Browsing Activities Research Articles

Limiting large-scale crawls of social networking sites

Online social networking sites (OSNs) like Facebook and Orkut contain personal data of millions of users. Many OSNs view this data as a valuable asset that is at the core of their business model. Both OSN users and OSNs have strong incentives to restrict large scale crawls of this data. OSN users want to protect their privacy and OSNs their business interest. Traditional defenses against crawlers involve rate- limiting browsing activity per user account. These defense schemes, however, are vulnerable to Sybil attacks, where a crawler creates a large number of fake user accounts. In this paper, we propose Genie, a system that can be deployed by OSN operators to defend against Sybil crawlers. Genie is based on a simple yet powerful insight: the social network itself can be leveraged to defend against Sybil crawlers. We first present Genie's design and then discuss how Genie can limit crawlers while allowing browsing of user profiles by normal users.

Relating E-satisfaction to Behavorial Outcomes: An Empirical Study

Prior work has examined antecedents and behavioral outcomes of satisfaction in an offline setting but relatively little evidence explores whether the findings hold for increasingly important online settings. In addition, prior work has linked determinants of e-satisfaction to stated intentions about referrals, retention and a customer's willingness to pay more but not to stated purchasing or actual browsing behaviors. This paper extends the prior work to explore the antecedents of e-satisfaction, and the relations between e-satisfaction and two new behaviorial outcomes related to an online setting; customers' stated purchasing behavior (i.e. conversion) and actual browsing behavior (i.e. stickiness). Using a sample of 145 predominantly multi-channel retail firms and 683 firm quarters, the paper highlights two main results. First, existing models that examine the antecedents and consequences of satisfaction in the offline setting, also apply to an online setting. Specifically, Web site characteristics and customer service affected overall Web site satisfaction which, in turn, affected retention/referral, conversion, and stickiness. Second, Web site characteristics had a significant impact on all three types of behavioral outcomes, while Web site customer service was a significant driver of only retention/referral outcomes. An important implication of these results is that firms having online channels need to pay careful attention to the selection, design, and maintenance of Web site characteristics to ensure favourable behavorial outcomes. On the other hand, Web site customer service may be a necessary but not sufficient condition to achieving favourable outcomes from online settings.

The Effect of Behavioral Targeting on Trust in E-Commerce

Behavioral targeting is an online marketing method that collects data on the browsing activities of consumers, in order to 'target' more relevant online advertising. It places digital tags in the browsers of web site visitors, using these tags to track and aggregate consumer behavior. Most data is collected anonymously, i.e., not linked to a person's name. However, behavioral targeting does create digital dossiers on consumers that connect browsing activity to a tagged individual. This tagging is largely invisible to consumers, who are not asked to explicitly give consent for this practice. While this is presented as beneficial because it delivers a more personalized e-commerce experience, this paper will argue that behavioral targeting in its current form is damaging to trust in e-commerce. To document this damage, Whitworth's polite software framework will be applied to three case studies of behavioral targeting. Whitworth argues politeness is an important social requirement of software, defining politeness as 'offering the locus of control of a social interaction to another party.' This paper will show that behavioral targeting is impolite, and by using data collected clandestinely it undermines the autonomy of consumers in their online shopping and purchase decisions, thus eroding trust in e-commerce.

Distribution and population patterns of the threatened palm Brahea aculeata in a tropical dry forest in Sonora, Mexico

