Website Log Research Articles

Supporting informed decision making online in 20 minutes: an observational web-log study of a PSA test decision aid.

BackgroundWeb-based decision aids are known to have an effect on knowledge, attitude, and behavior; important components of informed decision making. We know what decision aids achieve in randomized controlled trials (RCTs), but we still know very little about how they are used and how this relates to the informed decision making outcome measures.ObjectiveTo examine men's use of an online decision aid for prostate cancer screening using website transaction log files (web-logs), and to examine associations between usage and components of informed decision making.MethodsWe conducted an observational web-log analysis of users of an online decision aid, Prosdex. Men between 50 and 75 years of age were recruited for an associated RCT from 26 general practices across South Wales, United Kingdom. Men allocated to one arm of the RCT were included in the current study. Time and usage data were derived from website log files. Components of informed decision making were measured by an online questionnaire.ResultsAvailable for analysis were 82 web-logs. Overall, there was large variation in the use of Prosdex. The mean total time spent on the site was 20 minutes. The mean number of pages accessed was 32 (SD 21) out of a possible 60 pages. Significant associations were found between increased usage and increased knowledge (Spearman rank correlation [ρ] = 0.69, P < .01), between increased usage and less favorable attitude towards PSA testing (ρ = -0.52, P < .01), and between increased usage and reduced intention to undergo PSA testing (ρ = -0.44, P < .01). A bimodal distribution identified two types of user: low access and high access users.ConclusionsIncreased usage of Prosdex leads to more informed decision making, the key aim of the UK Prostate Cancer Risk Management Programme. However, developers realistically have roughly 20 minutes to provide useful information that will support informed decision making when the patient uses a web-based interface. Future decision aids need to be developed with this limitation in mind. We recommend that web-log analysis should be an integral part of online decision aid development and analysis.Trial RegistrationISRCTN48473735; http://www.controlled-trials.com/ISRCTN48473735 (Archived by WebCite at http://www.webcitation.org/5pqeF89tS)

Improving Web Site Performance Using Commercially Available Analytical Tools

It is easy to accurately measure web site usage and to quantify key parameters such as page views, site visits, and more complex variables using commercially available tools that analyze web site log files and search engine use. This information can be used strategically to guide the design or redesign of a web site (templates, look-and-feel, and navigation infrastructure) to improve overall usability. The data can also be used tactically to assess the popularity and use of new pages and modules that are added and to rectify problems that surface. This paper describes software tools used to: (1) inventory search terms that lead to available content; (2) propose synonyms for commonly used search terms; (3) evaluate the effectiveness of calls to action; (4) conduct path analyses to targeted content. The American Academy of Orthopaedic Surgeons (AAOS) uses SurfRay's Behavior Tracking software (Santa Clara CA, USA, and Copenhagen, Denmark) to capture and archive the search terms that have been entered into the site's Google Mini search engine. The AAOS also uses Unica's NetInsight program to analyze its web site log files. These tools provide the AAOS with information that quantifies how well its web sites are operating and insights for making improvements to them. Although it is easy to quantify many aspects of an association's web presence, it also takes human involvement to analyze the results and then recommend changes. Without a dedicated resource to do this, the work often is accomplished only sporadically and on an ad hoc basis.

Learning Nonsparse Kernels by Self-Organizing Maps for Structured Data

The development of neural network (NN) models able to encode structured input, and the more recent definition of kernels for structures, makes it possible to directly apply machine learning approaches to generic structured data. However, the effectiveness of a kernel can depend on its sparsity with respect to a specific data set. In fact, the accuracy of a kernel method typically reduces as the kernel sparsity increases. The sparsity problem is particularly common in structured domains involving discrete variables which may take on many different values. In this paper, we explore this issue on two well-known kernels for trees, and propose to face it by recurring to self-organizing maps (SOMs) for structures. Specifically, we show that a suitable combination of the two approaches, obtained by defining a new class of kernels based on the activation map of a SOM for structures, can be effective in avoiding the sparsity problem and results in a system that can be significantly more accurate for categorization tasks on structured data. The effectiveness of the proposed approach is demonstrated experimentally on two relatively large corpora of XML formatted data and a data set of user sessions extracted from website logs.

