Using bi-clustering algorithm for analyzing online users activity in a virtual campus

Data mining algorithms have been proved to be useful for the processing of large data sets in order to extract relevant information and knowledge. Such algorithms are also important for analyzing data collected from the users' activity users. One family of such data analysis is that of mining of log files of online applications that register the actions of online users during long periods of time. A relevant objective in this case is to study the behavior of online users and feedback the design processes of online applications to provide better usability and adaption to users' preferences. The context of this work is that of a virtual campus in which thousands of students and tutors carry out the learning and teaching activity using online applications. The information stored in log files of virtual campuses tend to be large, complex and heterogeneous in nature. Hence, their mining requires both efficient and intelligent processing and analysis of user interaction data during long-term learning activities. In this paper, we present a bi-clustering algorithm for processing large log data sets from the online daily activity of students in a real virtual campus. Our approach is useful to extract relevant knowledge about user activity such as navigation patterns, activities performed as well as to study time parameters related to such activities. The extracted information can be useful not only to students and tutors to stimulate and improve their experience when interacting with the system but also to the designers and developers of the virtual campus in order to better support the online teaching and learning.Peer ReviewedPostprint (published version

Data pre-processing on web server logs for generalized association rules mining algorithm

Web log file analysis began as a way for IT administrators to ensure adequate bandwidth and server capacity on their organizations website. Log file data can offer valuable insight into web site usage.It reflects actual usage in natural working condition, compared to the artificial setting of a usability lab.It represents the activity of many users, over potentially long period of time, compared to a limited number of users for an hour or two each.This paper describes the pre-processing techniques on IIS Web Server Logs ranging from the raw log file until before mining process can be performed. Since the pre-processing is tedious process, it depending on the algorithm and purposes of the applications

Distributed-based massive processing of activity logs for efficient user modeling in a Virtual Campus

This paper reports on a multi-fold approach for the building of user models based on the identification of navigation patterns in a virtual campus, allowing for adapting the campus’ usability to the actual learners’ needs, thus resulting in a great stimulation of the learning experience. However, user modeling in this context implies a constant processing and analysis of user interaction data during long-term learning activities, which produces huge amounts of valuable data stored typically in server log files. Due to the large or very large size of log files generated daily, the massive processing is a foremost step in extracting useful information. To this end, this work studies, first, the viability of processing large log data files of a real Virtual Campus using different distributed infrastructures. More precisely, we study the time performance of massive processing of daily log files implemented following the master-slave paradigm and evaluated using Cluster Computing and PlanetLab platforms. The study reveals the complexity and challenges of massive processing in the big data era, such as the need to carefully tune the log file processing in terms of chunk log data size to be processed at slave nodes as well as the bottleneck in processing in truly geographically distributed infrastructures due to the overhead caused by the communication time among the master and slave nodes. Then, an application of the massive processing approach resulting in log data processed and stored in a well-structured format is presented. We show how to extract knowledge from the log data analysis by using the WEKA framework for data mining purposes showing its usefulness to effectively build user models in terms of identifying interesting navigation patters of on-line learners. The study is motivated and conducted in the context of the actual data logs of the Virtual Campus of the Open University of Catalonia.Peer ReviewedPostprint (author's final draft

Investigation of Heterogeneous Approach to Fact Invention of Web Users’ Web Access Behaviour

World Wide Web consists of a huge volume of different types of data. Web mining is one of the fields of data mining wherein there are different web services and a large number of web users. Web user mining is also one of the fields of web mining. The web users’ information about the web access is collected through different ways. The most common technique to collect information about the web users is through web log file. There are several other techniques available to collect web users’ web access information; they are through browser agent, user authentication, web review, web rating, web ranking and tracking cookies. The web users find it difficult to retrieve their required information in time from the web because of the huge volume of unstructured and structured information which increases the complexity of the web. Web usage mining is very much important for various purposes such as organizing website, business and maintenance service, personalization of website and reducing the network bandwidth. This paper provides an analysis about the web usage mining techniques. Â

An information security model based on trustworthiness for enhancing security in on-line collaborative learning

