Navigation Patterns Research Articles

A Reinforcement Learning Based Model for Adaptive Service Quality Management in E-Commerce Websites

Providing high-quality service to all users is a difficult and inefficient strategy for e-commerce providers, especially when Web servers experience overload conditions that cause increased response time and request rejections, leading to user frustration and reduced revenue. In an e-commerce system, customer Web sessions have differing values for service providers. These tend to: give preference to customer Web sessions that are likely to bring more profit by providing better service quality. This paper proposes a reinforcement-learning based adaptive e-commerce system model that adapts the service quality level for different Web sessions within the customer’s navigation in order to maximize total profit. The e-commerce system is considered as an electronic supply chain which includes a network of basic e- providers used to supply e-commerce services for end customers. The learner agent noted as e-commerce supply chain manager (ECSCM) agent allocates a service quality level to the customer’s request based on his/her navigation pattern in the e-commerce Website and selects an optimized combination of service providers to respond to the customer’s request. To evaluate the proposed model, a multi agent framework composed of three agent types, the ECSCM agent, customer agent (buyer/browser) and service provider agent, is employed. Experimental results show that the proposed model improves total profits through cost reduction and revenue enhancement simultaneously and encourages customers to purchase from the Website through service quality adaptation.

Uasisi: a modular and adaptable wearable system to assist the visually impaired

We present the design and early-stage implementation of Uasisi, a system to assist the visually impaired in navigating physical spaces. In its simplest form, a single wearable device can assist the user by sensing the proximity of objects in the environment and providing vibratory feedback. More devices can be added in a modular way to form a wireless body area network, and this can, in turn, be connected to a cloud infrastructure where data related to the navigational patterns of the user can be analyzed and help in making further predictions. Our system can also adapt to form part of an augmented environment where smart objects communicate and cooperate with each other to provide a more rich and complex navigation experience for the user. We show a series of experiments where various configurations of the system are tested with users who can not see and must navigate spaces previously unknown to them.

Social and Spatial Precursors to Innovation: The Diversity Advantage of the Creative Fringe

Innovation spaces and hubs are increasing in numbers internationally. Entrepreneurs and start-up founders who use these spaces and hubs are often unaware of being inside an echo chamber, i.e. a filter bubble they share with only like-minded people who have similar ideas and approaches to innovation. Digital technologies that use algorithms can aggravate these echo chambers by filtering towards improved personalised experience and preferences. Yet, social inclusion fosters diverse ideas and creativity, hence, has a positive impact on innovation. We studied the social navigation patterns of entrepreneurs and start-up founders, and their awareness and opinion about homogeneity in innovation spaces. This data informed the design of a tool to escape their echo chambers. The tool gives its users the opportunity to discover networks and innovation spaces that are at the creative fringe, that is, marginalised from mainstream spaces and hubs for creativity and innovation. Our findings show that users of innovation spaces often find themselves surrounded by like-minded people. Further, our study participants welcomed the ability to identify fringe spaces in order to discover and access more diverse people and ideas. Our approach seeks to unlock the diversity advantage of the creative fringe for the purpose of creativity and innovation.

Taxonomical Classification of Web Usage Mining Applications and its Ontological Representation

Web usage mining is used to find out fascinating consumer navigation patterns which can be applied to a lot of real-world problems, such as enriching websites or pages, generating newly topic or product recommendations and consumer behavior studies, etc. In this paper, an attempt has been made to provide a taxonomical classification of web usage mining applications with two levels of hierarchy. Further, the ontology for various categories of the web usage mining applications has been developed and to prove the completeness of proposed taxonomy, a rigorous case study has been performed. The comparative study with other existing classifications of web usage mining applications has also been performed.

Using Mapping to Evaluate Community Mobility and Participation While Aging in Place

Abstract Date Presented 4/19/2018 This study explored the utility of global positioning system mapping methods to understand participation in older adults aging in place. Community navigation patterns, social factors, and well-being disparities were examined in relation to how occupations were carried out in a community context. Primary Author and Speaker: Kendra Heatwole Shank Additional Authors and Speakers: Echo Presgraves

Geospatial Mapping of Late-Life Couplehood: Dimensions of Joint Participation.

For older adults aging in place, community mobility affects a constellation of interconnected occupations and can become a problematic aspect of the person-place relationship. The purpose of this research was to examine an older couple's mutually negotiated change in their community mobility and navigation patterns. Spatial data (using global positioning system [GPS] trackers), maps, activity logs, interviews, and well-being measures were collected longitudinally for both members of a long-married community-dwelling couple. Analyses showed changing patterns of occupational engagement and declining navigation and function over time, as well as three dimensions of joint navigation (intersection of health and abilities, perpetuation of long-term roles through participation, and an orientation toward future potentialities). Findings suggest that joint community navigation is multidimensional and may buffer individual functional losses as well as maximize perception of and performance in meaningful activities. This study also demonstrates the utility of mapping methods to better understand occupation for community-dwelling populations.

