Web Sessions Research Articles

Chi-square based hierarchical agglomerative clustering for web sessionization

Clustering is one of the fundamental techniques to organise similar objects into proper groups based on features in the domain of data mining, machine learning and pattern recognition. In each cluster, objects are more similar to each other on the basis of particular features. Clustering has numerous applications in multiple domains such as information retrieval, data mining, machine learning, pattern recognition, mathematics, medical and bioinformatics. Web centric applications are expanding day by day and the web has become one of the largest data repositories. During the last decade, information and knowledge retrieval from the web has become a challenging research area. Similarity computation among the data objects (web sessions) is complex, however is a significant problem in unsupervised learning. This research is an attempt to overcome these challenges and problems. The objective of this research paper is to introduce a chi-square based similarity measure to compute the similarity among the sessions. A chi-square based approach is being applied to compute the statistically significant relationship between observed and expected frequencies of the number of pages visited and the time consumed by a user during a session. Moreover, a chi-square based hierarchical agglomerative clustering (Chi-HAC) technique is proposed to extract useful knowledge from web log. The Chi-HAC helps to improve the visualisation of web logs and is equally important for website designers, developers and owners for the improvements of websites at each level. Experimental results with two different log files reveal that the proposed similarity measure with Chi-HAC algorithm has significantly improved the computation among data objects in web sessions.

Reconstructing Sessions from Data Discovery and Access Logs to Build a Semantic Knowledge Base for Improving Data Discovery

Big geospatial data are archived and made available through online web discovery and access. However, finding the right data for scientific research and application development is still a challenge. This paper aims to improve the data discovery by mining the user knowledge from log files. Specifically, user web session reconstruction is focused upon in this paper as a critical step for extracting usage patterns. However, reconstructing user sessions from raw web logs has always been difficult, as a session identifier tends to be missing in most data portals. To address this problem, we propose two session identification methods, including time-clustering-based and time-referrer-based methods. We also present the workflow of session reconstruction and discuss the approach of selecting appropriate thresholds for relevant steps in the workflow. The proposed session identification methods and workflow are proven to be able to extract data access patterns for further pattern analyses of user behavior and improvement of data discovery for more relevancy data ranking, suggestion, and navigation.

Case Study : Comparative Analysis: On Clustering of Sequential Data Streams USING Optics and ICA

Clustering on web usage data is useful to identify what users are exactly looking for on the world wide web, lik e user traversals, users behavior and their characteristics, which helps for Web personalization. Clustering web sessions is to group them based on similarity and consists of minimizing the Intra-cluster similarity and maximizing the Inter-group similarity. In the past there exist multiple similarity measures like Euclidean, Jaccard ,Cosine ,Manhanttan, Minkowski, and many to measure similarity between web patterns. In this paper, we enhanced Icremental clustering algorithm (ICA) based on OPTICS. Experiments are performed on MSNBC.COM website ( free online news channel), on sequential data streams in the context of clustering in the domain of Web usage mining. Specially, we present a detailed comparison of ICA and OPTICS and the results illustrate that ICA is much more suitable for clustering the dynamic datasets. The Inter-cluster and Intra-cluster distances are computed using Average Levensthien distance (ALD) to demonstrate the usefulness of the proposed approach in the context of web usage mining. This new enhanced (ICA algorithm )has good results when compared with existing OPTICS clustering technique , and provided good time requirements of the newly developed algorithms.

BYOD 환경을 고려한 모바일 웹을 위한 세션 관리 개선 방안 연구

This paper explains a web session management system for mobile web environment with BYOD(Bring Your Own Device). This system operates by enhanced secure session token. This system consists of an unique identifier, time stamp, and encryption algorithm. The Unique identifier in this system classifies each mobile device for web security based on mobile environment with BYOD. And the Time stamp in this system that determine session effectiveness for web security. Also the Cipher algorithm in this system that protects session token information for web security. This paper analysis a security of session management system running on mobile web environment using the simulation techniques. The proposed method is more suitable than the other methods under enviroment mobile web environment with BYOD.