The use of non-timber forest products (NTFPs) has great potential for the conservation of natural resources and rural development. Palms are important NTFPs, providing numerous products, including leaves. The harvest of palm leaves rarely results in the immediate death of individuals and can be considered one example of the sustainable use of forest resources. However, in most cases basic ecological information, such as distribution and abundance of the species is unknown, as is information on the ecological implications of human impacts, such as leaf harvest and livestock grazing. In the tropical dry forests of northwest Mexico, leaves from the threatened palm Brahea aculeata are harvested for roofing material and represent an important NTFP. In this study, we assessed the distribution and abundance patterns of this species across 52 plots in the tropical dry forest of Sierra de Álamos-Rio Cuchujaqui Reserve (SARCR) in Sonora, Mexico. We also evaluated patterns of leaf harvest and cattle browse intensity on palm populations. We found that B. aculeata density is highly variable across the landscape with a mean (±SE) of 121.7 ± 36.3 ha −1. Results indicate that B. aculeata is primarily distributed near to arroyos and rivers. The highest densities were found in sites with low incidence radiation (<0.06 MJ cm −2) and narrow stream width of arroyos/rivers (<9.5 m). Palm abundance also varied within the plots, and B. aculeata attained its highest densities near to the arroyo edge (first 20 m from the edge), perhaps indicating a microhabitat effect on palm demography. Overall, fewer than 6% of the stems were seedlings. Leaf harvesting and browsing appear to affect demographic vital rates of the species; specifically we found a significant effect of harvesting and browsing activity on the proportion of reproductive active adults. Thus, low levels of seedlings in the populations may be the result of reduced fruit production by adults and higher mortality rates of seedlings due to livestock herbivory. Result from interviews with land owners also indicated that past land use, especially along arroyos might also have important impacts on the observed distribution, low densities and absence of recruitment in some areas. We believe current distribution and abundance of NTFP, such as B. aculeata at SARCR may be a result of combined effects of environmental factors and human impacts. Results from this study will be used to develop appropriate conservation, management and restoration plans of B. aculeata in the area.

What determines an engaging website?: An empirical study of website characteristics and operational performance

With the emergence of a knowledge-based, digital economy, value creation is predicated on the ability to enhance consumer access, engagement, and interactivity. The requirements for successful website features that build on access and interactivity, however, are not in accord with some consumer surveys that indicate dissatisfaction with online transactions. We argue that access and interactivity alone do not necessarily lead to operational performance (page views and duration), but that the relationship is critically influenced by consumer browsing activities and website characteristics. In this paper, we examine two specific characteristics that are hypothesized to be positively related to the operational performance: the extent to which the activity is search-based versus experience-based, and website characteristics that induce consumer engagement. Using data obtained from 177 Korean websites, our results support our hypotheses. Even so, findings also suggest some confounding features of search and browsing activities. Collectively, this study corroborates contemporary views of consumers as actively engaged in the process of value creation.

Conceptual approach for multi-level restructuring of categorized documents in a corpus

In order to improve the browsing activity in a documentary database, we propose a conceptual approach for multi-level restructuring of categorized documents in a corpus. Starting from a manual and static organized corpus, based on the domain ontology, we derive new dynamically generated structures embedded in the static one. We use a conceptual recursive indexing method based on the selection of the minimal number of concepts covering either a document or a subset of documents corresponding to a sub-corpus. Hence, our system provides an additional browsing feature to the user, by dynamically providing the system with a conceptual structure of clusters of documents. For illustration, you may find in the figure an application to Arabic financial news for a particular ontology. Therefore, one finds sub-category under the category . Also, under the category, etc. In parallel with the classical browser system, indexing words, provided for each level, give the user more details about the file&apos;s content, as well as the category content, before further exploration. Our approach improves human-computer interaction by decreasing the browsing time. Assessment of the proposed method proves that combining manual documents categorizations, with the automatic feature generations, gives a flexible and effective structured browsing interface to the users. Finally, low-level features help for incrementally placing new documents in the right category, by using suitable supervised classification methods.