L'objectiu principal d'aquesta tesi és incorporar propietats i serveis de la seguretat en sistemes d'informació en l'aprenentatge col·laboratiu en línia, seguint un model funcional basat en la valoració i predicció de la confiança. Aquesta tesi estableix com a punt de partença el disseny d'una solució de seguretat innovadora, basada en una metodologia pròpia per a oferir als dissenyadors i gestors de l'e-learning les línies mestres per a incorporar mesures de seguretat en l'aprenentatge col·laboratiu en línia. Aquestes guies cobreixen tots els aspectes sobre el disseny i la gestió que s'han de considerar en els processos relatius a l'e-learning, entre altres l'anàlisi de seguretat, el disseny d'activitats d'aprenentatge, la detecció d'accions anòmales o el processament de dades sobre confiança. La temàtica d'aquesta tesi té una naturalesa multidisciplinària i, al seu torn, les diferents disciplines que la formen estan íntimament relacionades. Les principals disciplines de què es tracta en aquesta tesi són l'aprenentatge col·laboratiu en línia, la seguretat en sistemes d'informació, els entorns virtuals d'aprenentatge (EVA) i la valoració i predicció de la confiança. Tenint en compte aquest àmbit d'aplicació, el problema de garantir la seguretat en els processos d'aprenentatge col·laboratiu en línia es resol amb un model híbrid construït sobre la base de solucions funcionals i tecnològiques, concretament modelatge de la confiança i solucions tecnològiques per a la seguretat en sistemes d'informació.El principal objetivo de esta tesis es incorporar propiedades y servicios de la seguridad en sistemas de información en el aprendizaje colaborativo en línea, siguiendo un modelo funcional basado en la valoración y predicción de la confianza. Esta tesis establece como punto de partida el diseño de una solución de seguridad innovadora, basada en una metodología propia para ofrecer a los diseñadores y gestores del e-learning las líneas maestras para incorporar medidas de seguridad en el aprendizaje colaborativo en línea. Estas guías cubren todos los aspectos sobre el diseño y la gestión que hay que considerar en los procesos relativos al e-learning, entre otros el análisis de la seguridad, el diseño de actividades de aprendizaje, la detección de acciones anómalas o el procesamiento de datos sobre confianza. La temática de esta tesis tiene una naturaleza multidisciplinar y, a su vez, las diferentes disciplinas que la forman están íntimamente relacionadas. Las principales disciplinas tratadas en esta tesis son el aprendizaje colaborativo en línea, la seguridad en sistemas de información, los entornos virtuales de aprendizaje (EVA) y la valoración y predicción de la confianza. Teniendo en cuenta este ámbito de aplicación, el problema de garantizar la seguridad en los procesos de aprendizaje colaborativo en línea se resuelve con un modelo híbrido construido en base a soluciones funcionales y tecnológicas, concretamente modelado de la confianza y soluciones tecnológicas para la seguridad en sistemas de información.This thesis' main goal is to incorporate information security properties and services into online collaborative learning using a functional approach based on trustworthiness assessment and prediction. As a result, this thesis aims to design an innovative security solution, based on methodological approaches, to provide e-learning designers and managers with guidelines for incorporating security into online collaborative learning. These guidelines include all processes involved in e-learning design and management, such as security analysis, learning activity design, detection of anomalous actions, trustworthiness data processing, and so on. The subject of this research is multidisciplinary in nature, with the different disciplines comprising it being closely related. The most significant ones are online collaborative learning, information security, learning management systems (LMS), and trustworthiness assessment and prediction models. Against this backdrop, the problem of securing collaborative online learning activities is tackled by a hybrid model based on functional and technological solutions, namely, trustworthiness modelling and information security technologies

Data Mining of Web Access Logs From an Academic Web Site

Abstract. We have used a general purpose data mining tool to determine whether we can find any ‘golden nuggets ’ in the web access logs of a large academic web site. Our goal was to use general purpose data mining algorithms to analyse visitors to the websit

Phishing website detection using intelligent data mining techniques. Design and development of an intelligent association classification mining fuzzy based scheme for phishing website detection with an emphasis on E-banking.

Phishing techniques have not only grown in number, but also in sophistication. Phishers might have a lot of approaches and tactics to conduct a well-designed phishing attack. The targets of the phishing attacks, which are mainly on-line banking consumers and payment service providers, are facing substantial financial loss and lack of trust in Internet-based services. In order to overcome these, there is an urgent need to find solutions to combat phishing attacks. Detecting phishing website is a complex task which requires significant expert knowledge and experience. So far, various solutions have been proposed and developed to address these problems. Most of these approaches are not able to make a decision dynamically on whether the site is in fact phished, giving rise to a large number of false positives. This is mainly due to limitation of the previously proposed approaches, for example depending only on fixed black and white listing database, missing of human intelligence and experts, poor scalability and their timeliness. In this research we investigated and developed the application of an intelligent fuzzy-based classification system for e-banking phishing website detection. The main aim of the proposed system is to provide protection to users from phishers deception tricks, giving them the ability to detect the legitimacy of the websites. The proposed intelligent phishing detection system employed Fuzzy Logic (FL) model with association classification mining algorithms. The approach combined the capabilities of fuzzy reasoning in measuring imprecise and dynamic phishing features, with the capability to classify the phishing fuzzy rules. Different phishing experiments which cover all phishing attacks, motivations and deception behaviour techniques have been conducted to cover all phishing concerns. A layered fuzzy structure has been constructed for all gathered and extracted phishing website features and patterns. These have been divided into 6 criteria and distributed to 3 layers, based on their attack type. To reduce human knowledge intervention, Different classification and association algorithms have been implemented to generate fuzzy phishing rules automatically, to be integrated inside the fuzzy inference engine for the final phishing detection. Experimental results demonstrated that the ability of the learning approach to identify all relevant fuzzy rules from the training data set. A comparative study and analysis showed that the proposed learning approach has a higher degree of predictive and detective capability than existing models. Experiments also showed significance of some important phishing criteria like URL & Domain Identity, Security & Encryption to the final phishing detection rate. Finally, our proposed intelligent phishing website detection system was developed, tested and validated by incorporating the scheme as a web based plug-ins phishing toolbar. The results obtained are promising and showed that our intelligent fuzzy based classification detection system can provide an effective help for real-time phishing website detection. The toolbar successfully recognized and detected approximately 92% of the phishing websites selected from our test data set, avoiding many miss-classified websites and false phishing alarms

