test. Three search tasks were designed based on Kim's search task definitions. Moreover, an individual lab session was arranged and then participants’ memos were analyzed using content analysis. Findings – In all, 48 strategies in four categories of behaviors in searching the Web were identified. There were associations between users’ cognitive styles and their information searching behavior. The participants’ selection of the search initiation behaviors varied, so that imagers suffered from more varied initial behavior than verbalizers. The verbalizers tended to search in a narrow area, then broadening the area and following structured navigation and reading behavior to process information, while imagers tended to search in a general area, then narrowing down the search and adopting mixed navigational styles and mixed behaviors to process information. This study revealed that there was a difference in search performance of verbalizers and imagers descriptively, as verbalizers spent more time compared to imagers and imagers visited more nodes than verbalizers for the tasks completion. In addition, the task was an important variable influencing the search performance. Based on the key findings (search initiation behaviors, formulating search queries, navigational behaviors, information processing behaviors), a conceptual pattern of Web searching and cognitive styles is presented. Research limitations/implications – The study provides a new understanding of Web users’ information search behavior based on cognitive styles which contributes to the theoretical basis of Web search research. It also raises various questions within the context of user studies Originality/value – The paper adopted a mixed approach in the area of information searching on the Web. A valuable contribution lies in the methods developed.
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Ramanathaiah, Ramakrishnan M., Bhawna Nigam, and M. Niranjanamurthy. "Construction of User’s Navigation Sessions from Web Logs for Web Usage Mining." Journal of Computational and Theoretical Nanoscience 17, no. 9 (July 1, 2020): 4432–37. http://dx.doi.org/10.1166/jctn.2020.9091.

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Web Usage Mining applies fewer techniques in record data to pull out the behavior of users. The knowledge mined from the web log can be utilized in web personalization, Prediction, prefetching, restructuring of web sites etc. It consists of three steps in preprocessing, pattern detection and analysis. Web log information is typically noisy and uncertain and preprocessing is a significant process ahead of mining. The Patterns discovered after applying the mining techniques are dependent on the accuracy of the weblog which in turn depends on the preprocessing phase. The output of preprocessing should be the user’s navigation session file. In this paper the techniques of preprocessing and the method for construction of user’s navigation session file is proposed.
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Richter, Tobias, Johannes Naumann, and Stephan Noller. "LOGPAT: A semi-automatic way to analyze hypertext navigation behavior." Swiss Journal of Psychology 62, no. 2 (June 2003): 113–20. http://dx.doi.org/10.1024//1421-0185.62.2.113.

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In hypertext research, log files represent a useful source of information about users’ navigational behavior. Since log files can contain enormous amounts of data, methods for data reduction with a minimum loss of information are needed. In this paper, LOGPAT (Log file Pattern Analysis) is presented, a Web-based tool for analyzing log files. With LOGPAT, single-unit, sequential, and graph-theoretic measures (including distance matrices) for the description of user navigation can be computed. The paper gives an overview of these methods and discusses their value for psychological research on hypertext. Components and analysis options of LOGPAT are described in detail. The program’s basic options are illustrated by data from a study on learning with hypertext.
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Arora, Anshu Saxena, and Mahesh S. Raisinghani. "Redefining Web Users' Optimal Flow Experiences in Online Environments." International Journal of Web-Based Learning and Teaching Technologies 4, no. 3 (July 2009): 1–21. http://dx.doi.org/10.4018/jwbltt.2009090801.

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The article highlights a research study on consumer navigation behavior through the Web users’ optimal Flow experiences in the online environments. The research study establishes the empirical groundwork for measuring Web users’ Flow experiences in the Web environment. The article proposes a comprehensive definition of Flow on the basis of Comprehensive Process (Flow) Model of Network Navigation, considering that the Flow concept is a multidimensional concept in the “multi-activity” medium of the Web. Flow has been defined as a multi-dimensional and context-specific concept. Furthermore, the research article proposes that there are 10 Flow constructs (also called “the antecedents of Flow”) along with the three states of Flow, namely, Perfect Flow, Imperfect-Intensive Flow, and Imperfect Flow. Consumer Behavior on the Web is studied using the Flow concept for three categories of Flow users, namely, Perfect and Imperfect-Intensive Flow (PIIF) users, Imperfect Flow (IF) users, and Non-Flow (NF) users. These users achieve Flow depending on 10 Flow-constructs and three Flow states. Empirical results suggest a direct relationship between the Flow states and the Flow user categories and between expected Web user in the future (EXPUSE) and the Flow user categories. This research study provides a basis for future researchers to study consumer navigation behavior on the Web using the Flow concept for three categories of Flow users through 10 Flow constructs and three Flow states. The research has significant implications for theory and practice.
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P. G., Om Prakash, Jaya A., Ananthakumaran S., and Ganesh G. "Predicting the user navigation pattern from web logs using weighted support approach." Indonesian Journal of Electrical Engineering and Computer Science 21, no. 3 (March 10, 2021): 1722. http://dx.doi.org/10.11591/ijeecs.v21.i3.pp1722-1730.