Incorporating web browsing activities into anchor texts for web search

Anchor texts complement Web page content and have been used extensively in commercial Web search engines. Existing methods for anchor text weighting rely on the hyperlink information which is created by page content editors. Since anchor texts are created to help user browse the Web, browsing behavior of Web users may also provide useful or complementary information for anchor text weighting. In this paper, we discuss the possibility and effectiveness of incorporating browsing activities of Web users into anchor texts for Web search. We first make an analysis on the effectiveness of anchor texts with browsing activities. And then we propose two new anchor models which incorporate browsing activities. To deal with the data sparseness problem of user-clicked anchor texts, two features of user's browsing behavior are explored and analyzed. Based on these features, a smoothing method for the new anchor models is proposed. Experimental results show that by incorporating browsing activities the new anchor models outperform the state-of-art anchor models which use only the hyperlink information. This study demonstrates the benefits of Web browsing activities to affect anchor text weighting.

A Semantic Web Approach for Improving Ranking Model of Web Document

Ranking models are used by Web search engines to answer user queries based on key words. Traditionally ranking models are based on a static snapshot of the Web graph, which is basically the link structure of the Web documents. The visitor's browsing activities is directly related to importance of the document. However in this traditional static model the document importance on account of interactive browsing is neglected. Thus this model lacks the ability of taking advantage of user interaction for document ranking. In this paper we propose a model based on semantic web to improve the local ranking of the Web documents. This model works on Ant Colony algorithm to enable the Web servers to interact with Web surfers and thus improve the local ranking of Web documents. The local ranking then can be used to generate the global Web ranking.

패션상품 브라우징 유인요소와 저해요소에 관한 질적 연구

Shopping is the activity not only purchasing goods/services but also pursuing the emotional satisfaction. Browsing can be defined as shopping behavior looking around the store without purchasing intention. Through the browsing activity, consumers are able to collect the information and be ready for the possible purchases while marketers have an opportunity to inform consumers of products/ stores/ brands. The more browsing activity, the more stimuli for buying, the more unplanned/ impulse buying. Therefore, this is the time that consumer's browsing activity is getting importance in the area of fashion marketing. The purpose of this study was to examine attracting and hindering factors related to browsing activity especially for purchase of fashion items, using a qualitative research method. An in-depth interview was conducted with 10 female shoppers ranged age 21-50. Included in the questions were consumer's opinions about VMD, convenience, traffic, salesman's attitude, companions, prices, sizes and fitting arrangement. The results of this study provide fashion store managers with the detailed and practical information to draw the consumers in the store.

Application of salesman-like recommendation system in 3G mobile phone online shopping decision support

The rapid growth of e-commerce has confronted both enterprises and consumers with a new situation. Whereas companies are finding it harder to survive, consumers are unable to effectively select the products that really to meet their needs. To reduce the product overload of Internet shoppers, a variety of recommendation techniques that track previous actions of groups of consumers to make personalized recommendations have been developed and applied. Current personalized recommendation systems suffer from the need to analyze large sets of consumer data, or data for numerous consumers. However, even within a single group, consumer preferences may differ, and individual preferences may also change with circumstances. Additionally, the consumer product knowledge influences their browsing actions. To orient Web-visitors on how to become consumers, a salesman-like recommendation technology was developed based on visitor product preference index, which comprises of their product knowledge and browsing actions in scene. A prototype system for use with high-technology product, 3G phones, was developed to test the effectiveness of the recommendation technology. Through a test of 250 objectives, the results show that the recommendation deviation level can be reduced to 0.49, and exact fit with visitor favor products can reach 60.8%, showing that the proposed model can achieve recommendation effectiveness.

An examination of consumer browsing behaviors

PurposeBrowsing is a common consumer behavior, but it has not been researched extensively. The aim of this paper is to fill some of the gaps in the research.Design/methodology/approachDrawing on literature from different areas, consumers' browsing experiences, browsing patterns, and factors influencing browsing activities are empirically examined. A combination of interviews and shopping trips with informants to examine the issues are used.FindingsThe results show that browsing serves both functional and recreational purposes. Consumers vary by the degree to which they browse functionally or recreationally. Browsing behaviors are influenced by both consumer characteristics and the retail environment. Browsing is a powerful consumer information acquisition activity and has both desired and undesired consequences for consumer purchases. Consumers use various strategies to cope with the undesired consequences.Practical implicationsExploration of browsing patterns and factors influencing these patterns suggests important managerial implications for enhancing desirable browsing and reducing unnecessary browsing.Originality/valueThe conceptualization and findings of this research contribute to two areas of research: consumer information search and consumer shopping behaviors in retail environments. An examination of the role of browsing offers an empirical extension to the information acquisition framework.