Case studies using 3D technologies for corrective osteotomies : synergy between engineer and surgeon

Three-dimensional (3D) visualization, surgical pre-planning, and 3D printing or additive manufacturing of patient specific instruments and implants are fast gaining attention in the medical world. Already widely used in cranio-maxillofacial, dental, and total knee replacement surgery, 3D technologies are now starting to create a trend in the upper limb region too. A crucial step in establishing successful synergy between 3D technology and the orthopaedic world is to thoroughly get to know one another. Technology companies should constantly be aware of the changing needs of the medical field and be ready to evolve where and when needed. The medical field, in turn, should be aware of the new possibilities this technology offers but also mindful of its limitations. This is true in general and maybe even more so for corrective osteotomies in the upper limb, where current techniques mostly rely on two-dimensional(2D) X-rays and mass-standardized implant designs to solve often complex and extremely individualized malformations. In day to day practice, this synergy starts with an orthopaedic surgeon virtually planning his/her surgery together with the (clinical) engineer. Using Materialise solutions (Materialise N.V, Leuven, Belgium), nearly 500 upper-and lower limb cases have been completed with this personalized approach globally. It requires the surgeon and the engineer to, ‘sit together’, as it were, during online web sessions to discuss the case and to find the preferred solution for each individual patient. Applications for this 3D technology range from mal-united distal and diaphyseal extra-articular fractures to intra-articular fractures with more than 2 distal fragments, rare forms of radio-ulnar synostosis, cubitus varus/valgus, multiple hereditary exostosis, and Madelung deformities. Preparing for corrective osteotomies with the use of digital pre-planning is, in most cases, complemented with 3D printed guides. With engineering experience in approximately 180 of such cases, a few case studies are selected to highlight virtual planning, its possibilities, and its consequences. A common approach in the virtual pre-planning of upper limb corrective osteotomies is having a 3D visualization of both limbs based on a CT scan. The 3D visualization is then manipulated to reveal the comparison between the healthy – if any – and the surgical side, illustrating very clearly the deformity and the correction needed. Decisions are made with respect to the amount of lengthening or shortening required, whether the intra-articular component needs to be addressed, where to perform the osteotomy, which plate to use, and many more. This is all done with a focus on the original pathology that must be addressed. Often, this step is an eye-opening diagnostic tool as many 3D deformities are not captured on X-ray. Virtual 3D planning provides an opportunity to digitally “test out” several different approaches for the surgery, resulting in a final, preferred solution that can then be brought to the OR. However, to reach this optimized surgical plan, there is a high need for synergy between the clinical knowledge and experience of the surgeon and the technical knowledge and experience of the engineer involved in the planning. When this synergy is established, patients get treatments with a single, full-contact osteotomy, or with optimized wedges for grafting. In some cases, patients are finally treated for a pathology that was previously deemed impossible to treat with conventional, standard techniques. The potential applications of this technology are boundless, but the limitations must be carefully considered as well. For example, simulation of the behavior of the soft tissue after correction still remains uncertain. Although the goal of the surgical plan is to achieve a bony anatomical restoration, there is no guarantee that the soft tissues will allow this bony restoration to regain full pro-supination and/or flexion-extension. Additionally, in cases where a healthy contralateral side is unavailable or bilateral congenital deformities are involved, the surgical plan is even more dependent on the surgeon’s experience to correct the malunion in the most suitable way. Provided each other’s strengths and limitations are taken into consideration, synergy between an engineer and a surgeon can become the foundation for revolutionizing the way orthopaedic surgery is done. It is clear the future holds more exciting new opportunities. Figure 1