Investigating the relationship between task complexity, cognitive ability and disorientation in hypertext navigation

Users sometimes face a common and serious problem called disorientation, which is defined as the feeling of being lost in a web-based environment. It is important to determine the reasons for disorientation in order to make the students navigate more efficiently in these environments. The aim of this study is to investigate the relationship between navigation patterns, disorientation level and students’ cognitive ability. For this purpose, an experimental research was designed and a 223-page Wiki environment was developed as a network structured hypertext environment. Sixty-nine university students’ navigation processes including 6.880-row log data were recorded in order to measure their disorientation scores. We found that task complexity negatively affected disorientation scores. Disorientation scores decreased as the tasks became more difficult. Possible causes of the results are discussed. Keywords: Disorientation, cognitive ability, hypermedia navigation, task complexity.

Navigating Print and Digital Sources: Students’ Selection, Use, and Integration of Multiple Sources Across Mediums

Academic tasks frequently require students to effectively process multiple sources across print and digital mediums. Yet, studies of multiple source use have almost exclusively confined examinations to a single medium. In the present study, undergraduate students (n = 50) wore a head-mounted video camera while developing a PowerPoint presentation based on print and digital sources. Students more frequently selected certain digital sources and incorporated more digital sources into their presentations, but students spent more time using and transforming printed sources. However, differences by medium became nonsignificant when controlling for topic knowledge, and topic knowledge moderated some relations. Sequential transition analyses revealed that students with lower versus higher topic knowledge exhibited different patterns of navigation within and across mediums.

Investigating the relationship between task complexity, cognitive ability and disorientation in hypertext navigation

Users sometimes face a common and serious problem called disorientation, which is defined as the feeling of being lost in aweb-based environment. It is important to determine the reasons for disorientation in order to make the students navigatemore efficiently in these environments. The aim of this study is to investigate the relationship between navigation patterns,disorientation level and students’ cognitive ability. For this purpose, an experimental research was designed and a 223-pageWiki environment was developed as a network structured hypertext environment. Sixty-nine university students’ navigationprocesses including 6.880-row log data were recorded in order to measure their disorientation scores. We found that taskcomplexity negatively affected disorientation scores. Disorientation scores decreased as the tasks became more difficult.Possible causes of the results are discussed.Keywords: Disorientation, cognitive ability, hypermedia navigation, task complexity.

Expressive Languages for Querying the Semantic Web

The problem of querying RDF data is a central issue for the development of the Semantic Web. The query language SPARQL has become the standard language for querying RDF since its W3C standardization in 2008. However, the 2008 version of this language missed some important functionalities: reasoning capabilities to deal with RDFS and OWL vocabularies, navigational capabilities to exploit the graph structure of RDF data, and a general form of recursion much needed to express some natural queries. To overcome these limitations, a new version of SPARQL, called SPARQL 1.1, was released in 2013, which includes entailment regimes for RDFS and OWL vocabularies, and a mechanism to express navigation patterns through regular expressions. Unfortunately, there are a number of useful navigation patterns that cannot be expressed in SPARQL 1.1, and the language lacks a general mechanism to express recursive queries. To the best of our knowledge, no efficient RDF query language that combines the above functionalities is known. It is the aim of this work to fill this gap. To this end, we focus on a core fragment of the OWL 2 QL profile of OWL 2 and show that every SPARQL query enriched with the above features can be naturally translated into a query expressed in a language that is based on an extension of Datalog, which allows for value invention and stratified negation. However, the query evaluation problem for this language is highly intractable, which is not surprising since it is expressive enough to encode some inherently hard queries. We identify a natural fragment of it, and we show it to be tractable and powerful enough to define SPARQL queries enhanced with the desired functionalities.

Stress-based navigation for microscopic robots in viscous fluids

Objects moving in fluids experience patterns of stress on their surfaces determined by their motion and the geometry of nearby boundaries. Fish and underwater robots can use these patterns for navigation. This paper extends this stress-based navigation to microscopic robots in tiny vessels, where robots can exploit the physics of fluids at low Reynolds number. This applies, for instance, in vessels with sizes and flow speeds comparable to those of capillaries in biological tissues. We describe how a robot can use simple computations to estimate its motion, orientation and distance to nearby vessel walls from fluid-induced stresses on its surface. Numerically evaluating these estimates for a variety of vessel sizes and robot positions shows they are most accurate when robots are close to vessel walls.