Cross-shelf variation in browsing intensity on the Great Barrier Reef

Herbivory is widely accepted as a key process determining the structure and resilience of coral reefs, with regional reductions in herbivores often being related to shifts from dominance by coral to leathery macroalgae. The removal of leathery macroalgae may therefore be viewed as a critical process on coral reefs. However, few studies have examined this process beyond a within-reef scale. Here, browsing activity was examined across the entire Great Barrier Reef shelf using bioassays of the leathery macroalga Sargassum to directly quantify algal removal. The assays revealed marked cross-shelf variation in browsing intensity, with the highest rates recorded on mid-shelf reefs (55.2–79.9% day-1) and decreasing significantly on inner- (10.8–17.0% day-1) and outer-shelf (10.1–10.4% day-1) reefs. Surprisingly, the variation in browsing intensity was not directly related to estimates of macroalgal browser biomass; rather, it appears to be shaped primarily by the local environment and behaviour of the component species. Removal rates across the inner- and mid-shelf reefs appear to be related to the attractiveness of the assays relative to the resident algal communities. Controlling for the influence of the resident algal communities revealed a positive relationship between removal rates and the biomass of a single macroalgal browsing species, Naso unicornis. In contrast, the low removal rates on the outer-shelf reefs displayed no relationship to algal or herbivore communities and appeared to reflect a negative behavioural response by the resident fishes to a novel, or unfamiliar, alga. These findings not only highlight the complexities of the relationship between fish presence and ecological function, but also the value of examining ecological processes across broader spatial scales.

Behavioral Targeting: A Case Study of Consumer Tracking on Levis.com

Behavioral targeting is an online marketing method that collects data on the browsing activities of consumers, in order to target more relevant online advertising. It places digital tags in the browsers of web site visitors, using these tags to track and aggregate consumer behavior. The vast majority of data is collected anonymously, i.e., not linked to a person‟s name. However, behavioral targeting does create digital dossiers on consumers with the aim of connecting browsing activity to a tagged individual. This tagging is largely invisible to consumers, who are not asked to explicitly give consent for this practice. By using data collected clandestinely, behavioral targeting undermines the autonomy of consumers in their online shopping and purchase decisions. In order to illustrate the nature of consumer tracking, a case study was conducted that examined behavioral targeting within Levis.com, the e-commerce site for the Levis clothing line. The results show the Levis web site loads a total of nine tracking tags that link to eight third party companies, none of which are acknowledged in the Levis privacy policy. Behavioral targeting, by camouflaging the tracking of consumers, can damage the perceived trustworthiness of an e-commerce site or the actor it represents. The risks behavioral targeting presents to trust within e-commerce are discussed, leading to recommendations to reestablish consumer control over behavioral targeting methods.

Google’s Ad Preference Manager: One Small Step for Google, One Giant Leap for Privacy

