Web crawlers on a health related portal: Detection, characterisation and implications

Web crawlers are automated computer programs that visit websites in order to download their content. They are employed for non-malicious (search engine crawlers indexing websites) and malicious purposes (those breaching privacy by harvesting email addresses for unsolicited email promotion and spam databases). Whatever their usage, web crawlers need to be accurately identified in an analysis of the overall traffic to a website. Visits from web crawlers as well as from genuine users are recorded in the web server logs. In this paper, we analyse the web server logs of NRIC, a health related portal. We present the techniques used to identify malicious and non-malicious web crawlers from these logs, using a blacklist database and analysis of the characteristics of the online behaviour of malicious crawlers. We use visualisation to carry out sanity checks along the crawler removal process. We illustrate the use of these techniques using 3 months of web server logs from NRIC. We use a combination of visualisation and baseline measures from Google Analytics to demonstrate the efficacy of our techniques. Finally, we discuss the implications of our work on the analysis of the web traffic to a website using web server logs and on the interpretation of the results from such analysis. © 2011 IEEE

Patia: Adaptive distributed webserver (A position paper)

This paper introduces the Patia Adaptive Webserver architecture, which is distributed and consists of semi-autonomous agents called FLYs. The FLY carries with it the set of rules and adaptivity policies required to deliver the data to the requesting client. Where a change in the FLY’s external environment could affect performance, it is the FLY’s responsibility to change the method of delivery (or the actual object being delivered). It is our conjecture that the success of today’s multimedia websites in terms of performance lies in the architecture of the underlying servers and their ability to adapt to changes in demand and resource availability, as well as their ability to scale. We believe that the distributed and autonomous nature of this system are key factors in achieving this.

Modeling User Preferences in Recommender Systems: A Classification Framework for Explicit and Implicit User Feedback

Recommender systems are firmly established as a standard technology for assisting users with their choices; however, little attention has been paid to the application of the user model in recommender systems, particularly the variability and noise that are an intrinsic part of human behavior and activity. To enable recommender systems to suggest items that are useful to a particular user, it can be essential to understand the user and his or her interactions with the system. These interactions typically manifest themselves as explicit and implicit user feedback that provides the key indicators for modeling users' preferences for items and essential information for personalizing recommendations. In this article, we propose a classification framework for the use of explicit and implicit user feedback in recommender systems based on a set of distinct properties that include Cognitive Effort, UserModel, Scale of Measurement, and Domain Relevance.We develop a set of comparison criteria for explicit and implicit user feedback to emphasize the key properties. Using our framework, we provide a classification of recommender systems that have addressed questions about user feedback, and we review state-of-the-art techniques to improve such user feedback and thereby improve the performance of the recommender system. Finally, we formulate challenges for future research on improvement of user feedback. © 2014 ACM

Application of User Profiling on Ontology Module Extraction for Medical portals

One fit all for approach for searching and ranking discovered knowledge on the Internet does not cater for the diverse variety of users and user groups with different preferences, information needs and priorities. This is of a particular case in the National electronic Library of Infection in the UK (NeLI, www.neli.org.uk) accessed by a number of medical professionals with different preferences and medical information needs. We define personal and group profiles, based on user-specified interests, and develop an ontology module extraction service defining the key area of the infection ontology of a particular relevance to each user group. In this paper we discuss how ontology modularisation can improve the NeLI portal by providing customised alert, recommender service and specialitycustomised browsing tree structure

The community structure of soil fauna of roadside trees at three different elevations in Mauritius / Zaynab Jawaheer

This study was carried out in Mauritius during summer from November 2012 to April 2013 and was designed to test the hypothesis that roadside tree diversity, elevation and bait type in pitfall traps affect soil fauna distribution and abundance The specific objectives of this study were to determine the species richness and diversity of roadside trees and to quantify the species richness, diversity, abundance and biomass of soil fauna of roadside trees in pitfall traps at different elevations. Soil fauna were collected utilizing pitfall traps made of plastic cups containing three different bait types (beef extract, beer and banana, and soap water) placed at three different elevations (Flic en Flac, 5m; Rose-Hill, 221m; and Mare aux Vacoas, 569m). Traps were placed among primary roadside tree species: Casuarina equisetifolia (Flic en Flac,), Dictyosperma album (Rose-Hill) and Pinus sylvestris (Mare aux Vacoas). A total of 18,114 individuals of soil fauna were sampled of which 10,142 individuals were sampled at Flic en Flac; 5293 individuals at Rose-Hill; and 2697 individuals at Mare aux Vacoas. The most abundant soil fauna among the three study sites was Carpophilus cheesmani (relative frequency=25.31%; relative abundance=46.54%). The heaviest soil fauna recorded was Achatina immaculata (mean biomass=1.2g). The Shannon Wiener Diversity varied significantly (p<0.05) between elevations (5m=1.84, 221m =1.21, 569m=2.54) while evenness was highest at 569m (0.92) followed by 5m (0.70) and lowest at 221m (0.42). The study sites with the highest soil fauna similarity were Mare aux Vacoas and Rose-Hill (0.71). Significant difference in soil fauna abundance and biomass was observed between elevations (<0.05), between months (<0.05) and between bait trap types (p<0.05). Significant correlations (p<0.05) between soil physiochemical parameters were recorded as well as their effect on soil fauna abundance. This study gives an initial view on the diversity, biomass and abundances of soil fauna from roadside trees of Mauritius. The results of this study support the concept that diversity of roadside trees and elevation have an impact on the community structure, abundance and biomass of soil fauna. This study can be useful in determining soil fauna and their plant host specificity as such data has implications for biological control as well as for collection of specific insects. This study also has implications for town planners with respect to planting roadside trees and their ensuing edaphic communities for managing insect pests. When comparing the three study sites, anthropogenic disturbances seem to have affected the soil fauna diversity, abundance and biomass. In this study, the observed effects have been highlighted and could be useful to beach authorities and municipal councils to avoid costly maintenance

Enabling Collaborative eHealth Research using Web 2.0 Tools

In this paper, we describe two Web 2.0 based systems designed to facilitate and enhance collaborative eHealth research activities. Using a combination of Forums, Wikis and connectivity to 3rd party social networking systems, we have designed systems to support collaborative document creation (including editing, reviewing and publication), dissemination of material to relevant communities, discussion of ideas, and sharing of opinions. The ECDC Field Epidemiology Manual Wiki and Medicine Support Unit Online Forums are presented herein, including an overview to the system architectures, and user interaction models. We present our planned methods of evaluation, focusing on the ability to measure successful and sustainable community involvement