Web Mining for Web Personalization

Web personalization is the process of customizing a Web site to the needs of specific users, taking advantage of the knowledge acquired from the analysis of the user\u27s navigational behavior (usage data) in correlation with other information collected in the Web context, namely, structure, content, and user profile data. Due to the explosive growth of the Web, the domain of Web personalization has gained great momentum both in the research and commercial areas. In this article we present a survey of the use of Web mining for Web personalization. More specifically, we introduce the modules that comprise a Web personalization system, emphasizing the Web usage mining module. A review of the most common methods that are used as well as technical issues that occur is given, along with a brief overview of the most popular tools and applications available from software vendors. Moreover, the most important research initiatives in the Web usage mining and personalization areas are presented

Ad hoc communities on the road: Serendipitous social encounters to enhance tourist experiences

Driving can be a lonely activity. While there has been a lot of research and technical inventions concerning car-to-car communication and passenger entertainment, there is still little work concerning connecting drivers. Whereas tourism is very much a social activity, drive tourists and road trippers have few options to communicate with fellow travelers. Our study is placed at the intersection of tourism and driving. It aims to enhance the trip experience during driving through social interaction. This paper explores how a mobile application that allows instant messaging between travelers sharing similar context can establish a temporary, ad hoc community and enhance the road trip experience. A prototype was developed and evaluated in various user and field studies. The study’s outcomes are relevant for the design of future mobile tourist guides that benefit from community design, social encounters and recommendations

Hypermedia-based discovery for source selection using low-cost linked data interfaces

Evaluating federated Linked Data queries requires consulting multiple sources on the Web. Before a client can execute queries, it must discover data sources, and determine which ones are relevant. Federated query execution research focuses on the actual execution, while data source discovery is often marginally discussed-even though it has a strong impact on selecting sources that contribute to the query results. Therefore, the authors introduce a discovery approach for Linked Data interfaces based on hypermedia links and controls, and apply it to federated query execution with Triple Pattern Fragments. In addition, the authors identify quantitative metrics to evaluate this discovery approach. This article describes generic evaluation measures and results for their concrete approach. With low-cost data summaries as seed, interfaces to eight large real-world datasets can discover each other within 7 minutes. Hypermedia-based client-side querying shows a promising gain of up to 50% in execution time, but demands algorithms that visit a higher number of interfaces to improve result completeness

Bridging the Information Gap for Ulcerative Colitis Patients

Nearly all humans, throughout the course of their life, have been diagnosed with everything from a mild cold, to a viral infection, or perhaps a diagnosis of a chronic condition. Upon experiencing symptoms, patients are exposed to a plethora of information. The Internet holds home remedies, for those wary of the doctor\u27s office, or there are advice boards where people share their experiences, trials, and tribulations. In some cases, the doctor is the purveyor of the information and written materials are sent home with the patient dictating the regimen to follow to achieve wellness. However, some patients, particularly ulcerative colitis patients, find themselves without these written materials and without access to health information specifically tailored to their needs. Patients must forage for information while trying to maintain their health after diagnosis. This study explores the holes in the information-sharing process through interviews and surveys, focusing specifically on patients, technical medical writers, and gastroenterologists. The study finds most ulcerative colitis patients do not receive the information they need

Technology Use by Registered Dietitians for Patient Care in an Outpatient Setting

Background Technology use in digital health tools has increased significantly since the COVID-19 pandemic disrupted many in-office patient care services. Although healthcare practices have adopted several technologies, they remain surrounded by a saturated increase in consumer-based wearables and smartphone applications. As a result, attitudes and acceptability toward integrating these technologies for patient care are evolving. Digital health tools is an umbrella term including several technologies utilized among health care providers for the purpose of patient care. The inclusion of digital health tools by Registered Dietitian Nutritionists’ (RDNs) in practice provides a more robust and personalized approach to patients and their health needs. Reasons for decisions about incorporating digital health tools into the RDN practice setting are limited in the professional literature. Methods An exploratory cross-sectional survey design was used. Professionals working as Registered Dietitian Nutritionists (RDNs) were recruited utilizing a snowball sampling approach among several practice settings. Survey compilation included a literature review, identifying and utilizing two surveys otherwise used for different purposes and target audiences. Data collection consists of a 2-step process with a survey pilot test and distribution of a final survey administered via Qualtrics. Data analysis was conducted using SPSS v27.0. Results Sixteen of 20 professionals completed the survey in its entirety: 2 working in employee wellness, 13 in a hospital-based system, and 1 in both employee wellness and community/public health. Quantitative analysis depicted the highest usage of tele-visits/virtual visits and less appreciation for technology in eating disorders. Additionally, RDNs reported heightened chances of adopting a tool if the technology is the standard of care. Qualitative analysis indicated that professionals working in a setting for diabetes had a positive attitude towards wearable or smartphone nutrition applications. Moreover, other practice settings such as dialysis and post-liver transplant, eating disorders, or employee wellness produced either a neutral or negative attitude. Conclusions Registered dietitian nutritionists are highly interested in using digital health tools for patient care. However, it is difficult to conclude the current use of technology in outpatient practice. RDNs understand the potential of technology, such as wearables, in offering patients care concerning their illness or diagnosis. Although RDNs utilize telehealth, other technologies such as wearables and smartphone nutrition apps have yet to be widely adopted. The use of technology among RDNs who practice in an outpatient setting is highly variable, and therefore a presumption cannot be made. Therefore, future research is warranted, focusing on patients with various health conditions and diverse samples

A heuristic-based approach to code-smell detection

Encapsulation and data hiding are central tenets of the object oriented paradigm. Deciding what data and behaviour to form into a class and where to draw the line between its public and private details can make the difference between a class that is an understandable, flexible and reusable abstraction and one which is not. This decision is a difficult one and may easily result in poor encapsulation which can then have serious implications for a number of system qualities. It is often hard to identify such encapsulation problems within large software systems until they cause a maintenance problem (which is usually too late) and attempting to perform such analysis manually can also be tedious and error prone. Two of the common encapsulation problems that can arise as a consequence of this decomposition process are data classes and god classes. Typically, these two problems occur together – data classes are lacking in functionality that has typically been sucked into an over-complicated and domineering god class. This paper describes the architecture of a tool which automatically detects data and god classes that has been developed as a plug-in for the Eclipse IDE. The technique has been evaluated in a controlled study on two large open source systems which compare the tool results to similar work by Marinescu, who employs a metrics-based approach to detecting such features. The study provides some valuable insights into the strengths and weaknesses of the two approache