Full Report: Use and Users of Digital Resources: A Focus on Undergraduate Education in the Humanities and Social Sciences

A "build it and they will come" approach to many university digitization initiatives has precluded systematic investigations of the demand for these resources. Those who fund and develop digital resources have identified the general lack of knowledge about the level and quality of their use in educational settings as pressing concerns. This full report describes our research and the complete results of a large 2-year study. The purpose of our research was (1) to map the universe of digital resources available to a subset of undergraduate educators in the humanities and social sciences, and (2) to investigate how and if available digital resources are actually being used in undergraduate teaching environments. We employed multiple methods, including surveys and focus groups. Our definition of digital resources was intentionally broad and included rich media objects (e.g., maps, video, images, etc.) as well as text

Towards an Understanding of the Astro Tourist: A conceptual and Empirical Study

It is well documented that mankind has been intrigued by the stars in the sky above for centuries. The stars traditionally represented a means of navigation, symbolised the gods and, to this day, inspire scientific examination and the creative imagination. However, few attempts have been made to conceptualise and empirically analyse the link between stargazers and tourism, thus creating a necessity for exploration. Stargazers (known as astro tourists throughout study) vary widely from those interested in the moon; the discovery of new planets; to those interested in the constellations, particularly as their motivations and preferences for being in the dark are varied and multidimensional. Therefore, the purpose of this ethnographic study was to critically explore the experiences and behaviours of the astro tourists as they are instrumental in providing an understanding of this emerging special interest form of tourism in the real world. Specifically, the location of the case study was the first UK Dark Sky Park in Dumfries and Galloway, Scotland, a landscape that embodies the darkness required to observe the stars in the sky above with the naked eye. Dark sky designation is a contemporary construct designed to protect the night sky from light pollution, it offers the astro tourist the opportunity to see the Milkyway on a cloud free, moonless night. It also offers tourists the chance to experience true darkness, an experience that is denied to many due to light pollution. To date, literature related to astro tourism has focused predominantly upon the management of the destination. For example, a few studies are related to the astro tourist as an environmentalist who seeks to protect the night sky, whereas others relate to the pursuit of science. As a result, a gap has emerged in the understanding of the needs and experiences of the aforementioned astro tourist. In addressing this gap, this research provides a critical exploration of the astro tourist as it identifies the experiences, the spiritual nature of being in the dark, and the significance that outer-space has on the contemporary tourist. This study is instrumental in developing a contextual framework that reflects the dynamic relationships between need satisfaction, space embodiment and place significance as it critically discusses how these three concepts link to understanding the astro tourist experience. This thesis is an ethnographic study that contains a complex interplay with a phenomenographic approach, thus a dual methodology is applied. Consequently, this study focuses upon the use of qualitative research methods within an interpretative/constructive paradigm, whilst seeking to explore the ‘different ways’ in which ‘people experience something’ or ‘think about something’ (Ryan, 1995:53). This study is framed by psychogeographic ideology, employed initially to develop an environmental understanding of the astro tourist experience via observation, it aimed to ascertain the sensory motives experienced by the participants via survey, and finally to delve deeper into the behaviours and experiences of participants via interviews. Throughout the study, reflexivity is employed to portray the journey from darkness to light. The findings add to the body of knowledge by illustrating that astro tourists are interested in far more than learning about the stars, they visit the destination to look up, usually with family and friends; the dark has a significant effect upon their experience as for many it is existential; the weather and the presence of others at the event enhance the experience due to their physicality. Many astro tourists do not have an interest in the forest park or their Earthly surroundings at place, they focus upon the night-sky; outer space plays a significant role in their experience, whereas place is an enabler, a means to an end, this adds a hitherto unexplored dimension to the tourists’ experience and behaviour research, which traditionally placed the destination central to the visitor experience – making astro tourism a none destination experience. Sensory dimensions of the experience are created by a tri-partite relationship which incorporates the dark, space and the senses, these combine to give significance to the astro tourist experience