Analyzing and Predicting User Navigation Pattern from Weblogs using Modified Classification Algorithm

<p>A Weblogs contains the history of User Navigation Pattern while user accessing the websites. The user navigation pattern can be analyzed based on the previous user navigation that is stored in weblog. The weblog comprises of various entries like IP address, status code and number of bytes transferred, categories and time stamp. The user interest can be classified based on categories and attributes and it is helpful in identifying user behavior. The aim of the research is to identifying the interested user behavior and not interested user behavior based on classification. The process of identifying user interest, it consists of Modified Span Algorithm and Personalization Algorithm based on the classification algorithm user prediction can be analyzed. The research work explores to analyze user prediction behavior based on user personalization that is captured from weblogs. </p>

Navigation Patterns and Scent Marking: Underappreciated Contributors to Hippocampal and Entorhinal Spatial Representations?

According to the currently prevailing theory, hippocampal formation constructs and maintains cognitive spatial maps. Most of the experimental evidence for this theory comes from the studies on navigation in laboratory rats and mice, typically male animals. While these animals exhibit a rich repertoire of behaviors associated with navigation, including locomotion, head movements, whisking, sniffing, raring and scent marking, the contribution of these behavioral patterns to the hippocampal spatially-selective activity has not been sufficiently studied. Instead, many publications have considered animal position in space as the major variable that affects the firing of hippocampal place cells and entorhinal grid cells. Here we argue that future work should focus on a more detailed examination of different behaviors exhibited during navigation to better understand the mechanism of spatial tuning in hippocampal neurons. As an inquiry in this direction, we have analyzed data from two datasets, shared online, containing recordings from rats navigating in square and round arenas. Our analyses revealed patchy navigation patterns, evident from the spatial maps of animal position, velocity and acceleration. Moreover, grid cells available in the datasets exhibited similar periodicity as the navigation parameters. These findings indicate that activity of grid cells could affect navigation parameters and/or vice versa. Additionally, we speculate that scent marks left by navigating animals could contribute to neuronal responses while rats and mice sniff their environment; the act of sniffing could modulate neuronal discharges even in virtual visual environments. Accordingly, we propose that future experiments should contain additional controls for navigation patterns, whisking, sniffing and maps composed of scent marks.

Mining association rules for admission control and service differentiation in e‐commerce applications

Workload demands in e‐commerce applications are very dynamic in nature, therefore it is essential for internet service providers to manage server resources effectively to maximize total revenue in server overloading situations. In this paper, a data mining technique is applied to a typical e‐commerce application model for identification of composite association rules that capture user navigation patterns. Two algorithms are then developed based on the derived rules for admission control, service differentiation, and priority scheduling. Our approach takes the following aspects into consideration: (a) only final purchase requests result in company revenue; (b) any other request can potentially lead to final purchase, depending upon the likelihood of the navigation sequence that starts from current request and leads to final purchase; (c) service differentiation and priority assignment are based on aggregated confidence and average support of the composite association rules. As identification of composite association rules and computation of confidence and support of the rules can be pre‐computed offline, the proposed approach incurs minimum performance overheads. The evaluation results suggest that the proposed approach is effective in terms of request management for revenue maximization.This article is categorized under: Application Areas > Science and Technology Algorithmic Development > Association Rules Algorithmic Development > Web Mining

Reusable Software Usability Specifications for mHealth Applications.

One of the key factors for the adoption of mobile technologies, and in particular of mobile health applications, is usability. A usable application will be easier to use and understand by users, and will improve user's interaction with it. This paper proposes a software requirements catalog for usable mobile health applications, which can be used for the development of new applications, or the evaluation of existing ones. The catalog is based on the main identified sources in literature on usability and mobile health applications. Our catalog was organized according to the ISO/IEC/IEEE 29148:2011 standard and follows the SIREN methodology to create reusable catalogs. The applicability of the catalog was verified by the creation of an audit method, which was used to perform the evaluation of a real app, S Health, application created by Samsung Electronics Co. The usability requirements catalog, along with the audit method, identified several usability flaws on the evaluated app, which scored 83%. Some flaws were detected in the app related to the navigation pattern. Some more issues related to the startup experience, empty screens or writing style were also found. The way a user navigates through an application improves or deteriorates user's experience with the application. We proposed a reusable usability catalog and an audit method. This proposal was used to evaluate a mobile health application. An audit report was created with the usability issues identified on the evaluated application.