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<p class="Abstract"><span id="docs-internal-guid-f3d644ee-7fff-d3c1-15b5-f75fe28d3e2d"><span>A weblog contains the history of previous user navigation pattern. If the customer accesses any portal of organization website, the log is generated in web server, based on sequence of user transaction. The weblog stored in the web server as unstructured format, it contains both positive and negative responses i.e. successful and unsuccessful responses, identifying the positive and negative response is not useful for identifying user behavior of individual user. Initially the successful response is taken, from that conversion of unstructured log format to structured log format through data preprocessing technique. The process of data preprocessor contains three step process data cleaning, user identification and session identification. The pattern is discovered by preprocessing technique from that user navigation pattern is generated. From that navigation pattern classifier technique is applied, the conversion of sequence pattern to sub sequence pattern by clustering technique. This research is to identify the user navigation pattern from weblog. The Improved Spanning classification algorithm classifies the frequent, infrequent and semi frequent pattern. To identify the optimal webpage using classificatopn algorithm from thet user behavior is identified.</span></span></p>
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Papatheocharous, Efi, Marios Belk, Panagiotis Germanakos, and George Samaras. "Towards Implicit User Modeling Based on Artificial Intelligence, Cognitive Styles and Web Interaction Data." International Journal on Artificial Intelligence Tools 23, no. 02 (April 2014): 1440009. http://dx.doi.org/10.1142/s0218213014400090.

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A key challenge of adaptive interactive systems is to provide a positive user experience by extracting implicitly the users' unique characteristics through their interactions with the system, and dynamically adapting and personalizing the system's content presentation and functionality. Among the different dimensions of individual differences that could be considered, this work utilizes the cognitive styles of users as determinant factors for personalization. The overarching goal of this paper is to increase our understanding about the effect of cognitive styles of users on their navigation behavior and content representation preference. We propose a Web-based tool, utilizing Artificial Intelligence techniques, to implicitly capture and find any possible relations between the cognitive styles of users and their characteristics in navigation behavior and content representation preference by using their Web interaction data. The proposed tool has been evaluated with a user study revealing that cognitive styles of users have an effect on their navigation behavior and content representation preference. Research works like the reported one are useful for improving implicit and intelligent user modeling in engineering adaptive interactive systems.
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Abu Al-Khair, Mona M., M. Koutb, and H. Kelash. "Building and Evaluating an Adaptive Smart Web Pages." Journal of Communications and Computer Engineering 3, no. 1 (October 16, 2012): 30. http://dx.doi.org/10.20454/jcce.2013.306.

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Each year the number of consumers and the variety of their interests increase. As a result, providers are seeking ways to infer the customer's interests and to adapt their websites to make the content of interest more easily accessible. Assume that past navigation behavior as an indicator of the user's interests. Then, the records of this behavior, kept in the web-server logs, can be mined to extract the user's interests. On this principal, recommendations can be generated, to help old and new website's visitors to find the information about their interest faster.
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Dissertations / Theses on the topic "Web navigation behavior"

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Gwizdka, Jacek, and 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.

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Task has been recognized as an influential factor in information seeking behavior. An increasing number of studies are concentrating on the specific characteristics of the task as independent variables to explain associated information-seeking activities. This paper examines the relationships between operational measures of information search behavior, subjectively perceived post-task difficulty and objective task complexity in the context of factual information-seeking tasks on the web. A questiondriven, web-based information-finding study was conducted in a controlled experimental setting. The study participants performed nine search tasks of varying complexity. Subjective task difficulty was found to be correlated with many measures that characterize the searcherâ s activities. Four of those measures, the number of the unique web pages visited, the time spent on each page, the degree of deviation from the optimal path and the degree of the navigation pathâ s linearity, were found to be good predictors of subjective task difficulty. Objective task complexity was found to affect the relative importance of those predictors and to affect subjective assessment of task difficulty.
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Bustos, 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.

