Improving dental care recommendation systems using trust and social networks

The growing popularity of Health Social Networking sites has a tremendous impact on people's health related experiences. However, without any quality filtering, there could be a detrimental effect on the users' health. Trust-based techniques have been identified as effective methods to filter the information for recommendation systems. This research focuses on dental care related social networks and recommendation systems. Trust is critical when choosing a dental care provider due to the invasive nature of the treatment. Surprisingly, current dental care recommendation systems do not use trust-based techniques, and most of them are simple reviews and ratings sites. This research aims at improving dental care recommendation systems by proposing a new framework, taking trust into account. It derives trust from both users' social networks and from existing crowdsourced information on dental care. Such a framework could be used for other healthcare recommendation systems where trust is of major importance. © 2014 IEEE

Analysing and using subjective criteria to improve dental care recommendation systems

Online reviews and rating sites are shaping industries as the users rely on recommendations given by former consumers and sharing opinions on the web. Dentistry has also been impacted by dental patients' reviews. This paper classifies trust-related information for dental care recommendations onto 4 categories: context, relationship, reputation and subjective criteria. It discusses each category and describes how they help focussing on trust when matching patients and dentists in brief. The paper then focuses on subjective criteria and presents the results of a survey aimed at showing trustrelated information emerged from subjective characteristics. Traits of personalities are used as subjective characteristics of patients and that of dentists are derived from the online patients' reviews. 580 Australian patients were surveyed to determine what factors affect their decision to find the trusted dentist. Subjective characteristics of dentists such as dentists' qualities and experienced dentists are considered the most important factors after location and cost. The most preferred dentists' qualities by almost all types of personalities are experienced, professional and quality of service. When the patients are further classified based on levels of fear, their preferences for dentists' qualities changed. Subjective qualities of both patients and dentists are important factors to improve the matching capability for the dental care recommendation systems

A NOVEL USER PROFILE-BASED FUZZY APPROACH FOR EVALUATING TRUST IN SEMANTIC WEB

ABSTRACT: As a developed World Wide Web architecture, the Semantic Web collects traditional web contents with a formal and understandable semantic using a machine. The main purpose of the Semantic Web is to increase automation, web information processing, and improve interactions and collaboration among information systems. The subject of trust is one of the main challenges in the semantic web. Since different tools and individuals exist in the semantic web, a certain measure of trust in an entity cannot be used and a central system is responsible for data collection and estimating the reliability. In this study, a fuzzy system is used to evaluate the trust measure in the semantic web. For this purpose, the user profile data including a list of pages, user sessions, and visited pages in each session, and the time of page viewings are used as semantic parameters. After determining the general framework of trust in the semantic web, the effectiveness of the above mentioned semantic parameters on the trust measure is investigated and effective parameters are used for evaluation in the fuzzy system. The experiment results show that the proposed fuzzy method with a mean absolute error of 2.5% and an average precision of 97.5% could achieve the right value of trust in the semantic web. ABSTRAK:  Sebagai senibina World Wide Web, Semantik Web mengumpul kandungan web tradisional bersama semantik formal dan mudah difahami menggunakan mesin. Tujuan utama Semantik Web adalah bagi meningkatkan automasi, pemprosesan maklumat web, dan meningkatkan interaksi dan kerjasama antara sistem maklumat. Kepercayaan adalah salah satu cabaran utama dalam web semantik. Disebabkan perbezaan alatan dan pelbagai individu wujud dalam web semantik, langkah tertentu sebagai entiti dipercayai tidak dapat digunakan dan sistem pusat adalah bertanggungjawab bagi pengumpulan data dan kebolehpercayaan anggaran. Dalam kajian ini, sistem rawak telah digunakan bagi menilai tahap kepercayaan dalam web semantik. Bagi tujuan ini, data profil pengguna termasuk senarai halaman, sesi pengguna, dan halaman yang dikunjungi dalam setiap sesi, dan masa paparan halaman telah digunakan sebagai parameter semantik. Selepas menentukan rangka umum kepercayaan dalam web semantik, keberkesanan parameter semantik yang dinyatakan di atas pada ukuran kepercayaan telah disiasat dan parameter yang berkesan telah digunakan bagi penilaian sistem rawak. Keputusan eksperimen menunjukkan bahawa kaedah rawak yang dicadangkan dengan ralat mutlak purata sebanyak 2.5% dan ketepatan purata sebanyak 97.5% dapat mencapai nilai kepercayaan yang benar dalam web semantik

Exploring Information Disclosure In Online Auctions

This research examines how a seller’s reputation score and auction pre-configuration affects people’s participation in communication within online auction communities. A leading horizontal intermediary auction platform is used to conduct this research. Its seller “feedback” mechanism and “ask seller a question” forum are chosen as representatives of post- and intra-transactional information disclosure. A self-developed classification approach is used to classify the buyer-initiated questions. The results of multinomial logistic regression indicate that product quality, shipment and payment issues are aspects that concern buyers the most in the early stages of an auction. Subsequently, their attention is likely to shift to seller credibility and price negotiations as listing durations get longer. In terms of the influ- ence of seller feedback ratings, our findings suggest that lower-rated traders are more likely to be asked questions about product description and seller credibility. Buyer concern about seller uncertainty is only alleviated if the seller has a good reputation. Even medium-rated sellers are suspected of being opportunistic. Moreover, buyers are more willing to discuss transaction-related issues and raise negotiation-associated questions with sellers who have already achieved high reputation scores. Finally, the theoretical and managerial implications are elaborated