Sharif Digital Repository

So far several methods have been proposed for clustering the web. On the other hand, many algorithms have been developed for clustering the relational data, but their usage for the Web is to be investigated. One main category of such algorithms is density based methods providing high quality results. In this paper first, a new density based algorithm is introduced and then it is compared with other algorithms of this category. The proposed algorithm has some interesting properties and capabilities such as hierarchical clustering and sampling, making it suitable for clustering the web data. © Springer-Verlag Berlin Heidelberg 2007  

Clustering is one of the most important approaches for mining and extracting knowledge from the web. In this paper a method for clustering the web data is presented which using a Bayesian network, finds appropriate representatives for each of the clusters. Having those representatives, we can create more accurate clusters. Also the contents of the web pages are converted into vectors which firstly, the number of dimensions is reduced, and secondly the orthogonality problem is solved. Experimental results show about the high quality of the resultant clusters. © Springer-Verlag Berlin Heidelberg 2007  

Using mixed method research the current study has analyzed Iranian researchers' information searching behavior on the Web. Based on extracted concepts, the model of their information searching behavior was revealed. Forty-four participants, including academic staff from universities and research centers were recruited for this study selected by purposive sampling. Data were gathered from questionnaires including ten questions and semi-structured interview. Each participant's memos were analyzed using grounded theory methods adapted from Strauss & Corbin (1998). Results showed that the main objectives of subjects were doing a research, writing a paper, studying, doing assignments, downloading... 

Recommendation plays an increasingly important role in our daily lives. Recommender systems automatically suggest items to users that might be interesting for them. Recent studies illustrate that incorporating social trust in Matrix Factorization methods demonstrably improves accuracy of rating prediction. Such approaches mainly use the trust scores explicitly expressed by users. However, it is often challenging to have users provide explicit trust scores of each other. There exist quite a few works, which propose Trust Metrics to compute and predict trust scores between users based on their interactions. In this paper, first we present how social relation can be extracted from users'... 

Recommender Systems have become an attractive field within the recent decade because they facilitate users' selection process within limited time. Conventional recommender systems have proposed numerous methods focusing on recommendations to individual users. Recently, due to a significant increase in the number of users, studies in this field have shifted to properly identify groups of people with similar preferences and provide a list of recommendations for each group. Offering a recommendations list to each individual requires significant computational cost and it is therefore often not efficient. So far, most of the studies impose four restrictive assumptions: (1) limited number of... 

Recommendation plays an increasingly important role in our daily lives. Recommender systems automatically suggest items to users that might be interesting for them. Recent studies illustrate that incorporating social trust in Matrix Factorization methods demonstrably improves accuracy of rating prediction. Such approaches mainly use the trust scores explicitly expressed by users. However, it is often challenging to have users provide explicit trust scores of each other. There exist quite a few works, which propose Trust Metrics to compute and predict trust scores between users based on their interactions. In this paper, first we present how social relation can be extracted from users'... 

In this research, a web-based simulator is developed, which can be used for generating image sequences of moving spermatozoa cells. It can be used for assessment of multiple object tracking algorithms, especially Computer Aided Sperm Analysis (CASA) systems. The developed software has many useful parameters such as blurring images or adding noise and it also gives full control of sperm counts and types. To illustrate performance of the developed simulator, three parameters (spermatozoa population, standard deviation of Gaussian blur filter and noise intensity) have been swept and the results of three different multiple object tracking algorithms were compared as an application of this... 

Nowadays web services composition that presents capabilities in response to customers' complex requirements has a special importance in real businesses. However, service choreography as a form of service composition, still faces many challenges. One of the most important challenges of the choreography domain is how to validate the model based on the corresponding requirements. To this end, in this paper processes choreographies are modeled using the interaction view of BPMN 2.0 standard. Then, goal modeling is suggested to extract the requirements. For each requirement all possible valid scenarios are considered and finally using Savara tool, the requirements' scenarios are modeled and the... 

Motivated by the problem of automatically composing network accessible services, such as those on the World Wide Web, this paper proposes an approach to exploit all semantic information available for semantic web services to complete this task. For semantic web services, we propose a prioritized and limited list of other web services, with composability measure value based on feasibility of being succeeding service in a composition to fulfill the request. Due to the fact that in semantic web services, semantic information- all description and signatures- is defined by ontology language, we use some of the mapping rules to estimate a correlation between services for composability. Then we... 

Internet banking is a tool to achieve competitive advantage and its usage has been spreading rapidly in recent years. This paper strives to identify a comprehensive study of the major internet banking quality measurements, which covers a wide range of literature relevant to international papers and scholars and then evaluate them through using a precise method, Shannon entropy. At the last stage the validated criteria were exploited to survey in Iranian banks. The empirical research consists of a quantitative study of internet banking by a sample of employees in two banks of Iran. In this regard, the raised question is about whether or not the internet banking is a strategic information... 

