The Experts below are selected from a list of 7026 Experts worldwide ranked by ideXlab platform
Michael L. Nelson - One of the best experts on this subject based on the ideXlab platform.
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evaluating sliding and sticky target policies by measuring temporal drift in acyclic walks through a web archive
International Journal on Digital Libraries, 2015Co-Authors: Scott G Ainsworth, Michael L. NelsonAbstract:When viewing an archived page using the archive's user interface (UI), the user selects a datetime to view from a list. The archived web page, if available, is then displayed. From this display, the web archive UI attempts to simulate the web Browsing Experience by smoothly transitioning between archived pages. During this process, the target datetime changes with each link followed, potentially drifting away from the datetime originally selected. For sparsely archived resources, this almost transparent drift can be many years in just a few clicks. We conducted 200,000 acyclic walks of archived pages, following up to 50 links per walk, comparing the results of two target datetime policies. The Sliding Target policy allows the target datetime to change as it does in archive UIs such as the Internet Archive's Wayback Machine. The Sticky Target policy, represented by the Memento API, keeps the target datetime the same throughout the walk. We found that the Sliding Target policy drift increases with the number of walk steps, number of domains visited, and choice (number of links available). However, the Sticky Target policy controls temporal drift, holding it to $$<$$<30 days on average regardless of walk length or number of domains visited. The Sticky Target policy shows some increase as choice increases, but this may be caused by other factors. We conclude that based on walk length, the Sticky Target policy generally produces at least 30 days less drift than the Sliding Target policy.
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evaluating sliding and sticky target policies by measuring temporal drift in acyclic walks through a web archive
arXiv: Digital Libraries, 2013Co-Authors: Scott G Ainsworth, Michael L. NelsonAbstract:When a user views an archived page using the archive's user interface (UI), the user selects a datetime to view from a list. The archived web page, if available, is then displayed. From this display, the web archive UI attempts to simulate the web Browsing Experience by smoothly transitioning between archived pages. During this process, the target datetime changes with each link followed; drifting away from the datetime originally selected. When Browsing sparsely-archived pages, this nearly-silent drift can be many years in just a few clicks. We conducted 200,000 acyclic walks of archived pages, following up to 50 links per walk, comparing the results of two target datetime policies. The Sliding Target policy allows the target datetime to change as it does in archive UIs such as the Internet Archive's Wayback Machine. The Sticky Target policy, represented by the Memento API, keeps the target datetime the same throughout the walk. We found that the Sliding Target policy drift increases with the number of walk steps, number of domains visited, and choice (number of links available). However, the Sticky Target policy controls temporal drift, holding it to less than 30 days on average regardless of walk length or number of domains visited. The Sticky Target policy shows some increase as choice increases, but this may be caused by other factors. We conclude that based on walk length, the Sticky Target policy generally produces at least 30 days less drift than the Sliding Target policy.
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Evaluating Methods to Rediscover Missing Web Pages from the Web Infrastructure
arXiv: Information Retrieval, 2009Co-Authors: Martin Klein, Michael L. NelsonAbstract:Missing web pages (pages that return the 404 "Page Not Found" error) are part of the Browsing Experience. The manual use of search engines to rediscover missing pages can be frustrating and unsuccessful. We compare four automated methods for rediscovering web pages. We extract the page's title, generate the page's lexical signature (LS), obtain the page's tags from the bookmarking website delicious.com and generate a LS from the page's link neighborhood. We use the output of all methods to query Internet search engines and analyze their retrieval performance. Our results show that both LSs and titles perform fairly well with over 60% URIs returned top ranked from Yahoo!. However, the combination of methods improves the retrieval performance. Considering the complexity of the LS generation, querying the title first and in case of insufficient results querying the LSs second is the preferable setup. This combination accounts for more than 75% top ranked URIs.
Hernan Lira - One of the best experts on this subject based on the ideXlab platform.
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using psychophysiological sensors to assess mental workload during web Browsing
Sensors, 2018Co-Authors: Angel Jimenezmolina, Cristian Retamal, Hernan LiraAbstract:Knowledge of the mental workload induced by a Web page is essential for improving users’ Browsing Experience. However, continuously assessing the mental workload during a Browsing task is challenging. To address this issue, this paper leverages the correlation between stimuli and physiological responses, which are measured with high-frequency, non-invasive psychophysiological sensors during very short span windows. An experiment was conducted to identify levels of mental workload through the analysis of pupil dilation measured by an eye-tracking sensor. In addition, a method was developed to classify mental workload by appropriately combining different signals (electrodermal activity (EDA), electrocardiogram, photoplethysmo-graphy (PPG), electroencephalogram (EEG), temperature and pupil dilation) obtained with non-invasive psychophysiological sensors. The results show that the Web Browsing task involves four levels of mental workload. Also, by combining all the sensors, the efficiency of the classification reaches 93.7%.
Angel Jimenezmolina - One of the best experts on this subject based on the ideXlab platform.