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The purpose of this paper is to explore web use and web navigation behavior. This paper presents findings from qualitative research based on interviews and diarie studies. The basis of this study is Eli Parisers work about “the filter bubble”. As personalization systems shape our experience of the web, based on who we are, our bubble of knowledge and information becomes smaller. But it’s not only how technology works to show us a narrow part of reality. Our own choices about websites, content and the activities on the web, lead us into another type of bubble. A behavior bubble. A bubble where all the content we consume is interesting. The conclusion of this paper is that narrow web navigation behavior can be observed among all subjects studied irrespective of age and devices used, whereas monotonous web navigation behavior only can be identified among individuals using a smartphone for web browsing.
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Becker, 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.

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Une étude de Nielsen (2006), largement citée, indique que les internautes explorent les pages Web suivant un pattern en forme de "F". Ce résultat a amené les concepteurs à organiser les informations d'une page en fonction de ce comportement, même si aucune étude n'a permis de répliquer ces résultats. Bien que les conclusions de cette étude portent sur le comportement visuel, la question des patterns comportementaux permettant de décrire la navigation des internautes se pose de manière plus générale. L'objectif de cette thèse a donc été de déterminer si des patterns pouvaient être mis en lumière à partir de différents indicateurs. Trois études ont été réalisées. Dans la première étude, 112 participants devaient réaliser quatre tâches de recherche d’information sur deux sites web différents. Le protocole impliquait une répétition immédiate de ces mêmes tâches. Une classification automatique a permis d'identifier 4 patterns qui se distinguent à la fois en termes de navigation sur la page d’accueil, mais aussi de performances. Lors des répétitions, la classification nous a permis d’identifier 3 des 4 patterns précédents. Ceci implique que les individus ne répètent pas forcément leur façon de rechercher l'information et ceci, peu importe la tâche, et le site. La deuxième étude a porté sur 27 individus et impliquait, pour les participants, de se présenter trois fois consécutives à 48 heures d’intervalle, afin de refaire les mêmes tâches. La répétition des tâches, que ce soit à court ou à moyen terme, entraîne une augmentation des performances, c'est-à-dire que les tâches sont réalisées plus rapidement et de façon plus efficiente. Toutefois, les patterns identifiés diffèrent entre les répétitions à court et moyen terme. Un autre résultat observé est que les stratégies ou patterns ne sont pas propres aux individus. En d'autres termes, un individu peut présenter ou adopter plusieurs patterns d'une tâche à une autre, d'un site à un autre ou d'une répétition à l'autre. Enfin, pour notre dernière étude, nous nous sommes demandé si l’homogénéité de nos échantillons pouvait influer sur les patterns. Nous avons donc réalisé une expérimentation comptant 47 participants avec des profils variés. Les individus ont eu tendance à se distinguer selon les 4 mêmes patterns identifiés. Nous avons pu observer qu’en fonction des individus, une même stratégie pouvait conduire à la réussite ou à l’échec de la tâche. De plus, les styles d’apprentissage ne semblent pas liés aux patterns observés. Les limites et les perspectives de ces travaux sont discutées
A 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
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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/.

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The web information behaviors of users as they interacted with a metadata navigator, the Personal Information (PI) Agent, and reflected upon their interaction experiences were studied. The process included studying the complete iterative (repeated) cycle of information needs, information seeking, and information use of users interacting with an internet-based prototype metadata PI Agent tool. Detlor’s theory of web information behaviors of organizational users was utilized as a theoretical foundation for studying human-information interactions via the PI Agent tool. The qualitative research design allowed for the use of triangulation within the context of a one-group pretest-posttest design. Triangulation occurred in three phases: (a) observe, (b) collect, and (c) reflect. Observations were made as participants solved three problem situations. Participants’ computer log and print screen data were collected, and follow-up interviews were conducted once all posttest sessions ended to enable users to reflect on their experiences. The three triangulation phases ensured saturation of data and greater depth regarding the participants’ information behaviors. Content analysis occurred via exploratory pattern analysis using the posttest Problem Steps Recorder (PSR) log data and on the six interviewees’ follow-up interview data. Users engaged in iterative cycles of information needs, information seeking, and information use to resolve the presented problem situations. The participants utilized the PI Agent tool iteratively to eliminate their knowledge gaps regarding the presented problem situations. This study was the first to use PSR log data for capturing evidence of the iterative search process as defined by Detlor. The implications for best practices were inspired by participant feedback, and recommendations for further study are made.
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Chang, Ying-Han, and 張映涵. "A Study on Video Navigation Behavior of Web Leisure." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/61946838097812518307.