Google’s new “Interest Based Advertising” (IBA) program represents the company’s first foray into what is generally called “Online Behavioral Advertising”: In order to deliver more relevant advertising, Google will begin tailoring ads delivered through AdSense on the Google Content Network and YouTube.com, based on a profile of each user’s interests created by tracking their browsing activity across sites that use AdSense - but not search queries or other user information. Google is sure to be attacked for crossing a “line in the sand” drawn by some privacy advocates between contextual and behavioral advertising, but those whose first priority is advancing consumer privacy should applaud Google for excluding sensitive categories and for putting the new Ad Preference Manager, with its persistent opt-out plug-in, at the core of the company’s new IBA program.It’s no accident that Google is now leading the pack of third party ad networks by developing innovative solutions that respect consumer privacy. Google risks alienating some advertisers and publishers with its bold empowerment of users, but was willing to take those risks because of its incentives as a consumer-facing company and able to do so because of its leadership in the marketplace. Uncomfortable as this reality may be for those who fret about antitrust issues and indeed for Google itself, the simple reality is that sometimes it takes “big dogs” to make self-regulatory systems truly effective.Google’s approach is precisely the kind of innovation that would be discouraged by pre-emptive government regulation. Worse, those who would freeze privacy protection in place would also freeze in place much of the Internet itself, precluding development of new business models that would compete with Google, allaying concerns about competition and benefiting consumers.

Exploitation of semantic relationships and hierarchical data structures to support a user in his annotation and browsing activities in folksonomies

In this paper we present a new approach to supporting users to annotate and browse resources referred by a folksonomy. Our approach is characterized by the following novelties: (i) it proposes a probabilistic technique to quickly and accurately determine the similarity and the generalization degrees of two tags; (ii) it proposes two hierarchical structures and two related algorithms to arrange groups of semantically related tags in a hierarchy; this allows users to visualize tags of their interests according to desired semantic granularities and, then, helps them to find those tags best expressing their information needs. In this paper we first illustrate the technical characteristics of our approach; then we describe various experiments allowing its performance to be tested; finally, we compare it with other related approaches already proposed in the literature.

Automated Semantic Analysis of Schematic Data

Content in numerous Web data sources, designed primarily for human consumption, are not directly amenable to machine processing. Automated semantic analysis of such content facilitates their transformation into machine-processable and richly structured semantically annotated data. This paper describes a learning-based technique for semantic analysis of schematic data which are characterized by being template-generated from backend databases. Starting with a seed set of hand-labeled instances of semantic concepts in a set of Web pages, the technique learns statistical models of these concepts using light-weight content features. These models direct the annotation of diverse Web pages possessing similar content semantics. The principles behind the technique find application in information retrieval and extraction problems. Focused Web browsing activities require only selective fragments of particular Web pages but are often performed using bookmarks which fetch the contents of the entire page. This results in information overload for users of constrained interaction modality devices such as small-screen handheld devices. Fine-grained information extraction from Web pages, which are typically performed using page specific and syntactic expressions known as wrappers, suffer from lack of scalability and robustness. We report on the application of our technique in developing semantic bookmarks for retrieving targeted browsing content and semantic wrappers for robust and scalable information extraction from Web pages sharing a semantic domain.

Linkages between wolf presence and aspen recruitment in the Gallatin elk winter range of southwestern Montana, USA

The decline of aspen (Populus tremuloides) in Yellowstone National Park (YNP) has been attributed to conifer encroachment, climatic influences, ungulate herbivory and more recently, a lack of grey wolves (Canis lupus) via trophic cascades. The current study explores evidence of a trophic cascade on aspen decline. We conducted the study in the Gallatin elk winter range of YNP, an area where aspen have not previously been studied. We approximated aspen origination dates from an age–diameter relationship to examine potential correlations between wolf presence and absence, elk (Cervus elaphus) herbivory and aspen recruitment. A comparative analysis was also conducted between the aspen data collected in the winter range and aspen data collected within two elk exclosures. Within the elk exclosures, aspen successfully recruited since fence construction in the 1940s. Outside the exclosures, aspen recruitment into mature stems began to decline in the 1920s (during wolf extirpation), completely ceased after the 1950s and has only been observed since the 1990s (post-wolf reintroduction). While a host of interacting biophysical factors may influence aspen recruitment and growth, the correlative results between aspen recruitment and historical elk browsing activities, coincident with the presence and absence of wolves, are consistent with a top–down trophic cascade.