The Influence of a Performance Improvement Program on MRI in Spinal Trauma

Introduction Performance improvement (PI) programs are an educational tool to analyze clinical parameters taking the behavior and attitude of clinicians into account.1 The impact of this tool is not fully explored in orthopedic and trauma surgery. This educational research aimed to deliver an effective PI program to orthopedic trauma surgeons, neurosurgeons, and radiologists to improve communication and the use of MRI in spinal trauma. Materials and Methods Following a worldwide web session on MRI in spinal injuries to identify the clinical need for an educational intervention, a three-step PI process was defined and implemented over a 6-month period in a hospital department. Opportunities for improvement were identified by applying a 10-item quality checklist to 26 cases. Then a focused educational intervention was delivered to address identified gaps, and a set of 22 post-education cases was compared. Results A total of 26 cases collected before the educational intervention showed several areas for potential improvement. In only 5 of the 26 cases, a specific trauma mechanism or a possible inflammatory or malignant illness was mentioned by the surgeon, where such information may lead to a change in MRI sequence planning. In 23 cases, the radiologist did not believe that the communication led to a change of plan, although sequences other than usual were performed. The educational intervention outlined the data and suggested actions. Comparing the information transfer of the pre- and postinterventional data there was a significant improvement following the intervention ( p = 0.0013). Following the intervention, the communication between surgeons and radiologists significantly influenced the sequences ( p = 0.0152). Conclusion There are specific aspects that may be improved concerning communication between the surgeon and the radiologist. Our PI program was able to demonstrate a significant influence on the behavior and attitude of surgeons and radiologists. In the future, the impact on patient-related outcome parameters has to demonstrate the clinical influence of PI programs in the care of spine patients. References Martin C, Rüetschi U, Cunningham M. Design and implementation of performance improvement programs for orthopedic trauma surgeons. Presented at: AMEE Conference; 2013

Trends in access of plant biodiversity data revealed by Google Analytics.

The amount of plant biodiversity data available via the web has exploded in the last decade, but making these data available requires a considerable investment of time and work, both vital considerations for organizations and institutions looking to validate the impact factors of these online works. Here we used Google Analytics (GA), to measure the value of this digital presence. In this paper we examine usage trends using 15 different GA accounts, spread across 451 institutions or botanical projects that comprise over five percent of the world's herbaria. They were studied at both one year and total years. User data from the sample reveal: 1) over 17 million web sessions, 2) on five primary operating systems, 3) search and direct traffic dominates with minimal impact from social media, 4) mobile and new device types have doubled each year for the past three years, 5) and web browsers, the tools we use to interact with the web, are changing. Server-side analytics differ from site to site making the comparison of their data sets difficult. However, use of Google Analytics erases the reporting heterogeneity of unique server-side analytics, as they can now be examined with a standard that provides a clarity for data-driven decisions. The knowledge gained here empowers any collection-based environment regardless of size, with metrics about usability, design, and possible directions for future development.

A Prevention Model for Session Hijack Attacks in Wireless Networks Using Strong and Encrypted Session ID

Abstract Most of the web applications are establishing the web session with the client. It is very important to protect the wireless networks against session hijacking attack. Session Hijack attack is easy to execute and difficult to detect. Wireless networks do not have specific boundary regions for the packets to be transferred. As the data packets are transferred in air, the chances of sniffing the network packets by the hackers or attackers are high by using the network sniffing tools. In this paper, we have proposed the Strong and Encrypted Session ID to prevent the session hijack attacks in web applications. Session ID is generated and the generated Session ID is encrypted, using a Secret Key Sharing algorithm and decrypted at the client side. We have tested the integrity of the session ID of length 32, 92 and 212 characters in a web application. Attacks are executed to capture the session ID of a web application. Our experimental results proved that 212 characters encrypted session ID completely prevents the session hijack attacks in web applications of wireless networks.