A web page usage prediction scheme using sequence indexing and clustering techniques

In this paper we consider the problem of web page usage prediction in a web site by modeling users’ navigation history and web page content with weighted suffix trees. This user’s navigation prediction can be exploited either in an on-line recommendation system in a web site or in a web page cache system. The method proposed has the advantage that it demands a constant amount of computational effort per one user’s action and consumes a relatively small amount of extra memory space. These features make the method ideal for an on-line working environment. Finally, we have performed an evaluation of the proposed scheme with experiments on various web site log files and web pages and we have found that its quality performance is fairly well and in many cases an outperforming one.

Exploring website log data with coordinated dimension hierarchies and network pivots

Many interfaces exist for exploring multi-dimensional data, but most are not suitable for OLAP as they do not support aggregation and selection via dimension hierarchies. We introduce an interface for exploring OLAP data via coordinated dimension hierarchies and network views. Three dimension coordinations are identified; progressive, global and result only, for filtering and presenting data. We integrate these with a network pivot that supports joins through an arbitrary relation. We demonstrate with an example web log dataset of site visits organised into time, downloads, visitor address and referrer address dimensions and a network of prior and later visits.

A Two-Stage Model of the Promotional Performance of Pure Online Firms

Internet firms frequently employ a two-stage approach to promotional activities. In Stage 1, they attract customers to their websites through advertising. In Stage 2, firms generate sales transactions or sales leads through their website. Comprehensive assessment of the promotional performance of pure online firms requires the study of Stage 1 and of Stage 2 jointly. In this paper we develop a joint two-stage conceptual and econometric model for assessing website promotion on three important dimensions: (1) how advertising response can be measured by linking media schedules to website log files; (2) how advertising and website characteristics jointly affect the desired system outcome of the promotion; and (3) whether the joint investigation of advertising response and desired system outcomes is essential to assess the results of website promotion. Three general findings follow from application of our model to a pure online firm’s campaign to generate sales leads through print advertising. First, advertising and website characteristics affect sales leads in different ways. A characteristic may influence sales leads directly, or indirectly, or both. Second, assessing advertising effectiveness in an online environment may not require costly survey research data. Instead, secondary data available from website log files may be used for such assessment. Third, the interaction between the first and second stages of our two-stage model can lead to misspecifications that produce misleading inferences. This occurs because the unobserved characteristics in generating website visits and sales leads may be correlated.

Evaluating consumer website logs: a case study of The Times/The Sunday Times website

Evaluating consumer website logs: a case study of The Times/The Sunday Times website

Evaluating consumer website logs: a case study of The Times/The Sunday Times website

Information professionals have featured strongly in the evaluation of the use of commercial online hosts and online public access catalogues, but not so strongly in the evaluation of the use of websites. This paper describes a piece of research that was conducted on The Times/The Sunday Times websites, to determine the most appropriate methods for evaluating use and to establish what forms of analysis could best be derived. A database of one million subscribers and three months’ worth of logs, constituting 65 million lines of data, were obtained and the data were analysed using parsing techniques and the Statistical Package for the Social Sciences. There were problems associated with the analysis, largely because of the difficulties in establishing the identity of Web users, determining what actually constitutes use and measuring the time spent online. Men in their 30s were the sites’ most numerous subscribers. The majority of subscribers were foreign and came from commercial organisations. Use varied considerably from hour to hour and day to day and from country to country: in the UK, midweek lunchtimes proved very popular. On average, a user conducted 2.35 sessions over the survey period, spent 15 minutes on a search session and 0.5-2.1 minutes on reading a page. Commercial organisations and Americans were the heaviest users and news pages proved to be the most popular.

The one-card trick. Multi-application smart card E-commerce prototypes

Consult Hyperion has designed and built prototypes for BT which show the use of a Multos multi-application smart card for storing a digital ID and then demonstrating various E-commerce business applications (secure E-mail, ticketing, Web site log on etc.) via a variety of devices and networks. In addition, dynamic loading and deletion of card applications after card issue has been demonstrated. This article describes the prototypes.