Using Google Analytics for Improving Library Website Content and Design: A Case Study

Google Analytics is a free web analytics solution that provides webmasters with insightful information about how visitors find and interact with their websites. In this case study, we have experimented in using Google Analytics to analyze two of our websites: The Rutgers-Newark Law Library main website and The New Jersey Digital Legal Library website. It was used to monitor our visitors' browsing activities and viewing behaviors for three months. Based on our findings from Google Analytics reports, we have redesigned our website. Subsequent data collected by Google Analytics have confirmed that our new design better fits the information needs of our visitors and librarians. Google Analytics is very powerful and can be used for almost any website. We believe that other libraries will benefit from using Google Analytics as well. Limitations of Google Analytics are also discussed based on our experience with it.

Web usage mining with intentional browsing data

Many researches have developed Web usage mining (WUM) algorithms utilizing Web log records in order to discover useful knowledge to be used in supporting business applications and decision making. The quality of WUM in knowledge discovery, however, depends on the algorithm as well as on the data. This research explores a new data source called intentional browsing data (IBD) for potentially improving the effectiveness of WUM applications. IBD is a category of online browsing actions, such as ''copy'', ''scroll'', or ''save as,'' and is not recorded in Web log files. Consequently, the research aims to build a basic understanding of IBD which will lead to its easy adoption in WUM research and practice. Specifically, this paper formally defines IBD and clarifies its relationships with other browsing data via a proposed taxonomy. In order to make IBD available like Web log files, an online data collection mechanism for capturing IBD is also proposed and discussed. The potential benefits of IBD can be justified in terms of its enhancing and complementary effectiveness, which are illustrated by the rule implications of Web transaction mining algorithm for an EC application. Introducing IBD opens up the scope of WUM research and applications in knowledge discovery.

Behaviour of goats, sheep and cattle on natural pasture in the sub-humid zone of West Africa

The behaviour of sheep, goats and cattle on a shrub and tree savannah in the sub-humid zone of West Africa was studied during the dry (February to May), rainy (June to September) and cool season (October to January). Two mature females per animal species were followed by two observers during 3 days per month and behaviour activities were recorded every 15 min of the daily grazing time. When browsing, the plant name, plant part and plant height reached during prehension were recorded. The distance travelled and the grazing circuits were recorded with a step counter and a Geographic Position System device. The knowledge of farmers concerning appreciated browse species relative to the browse species consumed by animals in the area was also investigated. During the dry season sheep, goats and cattle spent around 25% of their time browsing and 20%, 16% and 31%, respectively, of their time grazing. During the cool season, goats (17%) browsed more than sheep (7%) and cattle (5%) (P < 0.05). During the rainy season, sheep browsed 20% of the time while cattle spent only 7% of their time browsing, while goats were tied, with no opportunity for browsing. Browsing leaves was the most important part of the browsing activity. During the cool season, browsing height was the same (1.0 m) for cattle and goats, but lower for sheep (0.6 m) (P < 0.05). In the dry and cool season, sheep and goats walked shorter distances than cattle. The plant species with the highest frequency of consumption were Acacia dudgeoni Craib, Ficus gnaphalocarpa (Miq.) A. Rich, Dioscorea togoensis Knuth, Cordia myxa L., and Manguifera indica L. for sheep and goats and Afzelia africana Sm., Kaya senegalensis (Desv.) A. Juss, Pterocarpus erinaceus Poir. and Dicrostachys cinerea (L.) Wight and Arn. for cattle. Species with a high frequency of citation by farmers were A. africana (92%), K. senegalensis (88%), P. erinaceus (86%), Faidherbia albida A. Chevalier (80%), A. dudgeoni (70%) and F. gnaphalocarpa (69%). In conclusion, browse species make an important contribution to the diet of ruminant animals in the sub-humid zone and farmers are familiar with the species consumed by ruminant animals.