SSM-DENCLUE : Enhanced Approach for Clustering of Sequential Data: Experiments and Test Cases

web usage data is useful to discover interesting patterns related to user traversals, behavior and their characteristics, which helps for the improvement of better Search Engines and Web personalization. Clustering web sessions is to group them based on similarity and consists of minimizing the Intra-cluster similarity and maximizing the Inter-group similarity. The other issue that arises is how to measure similarity between web sessions. There exist multiple similarity measures in the past like Euclidean , Jaccard ,Cosine and many. Most of the similarity measures presented in the history deal only with sequence data but not the order of occurrence of data. A novel similarity measure named SSM(Sequence Similarity Measure) is developed that shows the impact of clustering process ,when both sequence and content information is incorporated while computing similarity between sequences. SSM (Sequence Similarity measure) captures both the order of occurrence of page visits and the page information as well , and compared the results with Euclidean, Jaccard and Cosine similarity measures. Incorporating a new similarity measure, the existing Density clustering technique DENCLUE is enhanced and the new named as SSM-DENCLUE for Web personalization. The Inter-cluster and Intra-cluster distances are computed using Average Levensthien distance (ALD) to demonstrate the usefulness of the proposed approach in the context of web usage mining. This new similarity measure has significant results when comparing similarities between web sessions with other previous measures , and provided good time requirements of the newly developed SSM- DENCLUE algorithms. Experiments are performed on MSNBC.COM website ( free online news channel), in the context of Density based clustering in the domain of Web usage mining.

Refinement and evaluation of web session cluster quality

Refinement of web session clusters is an open research area these days. The basic reason for proposing the refinement algorithm is quite obvious because in any clustering algorithm the obtained clusters shall have some data items that are inappropriately clustered, hence never giving us 100 % quality. This inappropriateness can be improved through refinement and hence enhance the quality of clusters. In the proposed work, initial clusters are formed using K-Means clustering algorithm which suffers from local minima. The refinement on clusters is performed on the basis of access and time features Modified Knockout Refinement Algorithm (MKRA) which is a distance based dissimilarity measure. Refinement is also performed using Genetic Algorithm (GA), Particle Swarm Optimization (PSO), a combination of GA and PSO and a combination of MKRA, GA and PSO. The issue of local minima is overcome by a combination of GA and PSO. GA and PSO both find a true global optimal solution; GA suffers due to a costly fitness function and expensive computational cost which is resolved by PSO implemented in a linear fashion as it has better computational efficiency. Combination of GA and PSO help to overcome the problem of local minima. Results are evaluated on five synthetic datasets and three real datasets. Further it is shown experimentally that effectiveness of combining MKRA with evolutionary techniques produces well separated and cohesive clusters with improved quality. After getting refined clusters the same can be used to provide recommendations to the target user as an application of web usage clusters. Results show that the accuracy of recommender systems using refined clusters is better than the recommender system implemented using original clusters.

An Heighten PSO-K-harmonic Mean Based Pattern Recognition in User Navigation

The website navigation patterns can be searched and analyzed with the introduction of the new methodology. The user navigation path is stored as a sequence of URL categories in web server. The approaches followed are to separate the users and sessions from the web log files and acquiring the necessary patterns for web personalization. The clustering concept is used for grouping the necessary patterns in separate groups. The approaches used for clustering of navigation patterns are done with improvised particle swarm optimization technique which divides users depends on the order in which they request web pages. This approach mines the web log files which are resultant from the web users while interacting with web pages for a particular period of web sessions. The work carried with an optimized method of particle swarm optimization-K-Harmonic means to cluster the similar users based on their navigation pattern. Particle swarm optimization-K-Harmonic method is used to discover or extract user

Investigating the behavior of visually impaired users for multi‐session search tasks

Multi‐session search tasks are complex and span more than one web session. Such tasks are challenging because searchers must keep track of their search progress and the information they encounter across sessions. Multi‐session tasks can be cognitively taxing for visually impaired users because the lack of persistence of screen readers causes the load on working memory to be high. In this article, we first discuss the habitual behavior of visually impaired participants for multi‐session tasks when using popular search interfaces. We then present the evaluation of a search interface developed to support complex information seeking for visually impaired users. The user evaluation was structured in two sessions to simulate a multi‐session task. Thus, we discuss the strategies observed among participants to resume the search, to review previously encountered information, and to satisfy their evolved information need. We also compare the information‐seeking behavior across the two sessions and examine how the proposed interface supports participants for multi‐session tasks. Findings from this evaluation contribute to our understanding of the information‐seeking behavior of visually impaired users and have implications for the design of tools to support searchers to manage and make sense of information during multi‐session search tasks.