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using psychophysiological sensors to assess mental workload during web Browsing
Sensors, 2018Co-Authors: Angel Jimenezmolina, Cristian Retamal, Hernan LiraAbstract:Knowledge of the mental workload induced by a Web page is essential for improving users’ Browsing Experience. However, continuously assessing the mental workload during a Browsing task is challenging. To address this issue, this paper leverages the correlation between stimuli and physiological responses, which are measured with high-frequency, non-invasive psychophysiological sensors during very short span windows. An experiment was conducted to identify levels of mental workload through the analysis of pupil dilation measured by an eye-tracking sensor. In addition, a method was developed to classify mental workload by appropriately combining different signals (electrodermal activity (EDA), electrocardiogram, photoplethysmo-graphy (PPG), electroencephalogram (EEG), temperature and pupil dilation) obtained with non-invasive psychophysiological sensors. The results show that the Web Browsing task involves four levels of mental workload. Also, by combining all the sensors, the efficiency of the classification reaches 93.7%.
Scott G Ainsworth - One of the best experts on this subject based on the ideXlab platform.
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evaluating sliding and sticky target policies by measuring temporal drift in acyclic walks through a web archive
International Journal on Digital Libraries, 2015Co-Authors: Scott G Ainsworth, Michael L. NelsonAbstract:When viewing an archived page using the archive's user interface (UI), the user selects a datetime to view from a list. The archived web page, if available, is then displayed. From this display, the web archive UI attempts to simulate the web Browsing Experience by smoothly transitioning between archived pages. During this process, the target datetime changes with each link followed, potentially drifting away from the datetime originally selected. For sparsely archived resources, this almost transparent drift can be many years in just a few clicks. We conducted 200,000 acyclic walks of archived pages, following up to 50 links per walk, comparing the results of two target datetime policies. The Sliding Target policy allows the target datetime to change as it does in archive UIs such as the Internet Archive's Wayback Machine. The Sticky Target policy, represented by the Memento API, keeps the target datetime the same throughout the walk. We found that the Sliding Target policy drift increases with the number of walk steps, number of domains visited, and choice (number of links available). However, the Sticky Target policy controls temporal drift, holding it to $$<$$<30 days on average regardless of walk length or number of domains visited. The Sticky Target policy shows some increase as choice increases, but this may be caused by other factors. We conclude that based on walk length, the Sticky Target policy generally produces at least 30 days less drift than the Sliding Target policy.
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evaluating sliding and sticky target policies by measuring temporal drift in acyclic walks through a web archive
arXiv: Digital Libraries, 2013Co-Authors: Scott G Ainsworth, Michael L. NelsonAbstract:When a user views an archived page using the archive's user interface (UI), the user selects a datetime to view from a list. The archived web page, if available, is then displayed. From this display, the web archive UI attempts to simulate the web Browsing Experience by smoothly transitioning between archived pages. During this process, the target datetime changes with each link followed; drifting away from the datetime originally selected. When Browsing sparsely-archived pages, this nearly-silent drift can be many years in just a few clicks. We conducted 200,000 acyclic walks of archived pages, following up to 50 links per walk, comparing the results of two target datetime policies. The Sliding Target policy allows the target datetime to change as it does in archive UIs such as the Internet Archive's Wayback Machine. The Sticky Target policy, represented by the Memento API, keeps the target datetime the same throughout the walk. We found that the Sliding Target policy drift increases with the number of walk steps, number of domains visited, and choice (number of links available). However, the Sticky Target policy controls temporal drift, holding it to less than 30 days on average regardless of walk length or number of domains visited. The Sticky Target policy shows some increase as choice increases, but this may be caused by other factors. We conclude that based on walk length, the Sticky Target policy generally produces at least 30 days less drift than the Sliding Target policy.
Evangelos P Markatos - One of the best experts on this subject based on the ideXlab platform.
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minimizing information disclosure to third parties in social login platforms
International Journal of Information Security, 2012Co-Authors: Georgios Kontaxis, Michalis Polychronakis, Evangelos P MarkatosAbstract:Over the past few years, a large and ever increasing number of Web sites have incorporated one or more social login platforms and have encouraged users to log in with their Facebook, Twitter, Google, or other social networking identities. Research results suggest that more than two million Web sites have already adopted Facebook's social login platform, and the number is increasing sharply. Although one might theoretically refrain from such social login features and cross-site interactions, usage statistics show that more than 250 million people might not fully realize the privacy implications of opting-in. To make matters worse, certain Web sites do not offer even the minimum of their functionality unless users meet their demands for information and social interaction. At the same time, in a large number of cases, it is unclear why these sites require all that personal information for their purposes. In this paper, we mitigate this problem by designing and developing a framework for minimum information disclosure in social login interactions with third-party sites. Our example case is Facebook, which combines a very popular single sign-on platform with information-rich social networking profiles. Whenever users want to browse to a Web site that requires authentication or social interaction using a Facebook identity, our system employs, by default, a Facebook session that reveals the minimum amount of information necessary. Users have the option to explicitly elevate that Facebook session in a manner that reveals more or all of the information tied to their social identity. This enables users to disclose the minimum possible amount of personal information during their Browsing Experience on third-party Web sites.
