Standing on the shoulders of ants : stigmergy in the Web

Stigmergy is a biological term used when discussing insect or swarm behaviour, and describes a model supporting environmental communication separately from artefacts or agents. This phenomenon is demonstrated in the behavior of ants and their food gathering process when following pheromone trails, or similarly termites and their termite mound building process. What is interesting with this mechanism is that highly organized societies are achieved with a lack of any apparent management structure. Stigmergic behavior is implicit in the Web where the volume of users provides a self-organizing and self-contextualization of content in sites which facilitate collaboration. However, the majority of content is generated by a minority of the Web participants. A significant contribution from this research would be to create a model of Web stigmergy, identifying virtual pheromones and their importance in the collaborative process. This paper explores how exploiting stigmergy has the potential of providing a valuable mechanism for identifying and analyzing online user behavior recording actionable knowledge otherwise lost in the existing web interaction dynamics. Ultimately this might assist our building better collaborative Web sites.

Stigmergy in Web 2.0 : a model for site dynamics

Building Web 2.0 sites does not necessarily ensure the success of the site. We aim to better understand what improves the success of a site by drawing insight from biologically inspired design patterns. Web 2.0 sites provide a mechanism for human interaction enabling powerful intercommunication between massive volumes of users. Early Web 2.0 site providers that were previously dominant are being succeeded by newer sites providing innovative social interaction mechanisms. Understanding what site traits contribute to this success drives research into Web sites mechanics using models to describe the associated social networking behaviour. Some of these models attempt to show how the volume of users provides a self-organising and self-contextualisation of content. One model describing coordinated environments is called stigmergy, a term originally describing coordinated insect behavior. This paper explores how exploiting stigmergy can provide a valuable mechanism for identifying and analysing online user behavior specifically when considering that user freedom of choice is restricted by the provided web site functionality. This will aid our building better collaborative Web sites improving the collaborative processes.

Continuous and non-intrusive identity verification in real-time environments based on free-text keystroke dynamics

Internet services are important part of daily activities for most of us. These services come with sophisticated authentication requirements which may not be handled by average Internet users. The management of secure passwords for example creates an extra overhead which is often neglected due to usability reasons. Furthermore, password-based approaches are applicable only for initial logins and do not protect against unlocked workstation attacks. In this paper, we provide a non-intrusive identity verification scheme based on behavior biometrics where keystroke dynamics based-on free-text is used continuously for verifying the identity of a user in real-time. We improved existing keystroke dynamics based verification schemes in four aspects. First, we improve the scalability where we use a constant number of users instead of whole user space to verify the identity of target user. Second, we provide an adaptive user model which enables our solution to take the change of user behavior into consideration in verification decision. Next, we identify a new distance measure which enables us to verify identity of a user with shorter text. Fourth, we decrease the number of false results. Our solution is evaluated on a data set which we have collected from users while they were interacting with their mail-boxes during their daily activities.

Hot topic detection in news blogs from the perspective of W2T

News blog hot topics are important for the information recommendation service and marketing. However, information overload and personalized management make the information arrangement more difficult. Moreover, what influences the formation and development of blog hot topics is seldom paid attention to. In order to correctly detect news blog hot topics, the paper first analyzes the development of topics in a new perspective based on W2T (Wisdom Web of Things) methodology. Namely, the characteristics of blog users, context of topic propagation and information granularity are unified to analyze the related problems. Some factors such as the user behavior pattern, network opinion and opinion leader are subsequently identified to be important for the development of topics. Then the topic model based on the view of event reports is constructed. At last, hot topics are identified by the duration, topic novelty, degree of topic growth and degree of user attention. The experimental results show that the proposed method is feasible and effective.

Extracting news blog hot topics based on the W2T methodology

Although topic detection and tracking techniques have made great progress, most of the researchers seldom pay more attention to the following two aspects. First, the construction of a topic model does not take the characteristics of different topics into consideration. Second, the factors that determine the formation and development of hot topics are not further analyzed. In order to correctly extract news blog hot topics, the paper views the above problems in a new perspective based on the W2T (Wisdom Web of Things) methodology, in which the characteristics of blog users, context of topic propagation and information granularity are investigated in a unified way. The motivations and features of blog users are first analyzed to understand the characteristics of news blog topics. Then the context of topic propagation is decomposed into the blog community, topic network and opinion network, respectively. Some important factors such as the user behavior pattern, opinion leader and network opinion are identified to track the development trends of news blog topics. Moreover, a blog hot topic detection algorithm is proposed, in which news blog hot topics are identified by measuring the duration, topic novelty, attention degree of users and topic growth. Experimental results show that the proposed method is feasible and effective. These results are also useful for further studying the formation mechanism of opinion leaders in blogspace.