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碩士
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.
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Su, Chun-pin, and 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.

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碩士
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.
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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.

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Despite recent success by companies using the Internet to deal with their customers, one of the major remaining problems concerns understanding navigation on the Web and its relationship with Internet marketing. We study the factors that can affect customers' pre-purchase intentions by surveying visitors to a real pharmaceutical web site. More specifically, this study analyzes the behavior of consumers when they are confronted with Internet advertising (navigational characteristics). The model of flow designed by Hoffmann and Novak and previous findings and theories about several relevant affective, cognitive, and conative variables are taken into account to propose our model of consumers' pre-purchase intentions. Our findings suggest that navigational characteristics, skills, challenges, and optimum stimulation level positively and directly influence consumers' exploratory behavior when they visit the pharmaceutical web site. Surfers' involvement has a positive link with their pre-purchase intentions, optimum stimulation level, and attitudes toward the web site. Exploratory behavior has a positive relationship with attitudes toward the web site, whereas, need for cognition negatively influences customers' challenges and attitudes toward the web site. The impact of demographic variables such as gender, age and education on these affective, personality and behavioral variables is also investigated. Future research directions and limitations of this research are fully examined and discussed.
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Books on the topic "Web navigation behavior"

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Luna, David. Bilingual consumers and the Web: Moderators of language effects in Website navigation. Cambridge, MA: Marketing Science Institute, 2002.

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Lambertsson Björk, Eva, Jutta Eschenbach, and Johanna M. Wagner, eds. Women and Fairness. Navigating an Unfair World. Waxmann Verlag GmbH, 2021. http://dx.doi.org/10.31244/9783830993650.

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This collection brings together scholars from various disciplines to ask fundamental questions concerning how women handle the manifold impediments placed before them as they simply attempt to live full human lives. The collection explores narratives of women – real and fictional – who fight against these barriers, who succumb to them, who remain unaware of them, or choose to ignore them. It explores the ways we read women in cultural production, and how women are read in society. We assert the obstacles constructed into the very fabric of societies against fifty percent of the population are unfair, be they hindrances for women to attain their goals, encumbrances that limit women’s speech and societal participation – communal and artistic – or hindrances that prohibit specific behaviors and images of women.
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Troisi, Alfonso. Pleasure. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780199393404.003.0002.

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Contemporary neurobiological research has greatly improved our understanding of brain mechanisms that regulate hedonic response and the environmental stimuli that trigger physical and mental pleasure. However, to explain what purpose pleasure serves, we need to look at the problem from the perspective of evolutionary biology. Focusing on a specific type of pleasure, sexual pleasure, this chapter introduces several evolutionary studies that show how the variation in pleasurable experiences becomes understandable when hedonic capacity is viewed as an inner navigator that evolved to guide individuals toward the most adaptive behavioral choices. As a case in point, the alternative hypotheses that have been advanced to explain the evolution of female orgasm (the adaptive versus the byproduct hypothesis) are discussed. The findings of recent studies exploring the complexity of human sexual response and the striking sex differences that distinguish male and female responses to sexual stimuli are also presented.
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Modir, Shahla, and George Munoz, eds. Integrative Addiction and Recovery. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780190275334.001.0001.

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Integrative Addiction and Recovery is a book discussing the epidemic of addiction that is consuming our friends, family, and community nationwide. In 2016, there were 64,000 drug overdoses, and addiction became the top cause of accidental death in America in 2015. We are in a crisis and in need of a robust and integrated solution. We begin with the definition of addiction, neurobiology of addiction, and the epidemiology of varying substances of abuse and treatment guidelines. Section II reviews different types of addiction such as food, alcohol, sedative-hypnotics, cannabis, stimulants (such as cocaine and methamphetamine), opiates (including prescription and illicit opiates), and tobacco, and evidence-based approaches for their treatment using psychotherapy, pharmacotherapy, as well as holistic treatments including acupuncture, nutraceuticals, exercise, yoga, and meditation. We also have chapters on behavioral addictions and hallucinogens. Section III reviews co-occurring disorders and their evidence-based integrative treatment and also overviews the holistic therapeutic techniques such as acupuncture and TCM, Ayurveda, homeopathy, nutrition, nutraceuticals, art and aroma therapy, and equine therapy as tools for recovery. We have unique chapters on shamanism and ibogaine, as well as spirituality and group support (12 steps included). The final section deals with challenges facing recovery such as trauma, acute/chronic pain, and post acute withdrawal. Integrative Addiction and Recovery is an innovative and progressive textbook, navigating this complex disease with the most comprehensive approach.
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Book chapters on the topic "Web navigation behavior"

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Germanakos, Panagiotis, Efi Papatheocharous, Marios Belk, and George Samaras. "Data-Driven User Profiling to Support Web Adaptation through Cognitive Styles and Navigation Behavior." In 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.