Elimination of Backward Browsing using Decomposition and Compression for Efficient Navigation Prediction

Analysing the user's browsing patterns stored in weblog file can help in providing the personalised environment, improving website structure and recommending the suitable navigation pattern. While browsing the web, the user navigates in a forward direction following the web topology, results in the session having correlated web pages. Backward navigation takes place when the user returns to the previously visited page. This traversal results in increased session length, complexity and reduction in the prediction accuracy. The frequent backward movement also infers that the web community is not well structured. Therefore, to discover the meaningful browsing pattern and improve the website structure, it is essential to filter the repeated web pages from the session. This paper proposes two novel backward elimination techniques: decomposed backward browsing (BBDcom) and compressed backward browsing (BBCom). BBDcom reduces the length of a session using decomposition. It can restore the original session without losing data. BBCom compresses the session length by eliminating web page(s) lying in between the redundant web pages. The experimental result shows that proposed techniques improve the prediction accuracy and reduces the state-space complexity.

Homes or Just Houses: The Housing Needs of Female-Headed Households in Egypt

With the drastic rise in divorce rates in Egypt in the last few decades, targeting female-headed households as new housing segment is becoming increasingly crucial. Female-headed households are categorized as part of the housing vulnerable groups supported by the government. The housing needs, preferences and the market navigation patterns of this group are the study matter of this paper. While this group shares similarities in the housing needs with the two-parent families there are defined differences in the housing presences and market navigation patterns of the two groups. The paper also sheds the light on how the social characteristics of the female-headed households determine the housing problems they face with the current market offerings. Then, it outlines a typology of the housing preferred by the female heads, with the aim of generating recommendations that would help create more inclusive and satisfactory housing market offerings tailored for them. The proximity of the workplace to the housing unit in addition to the presence of an active community center within the neighborhoods was on top of their housing demands.

Elimination of backward browsing using decomposition and compression for efficient navigation prediction

Analysing the user's browsing patterns stored in weblog file can help in providing the personalised environment, improving website structure and recommending the suitable navigation pattern. While browsing the web, the user navigates in a forward direction following the web topology, results in the session having correlated web pages. Backward navigation takes place when the user returns to the previously visited page. This traversal results in increased session length, complexity and reduction in the prediction accuracy. The frequent backward movement also infers that the web community is not well structured. Therefore, to discover the meaningful browsing pattern and improve the website structure, it is essential to filter the repeated web pages from the session. This paper proposes two novel backward elimination techniques: decomposed backward browsing (BBDcom) and compressed backward browsing (BBCom). BBDcom reduces the length of a session using decomposition. It can restore the original session without losing data. BBCom compresses the session length by eliminating web page(s) lying in between the redundant web pages. The experimental result shows that proposed techniques improve the prediction accuracy and reduces the state-space complexity.

Deriving User Interest by mining user navigation patterns

Deriving User Interest by mining user navigation patterns

Navigation and Comprehension of Digital Expository Texts: Hypertext Structure, Previous Domain Knowledge, and Working Memory Capacity

Introduction. In contemporary information societies, reading digital text has become pervasive. One of the most distinctive features of digital texts is their internal connections via hyperlinks, resulting in non-linear hypertexts. Hypertext structure and previous knowledge affect navigation and comprehension of digital expository texts. From the Cognitive Load framework, working memory capacity would have a role in supporting decisions about navigation, and in situation model construction for comprehension. The present study assessed text structure, previous domain knowledge, and working memory capacity effects on comprehension and navigation of digital expository texts.Method. Fifty-six participants completed a working memory capacity measure, read four digital texts and answered questions about them. Hyperext structure (hierarchical vs. network) and previous thematic knowledge (high vs. low) were manipulated in a within-subjects design. Navigation behavior was indexed taking into account total time spent on each text, total number of pages per text, number of returns to the initial page, and number of nonlinear links clicked.Results. High previous knowledge, and high working memory capacity, led to better comprehension. Participants who read under network interfaces followed less structured navigation paths than those who read hierarchically organized interfaces. On the other hand, high previous knowledge texts led to more pages visited, more non-linear jumps in reading, and more returns to the overview in the Home page in the network condition. Also, total time spent on each text was longer for high working memory participants reading high previous knowledge texts.Discussion. Overall, this pattern of results adds to the literature about the beneficial effects promoted by hierarchical interfaces and concept maps; and the disorientation effects network hypertexts have for low domain knowledge students. On the other hand, given good previous knowledge and high working memory, a more variable pattern of navigation would help readers engage in more active reading processes.