Identifying web sessions with simulated annealing

Delivery of efficient service through a web site makes it compulsory in the redesigning stage to take into account the behavior of the users, which can be studied by means of a web log file that partially records information about user visits. The reconstruction of all of the sequences of pages that are visited by users who browse a web site is known as the web sessionization problem, and it has been formulated by means of an integer programming model; however, because a web log can accumulate a large amount of information, it is necessary to reconstruct the sessions over a period of weeks or months, thus the solution to this problem requires a long computational processing time. This paper presents a heuristic approach based on simulated annealing for the sessionization problem. Using this approach, it has been possible to reduce the processing time up to 166 times compared to the time that is required for the integer programming model. Furthermore, the metaheuristic solution finds new optimum values, which achieve increases on the order of 17% in the best cases.

Emerging research areas in SIP-based converged services for extended Web clients

The convergence of Next Generation Networks and Internet-based rich applications are generating relevant industrial opportunities in the market of mobility-enabled services. Even if this trend is widely recognized, there are still a few industrial-level solutions that effectively support session mobility in a transparent way and with the capability of openly integrating with existing and legacy applications. In this paper we propose a SIP-based hybrid architecture for Web session mobility that offers content sharing and session handoff between Web browsers. In addition, its technical originality includes integrating a SIP stack into a Web browser, thus offering the advantage of extending a Web browser to act as a SIP client. Lastly, a rich set of control services that prevent abuse of content sharing and session handoff are introduced into the proposed system. The implemented solution uses SIP in a standard way to migrate Web sessions between Web browsers; it is made up of a SIP integrated Web client and a converged (SIP and HTTP) Application Server that can be easily used to enable session mobility in any kind of Web-based application. In addition, the implemented system has recently evolved to a framework for developing different kinds of converged services over the Internet, analogously to what is possible with Google Wave and the existing telephony APIs. Finally, the paper reports the evaluation of the proposed framework and of the employed technologies, together with directions of future work, in terms of both extension to other application domains and exploration of research areas/models that can benefit form the adoption of SIP and Web-related solutions.

Design and Realization of the Component of Single Sign-On Based on Web Services and Session Verification

Single Sign-on is one of the most popular solutions for integrating enterprise business. In this paper, a component of SSO based on Web Services technology and Session state authentication mechanisms is designed and implemented, and this component is used in the ceramic industry integration services platform to address the problem of repeatedly login when various company users use multiple applications in the ceramic industry integration services platform.

An empirical investigation of Web session workloads: Can self-similarity be explained by deterministic chaos?

Several studies of Web server workloads have hypothesized that these workloads are self-similar. The explanation commonly advanced for this phenomenon is that the distribution of Web server requests may be heavy-tailed. However, there is another possible explanation: self-similarity can also arise from deterministic, chaotic processes. To our knowledge, this possibility has not previously been investigated, and so existing studies on Web workloads lack an adequate comparison against this alternative. We conduct an empirical study of workloads from two different Web sites: one public university, and one private company, using the largest datasets that have been described in the literature. Our study employs methods from nonlinear time series analysis to search for chaotic behavior in the web logs of these two sites. While we do find that the deterministic components (i.e. the well-known “weekend effect”) are significant components in these time series, we do not find evidence of chaotic behavior. Predictive modeling experiments contrasting heavy-tailed with deterministic models showed that both approaches were equally effective in modeling our datasets.