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Belk, Marios, Efi Papatheocharous, Panagiotis Germanakos, and George Samaras. "Investigating the Relation between Users’ Cognitive Style and Web Navigation Behavior with K-means Clustering." In 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.

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Khosla, Shivkumar, and Varunakshi Bhojane. "Performing Web Log Analysis and Predicting Intelligent Navigation Behavior Based on Student Accessing Distance Education System." In 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.

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Zaïane, Osmar R., Jia Li, and Robert Hayward. "Mission-Based Navigational Behaviour Modeling for Web Recommender Systems." In Advances in Web Mining and Web Usage Analysis, 37–55. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11899402_3.

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Juvina, Ion, and Herre van Oostendorp. "Individual Differences and Behavioral Aspects Involved in Modeling Web Navigation." In 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.

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Algur, Siddu P., Nitin P. Jadhav, and N. H. Ayachit. "Web Personalization Based on Short Term Navigational Behaviour and Meta Keywords." In 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.

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Geetharamani, R., and P. Revathy. "Grouping Users Through Pair Wise Sequence Alignment and Graph Traversal Based on Web Page Navigation Behaviour." In Lecture Notes in Electrical Engineering, 1770–91. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-1420-3_182.

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Arora, Anshu Saxena, and Mahesh S. Raisinghani. "Redefining Web Users' Optimal Flow Experiences in Online Environments." In Web-Based Education, 1531–49. IGI Global, 2010. http://dx.doi.org/10.4018/978-1-61520-963-7.ch104.

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The article highlights a research study on consumer navigation behavior through the Web users’ optimal Flowexperiences in the online environments. The research study establishes the empirical groundwork for measuring Webusers’ Flow experiences in the Web environment. The article proposes a comprehensive definition of Flow on the basis of Comprehensive Process (Flow) Model of Network Navigation, considering that the Flow concept is a multidimensional concept in the “multi-activity” medium of the Web. Flow has been defined as a multi-dimensional and context-specific concept. Furthermore, the research article proposes that there are 10 Flow constructs (also called “the antecedents of Flow”) along with the three states of Flow, namely, Perfect Flow, Imperfect-IntensiveFlow, and Imperfect Flow. Consumer Behavior on the Webis studied using the Flow concept for three categories ofFlow users, namely, Perfect and Imperfect-Intensive Flow(PIIF) users, Imperfect Flow (IF) users, and Non-Flow (NF) users. These users achieve Flow depending on 10 Flow-constructs and three Flow states. Empirical results suggest a direct relationship between the Flow states and the Flowuser categories and between expected Web user in the future (EXPUSE) and the Flow user categories. This research study provides a basis for future researchers to study consumer navigation behavior on the Web using theFlow concept for three categories of Flow users through 10Flow constructs and three Flow states. The research has significant implications for theory and practice.
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Kung, Hsiang-Jui, and Hui-Lien Tung. "Web Application Classification." In Handbook of Research on Public Information Technology, 520–30. IGI Global, 2008. http://dx.doi.org/10.4018/978-1-59904-857-4.ch048.

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Many companies use the Web to communicate with the external world as well as within their organizations and to carry out their business processes more effectively. A survey on Web application development shows that 84% of development projects do not meet business needs, 56% do not have the required functionality, 79% are behind schedule, and 63% are over budget (Standish Group, 2002). García-Cabrera, Rodríguez-Fórtiz, and Parets-Llorca (2002) report that the development of a Web application is never finished, and the nature of Web applications is evolutionary. The architecture of Web applications has three layers: conceptual, presentation, and navigation. It also has two perspectives: designer and viewer. Software evolution is “the dynamic behavior of programming systems as they are maintained and enhanced over their life times” (Belady & Lehman, 1976). Web application evolution is of increasing importance as more Web systems are in production.
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Arora, Anshu Saxena, and Mahesh S. Raisinghani. "Redefining Web Users’ Optimal Flow Experiences In Online Environments." In 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.