A rule-based hybrid method for anomaly detection in online-social-network graphs

Detecting anomalies in the online social network is a significant task as it assists in revealing the useful and interesting information about the user behavior on the network. This paper proposes a rule-based hybrid method using graph theory, Fuzzy clustering and Fuzzy rules for modeling user relationships inherent in online-social-network and for identifying anomalies. Fuzzy C-Means clustering is used to cluster the data and Fuzzy inference engine is used to generate rules based on the cluster behavior. The proposed method is able to achieve improved accuracy for identifying anomalies in comparison to existing methods.

Effects of transit quality of service characteristics on daily bus ridership

This study investigates whether an Australian city’s suburbs having high transit Quality of Service (QoS) are associated with higher transit ridership than those having low transit QoS •We explore how QoS measures including service frequency, service span, service coverage, and travel time ratio, along with implicit environmental predictors such as topographic grade factor influence bus ridership •We applied Multiple Linear Regression (MLR) to examine the relationship between QoS and ridership •Its outcomes enhance our understanding of transit user behavior, which is informative to urban transportation policy, planning, and provision

Pattern-growth based frequent serial episode discovery

Frequent episode discovery is a popular framework for pattern discovery from sequential data. It has found many applications in domains like alarm management in telecommunication networks, fault analysis in the manufacturing plants, predicting user behavior in web click streams and so on. In this paper, we address the discovery of serial episodes. In the episodes context, there have been multiple ways to quantify the frequency of an episode. Most of the current algorithms for episode discovery under various frequencies are apriori-based level-wise methods. These methods essentially perform a breadth-first search of the pattern space. However currently there are no depth-first based methods of pattern discovery in the frequent episode framework under many of the frequency definitions. In this paper, we try to bridge this gap. We provide new depth-first based algorithms for serial episode discovery under non-overlapped and total frequencies. Under non-overlapped frequency, we present algorithms that can take care of span constraint and gap constraint on episode occurrences. Under total frequency we present an algorithm that can handle span constraint. We provide proofs of correctness for the proposed algorithms. We demonstrate the effectiveness of the proposed algorithms by extensive simulations. We also give detailed run-time comparisons with the existing apriori-based methods and illustrate scenarios under which the proposed pattern-growth algorithms perform better than their apriori counterparts. (C) 2013 Elsevier B.V. All rights reserved.

Serviço de intercâmbio de material bibliográfico da Biblioteca da Câmara dos Deputados : uma proposta de melhoria que contemple a arquitetura da informação

Proposta de melhoria do Serviço de Intercâmbio da Biblioteca da Câmara dos Deputados a partir da adoção de um novo modelo balizado pela Arquitetura da Informação e que contemple os recursos tecnológicos atualmente disponíveis. Dentre as justificativas para esta proposta estão a necessidade de modernização para manutenção do serviço, um dos pilares do desenvolvimento de coleções; e o alinhamento deste serviço ao comportamento do usuário pela busca de informação, que vem mudando após o advento da internet. A pesquisa é do tipo exploratória que apresenta a revisão de literatura como base para a fundamentação teórica, na qual são discutidos os aspectos teóricos do desenvolvimento de coleções na modalidade de aquisição por doação, realizada por meio do serviço de intercâmbio entre as bibliotecas. No procedimento metodológico foi feito um estudo no Serviço de Intercâmbio da Biblioteca da Câmara dos Deputados para obter os dados estatísticos que quantificam essa atividade. Foi elaborado um questionário, e enviado as 14 bibliotecas da Rede RVBI para conhecer o funcionamento do serviço de intercâmbio em cada uma delas. Com base nas respostas advindas do questionário foi sugerida a criação de um catálogo coletivo de acesso público via web, nos moldes do Portal Estante Virtual, para centralizar e gerenciar as atividades de intercâmbio de publicações. Os objetivos do catálogo são centralizar as informações e substituir um serviço pouco automatizado nas bibliotecas, outros objetivos do catálogo são agilizar a troca de publicações entre bibliotecas, propiciar economia de espaço, de recursos humanos e financeiros ao otimizar as rotinas e promover a democratização das listas de doações para um número maior de bibliotecas.