Automatic object-oriented coding facility for product life cycle management of discrete products

Discrete products are produced in enormous quantity and diversity all over the world. A global collaborative manufacturing environment requires the minimisation of environmental impact that these products shall ultimately pose. The implementation of an efficient product life cycle management system that encapsulates complete historical information about the product shall prove useful. This information may pertain to the design methodology, material type, details regarding manufacturing methods, use of coating or paints and exposure to radiation, chemicals of varying pH and electroweak forces during production or use. It is essential to have access to this information when the product is in use or in the disassembly stage at the end of the useful life of a product to accomplish the proper reuse or disposal of each component. A coding system that embodies the product life cycle stages for discrete products is envisaged. The proposed coding system stores parameters that are related to the design, manufacture, usage and disposal of a product. A computer programme is developed to establish a product life cycle code (PLCC) in the form of a 256-bit binary number or 64-bit hexadecimal number. The code can be allocated to a component or product at its inception in an interactive web session and stored in a repository for record keeping. The cradle-to-grave binary or hexadecimal code becomes an essential part of each component and product and facilitates the usage, disassembly and disposal of each component. A case study related to the generation of PLCC for discrete products is included towards the end of the article.

Online risk-based authentication using behavioral biometrics

In digital home networks, it is expected that independent smart devices communicate and cooperate with each other, without the knowledge of the fundamental communication technology, on the basis of a distributed operating system paradigm. In such context, securing the access rights to some objects such as data, apparatus, and contents, is still a challenge. This paper introduces a risk-based authentication technique based on behavioral biometrics as solution approach to tackle this challenge. Risk-based authentication is an increasingly popular component in the security architecture deployed by many organizations to mitigate online identity fraud. Risk-based authentication uses contextual and historical information extracted from online communications to build a risk profile for the user that can be used accordingly to make authentication and authorization decisions. Existing risk-based authentication systems rely on basic web communication information such as the source IP address or the velocity of transactions performed by a specific account, or originating from a certain IP address. Such information can easily be spoofed, and as such, put in question the robustness and reliability of the proposed systems. In this paper, we propose a new online risk-based authentication system that provides more robust user identity information by combining mouse dynamics and keystroke dynamics biometrics in a multimodal framework. We propose a Bayesian network model for analyzing free keystrokes and free mouse movements involved in web sessions. Experimental evaluation of our proposed model with 24 participants yields an Equal Error Rate of 8.21 %. This is very encouraging considering that we are dealing with free text and free mouse movements, and the fact that many web sessions tend to be very short.

Indirect Positive and Negative Association Rules in Web Usage Mining

One of the purposes of Web usage mining is to find out interesting user association rules from web server logs. It has become vital for personalization, effective web site management, business and support services, creating adaptive web sites, and so on. In the web domain, items correspond to pages and transactions to user sessions. Indirect associations, type of infrequent pattern provide useful insight into the data. The concept of indirect association is to indirectly connect two rarely co-occurred pages via a third page called transitive page. Mining positive and negative association rules in web usage data become a hot spot. So, these all information leads find new approach for discovering efficient rules for web. Indirect positive and Negative Association Rules are discussed here which can be used for Web Recommendation, personalization etc. Mining indirect positive and negative association rules for the web is explored very little so far in the research work. The presented Proposed Approach of algorithm is to extract the positive and negative association rules from web session log file and then discover the indirect positive and negative association rules from it.

Modeling Web Session for Detecting Pseudo HTTP Traffic

More and more Internet services and applications are transferred by the HTTP protocol due to its openness. This brings new challenges to the security management of network boundary. In this paper, a new approach is proposed to detect the pseudo Web behavior which abuses the general HTTP protocol to pass through the network boundary. A new parameter is defined to extract the features of Web-session based on the inter-arrival time of HTTP requests. A nonlinear mapping function is introduced to protect the weak signals from the interference of the infrequent large values. An hidden Markov model with state duration is applied to describe the normal access behavior of Web sessions. The proposed model is dynamic, and does not rely on presupposed threshold and client- or server-side data which are widely used in traditional session detection approaches. An objective function is derived for predicting the near future behavior of a user's Web-session. The deviation between the prediction result and the real observation is used for detecting the pseudo Web behavior. Experiments based on real HTTP traces from large-scale Web proxies are implemented to valid the proposal.