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The article highlights a research study on consumer navigation behavior through the Web users’ optimal Flow experiences in the online environments. The research study establishes the empirical groundwork for measuring Web users’ Flow experiences in the Web environment. The article proposes a comprehensive definition of Flow on the basis of Comprehensive Process (Flow) Model of Network Navigation, considering that the Flow concept is a multidimensional concept in the “multi-activity” medium of the Web. Flow has been defined as a multi-dimensional and context-specific concept. Furthermore, the research article proposes that there are 10 Flow constructs (also called “the antecedents of Flow”) along with the three states of Flow, namely, Perfect Flow, Imperfect-Intensive Flow, and Imperfect Flow. Consumer Behavior on the Web is studied using the Flow concept for three categories of Flow users, namely, Perfect and Imperfect-Intensive Flow (PIIF) users, Imperfect Flow (IF) users, and Non-Flow (NF) users. These users achieve Flow depending on 10 Flow-constructs and three Flow states. Empirical results suggest a direct relationship between the Flow states and the Flow user categories and between expected Web user in the future (EXPUSE) and the Flow user categories. This research study provides a basis for future researchers to study consumer navigation behavior on the Web using the Flow concept for three categories of Flow users through 10 Flow constructs and three Flow states. The research has significant implications for theory and practice.
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Conference papers on the topic "Web navigation behavior"

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Xue, Li, Ming Chen, Yun Xiong, and Yangyong Zhu. "User Navigation Behavior Mining Using Multiple Data Domain Description." In 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.

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Pu, Hsiao-Tieh, and Yi-Wei Wong. "User navigation behavior of a selective dissemination of web information service." In the 2012 iConference. New York, New York, USA: ACM Press, 2012. http://dx.doi.org/10.1145/2132176.2132245.

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Zhang, Xin-lin, Huai-kou Miao, and Hong-wei Zeng. "Modeling and Consistency Checking Based on Category for Web Navigation Behavior." In 2009 International Conference on Computer Modeling and Simulation. ICCMS 2009. IEEE, 2009. http://dx.doi.org/10.1109/iccms.2009.82.

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Gomes, Bruno Guilherme, Pedro H. F. Holanda, Luciana F. Pontelho, Ana Paula Couto da Silva, and Olga Goussevskaia. "Characterizing User Behavior in a Music Navigation Application with Real-time Feedback." In Webmedia '17: Brazilian Symposium on Multimedia and the Web. New York, NY, USA: ACM, 2017. http://dx.doi.org/10.1145/3126858.3126875.

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Ghavare, Prajakta, and Prashant Ahire. "Big Data Classification of Users Navigation and Behavior Using Web Server Logs." In 2018 Fourth International Conference on Computing Communication Control and Automation (ICCUBEA). IEEE, 2018. http://dx.doi.org/10.1109/iccubea.2018.8697606.

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Yilmaz, Hakan, and Pinar Senkul. "Using Ontology and Sequence Information for Extracting Behavior Patterns from Web Navigation Logs." In 2010 IEEE International Conference on Data Mining Workshops (ICDMW). IEEE, 2010. http://dx.doi.org/10.1109/icdmw.2010.44.

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Mangal, Deepak, and K. V. Arya. "An efficient approach for web path traversal pattern based on visitor preferences and navigation behavior." In 2014 9th International Conference on Industrial and Information Systems (ICIIS). IEEE, 2014. http://dx.doi.org/10.1109/iciinfs.2014.7036508.

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Bansal, Priti, and Sangeeta Sabharwal. "A model based approach to test case generation for testing the navigation behavior of dynamic web applications." In 2013 Sixth International Conference on Contemporary Computing (IC3). IEEE, 2013. http://dx.doi.org/10.1109/ic3.2013.6612192.

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Hayati, Pedram, Vidyasagar Potdar, Kevin Chai, and Alex Talevski. "Web Spambot Detection Based on Web Navigation Behaviour." In 2010 24th IEEE International Conference on Advanced Information Networking and Applications. IEEE, 2010. http://dx.doi.org/10.1109/aina.2010.92.

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Lincke, Alisa, David Prieto, Romain Herault, Elin-Sofie Forsgärde, and Marcelo Milrad. "Visualizing Learners’ Navigation Behaviour using 360 Degrees Interactive Videos." In 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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You might also be interested in the extended bibliographies on the topic 'Web navigation behavior' for particular source types:
Journal articles
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