Student use of electronic information services in further education

Urquhart,C., Thomas, R., Spink, S., Fenton, R., Yeoman, A., Lonsdale, R., Armstrong, C., Banwell, L., Ray, K., Coulson, G. & Rowley, J. (2005). Student use of electronic information services in further education. International Journal of Information Management, 25(4), 347-362. Sponsorship: JISC

Event-driven implicit authentication for mobile access control

In order to protect user privacy on mobile devices, an event-driven implicit authentication scheme is proposed in this paper. Several methods of utilizing the scheme for recognizing legitimate user behavior are investigated. The investigated methods compute an aggregate score and a threshold in real-time to determine the trust level of the current user using real data derived from user interaction with the device. The proposed scheme is designed to: operate completely in the background, require minimal training period, enable high user recognition rate for implicit authentication, and prompt detection of abnormal activity that can be used to trigger explicitly authenticated access control. In this paper, we investigate threshold computation through standard deviation and EWMA (exponentially weighted moving average) based algorithms. The result of extensive experiments on user data collected over a period of several weeks from an Android phone indicates that our proposed approach is feasible and effective for lightweight real-time implicit authentication on mobile smartphones.

Social-aware opportunistic routing

The increased capabilities (e.g., processing, storage) of portable devices along with the constant need of users to retrieve and send information have introduced a new form of communication. Users can seamlessly exchange data by means of opportunistic contacts among them and this is what characterizes the opportunistic networks (OppNets). OppNets allow users to communicate even when an end-to-end path may not exist between them. Since 2007, there has been a trend to improve the exchange of data by considering social similarity metrics. Social relationships, shared interests, and popularity are examples of such metrics that have been employed successfully: as users interact based on relationships and interests, this information can be used to decide on the best next forwarders of information. This Thesis work combines the features of today's devices found in the regular urban environment with the current social-awareness trend in the context of opportunistic routing. To achieve this goal, this work was divided into di erent tasks that map to a set of speci c objectives, leading to the following contributions: i) an up-to-date opportunistic routing taxonomy; ii) a universal evaluation framework that aids in devising and testing new routing proposals; iii) three social-aware utility functions that consider the dynamic user behavior and can be easily incorporated to other routing proposals; iv) two opportunistic routing proposals based on the users' daily routines and on the content traversing the network and interest of users in such content; and v) a structure analysis of the social-based network formed based on the approaches devised in this work.

Modeling building semantics: providing feedback and sustainability

Even minor changes in user activity can bring about significant energy savings within built space. Many building performance assessment methods have been developed, however these often disregard the impact of user behavior (i.e. the social, cultural and organizational aspects of the building). Building users currently have limited means of determining how sustainable they are, in context of the specific building structure and/or when compared to other users performing similar activities, it is therefore easy for users to dismiss their energy use. To support sustainability, buildings must be able to monitor energy use, identify areas of potential change in the context of user activity and provide contextually relevant information to facilitate persuasion management. If the building is able to provide users with detailed information about how specific user activity that is wasteful, this should provide considerable motivation to implement positive change. This paper proposes using a dynamic and temporal semantic model, to populate information within a model of persuasion, to manage user change. By semantically mapping a building, and linking this to persuasion management we suggest that: i) building energy use can be monitored and analyzed over time; ii) persuasive management can be facilitated to move user activity towards sustainability.

Context relevant persuasive interaction and design: consideration of human factors influencing B2C persuasive interaction

The revolutions of electronic and mobile commerce have opened up unique opportunities for global marketing and business to consumer (B2C) persuasive interaction; with the aim of influencing user behavior. The success or failure of such persuasive interaction is impacted by cultural, social, and personal dimensions. Accordingly, failure to consider such dimensions risks the user forming a negative attitude towards retailer’s websites or mobile applications, which subsequently threatens customer behavior. A better understanding of human factors influencing the way people perceive B2C persuasive interaction is needed. This paper is introduces the concept of a context relevant persuasive interaction and proposes a guideline for designing relevant B2C persuasive interaction.

Network dynamics of mobile social networks

With the rapid development of smartphones and mobile Internet technology, we witness an overwhelming growth of mobile social networks (MSN), which is a type of social network, forming virtual communities among people with similar interests or commonalities. In MSNs, users play a crucial role for their development, deployment and success. Understanding the MSN user behavior therefore attracts interests of different entities - ISPs, service providers, and researchers. However, it is hard to gather a comprehensive real data set, little is known and even less has been published about MSN user activities. In this paper, we focus on analyzing MSN user behavior from the perspective of ISP network, which is seldom reported in literature. Based on the real data set collected from the mobile network gateway of a major mobile carrier who has more than five million subscribers, we present an in-depth user behavior analysis of four popular social networks. We study the MSN user behavior from six aspects: user requests, active online time, sessions, inter-session, the number of requests in a session, and inter-request. We found that power law and lognormal are two popular features of the studied objects, and exposed some interesting findings as well. We hope our work could be helpful for ISPs, MSN content providers, and researchers. © 2014 IEEE.