Exceptions are an indispensable part of the software development process. However, developers usually rely on imprecise results from a web search to resolve exceptions. More specifically, they should personally take into account the context of an exception, then, choose and adapt a relevant solution to solve the problem. In this paper, we present Exception Tracer, an Eclipse plug in that helps developers to resolve exceptions with respect to the stack trace in Java programs. In particular, Exception Tracer automatically provides candidate solutions to an exception by mining software systems in the Source Forge, as well as listing relevant discussions about the problem from the Stack Overflow... 

Context Event-Driven Software (EDS) is a class of software whose behavior is driven by incoming events. Web and desktop applications that respond to user-initiated events on their Graphical User Interface (GUI), or embedded software responding to events and signals received from the equipment in its operating environment are examples of EDS. Testing EDS poses great challenges to software testers. One of these challenges is the need to generate a huge number of possible event sequences that could sufficiently cover the EDS's state space. Objective In this paper, we introduce a new six-stage testing procedure for event-driven web applications to overcome EDS testing challenges. Method The... 

One of the important yet insufficiently studied subjects in fair allocation is the externality effect among agents. For a resource allocation problem, externalities imply that the share allocated to an agent may affect the utilities of other agents. In this paper, we conduct a study of fair allocation of indivisible goods when the externalities are not negligible. Inspired by the models in the context of network diffusion, we present a simple and natural model, namely network externalities, to capture the externalities. To evaluate fairness in the network externalities model, we generalize the idea behind the notion of maximin-share (MMS) to achieve a new criterion, namely,... 

In real-world networks, nodes might have more than one type of relationship. Signed networks are an important class of such networks consisting of two types of relations: positive and negative. Recently, embedding signed networks has attracted increasing attention and is more challenging than classic networks since nodes are connected by paths with multi-types of links. Existing works capture the complex relationships by relying on social theories. However, this approach has major drawbacks, including the incompleteness/inaccurateness of such theories. Thus, we propose network transformation based embedding to address these shortcomings. The core idea is that rather than directly finding the... 

Graph data structures are fundamental for studying connected entities. With an increase in the number of applications where data is represented as graphs, the problem of graph generation has recently become a hot topic. However, despite its significance, conditional graph generation that creates graphs with desired features is relatively less explored in previous studies. This paper addresses the problem of class-conditional graph generation that uses class labels as generation constraints by introducing the Class Conditioned Graph Generator (CCGG). We built CCGG by injecting the class information as an additional input into a graph generator model and including a classification loss in its... 

A web attack is an attack against a web server through the HTTP Protocol. By analyzing known web attacks, we find out that each one has its own behavior. Vestiges of their behavior could be detected in non-body parts of the HTTP Protocol. Such information can be used to verify web alerts generated by Web Application Firewalls (WAFs) and Web Intrusion Detection Systems (Web IDSs). In this paper, we propose a method to verify web alerts generated by mentioned sensors. The goal of the alert verification component is to eliminate or tag alerts that do not represent successful attacks. Our approach is based on analyzing HTTP Transaction metadata, including Request method, Request Headers, Status... 

Many real-world systems and applications such as World Wide Web, and social interactions can be modeled as networks of interacting nodes. However, in many cases, one encounters the situation where the pattern of the node-to-node interactions (i.e., edges) or the structure of a network is unknown. We address this issue by studying the Network Reconstruction Problem: Given a network with missing edges, how is it possible to uncover the network structure based on certain observable quantities extracted from partial measurements? We propose a novel framework called CS-NetRec based on a newly emerged paradigm in sparse signal recovery called Compressive Sensing (CS). The results demonstrate that... 

Clustering has become an increasingly important and highly complicated research area for targeting useful and relevant information in modern application domains such as the World Wide Web. Recent studies have shown that the most commonly used partitioning-based clustering algorithm, the K-means algorithm, is more suitable for large datasets. However, the K-means algorithm may generate a local optimal clustering. In this paper, we present novel document clustering algorithms based on the Harmony Search (HS) optimization method. By modeling clustering as an optimization problem, we first propose a pure HS based clustering algorithm that finds near-optimal clusters within a reasonable time.... 

Web Engineering has been enriched with processes and modeling languages that focus on the specific features of web-based systems, taking into account the special requirements and constraints that are associated with this specific context. Process Patterns, on the other hand, represent elements of knowledge and experience in software engineering; they also act as reusable method chunks that can be used for constructing bespoke methodologies that are tailored to fit specific project situations. We propose a set of process patterns based on current web development practices. A number of prominent web development methodologies have been studied, and a set of process patterns has been elicited... 

"Web 2.0" refers to a second generation of web development and design, that facilitates communication, secure information sharing, interoperability, and collaboration on the World Wide Web. The truth is that Web 2.0 is a difficult term to define, even for web experts. Usually phrases like "the web as platform" and "architecture of participation" are used to describe this term. Examples of Web 2.0 include web-based communities, hosted services, web applications, social-networking sites, video-sharing sites, wikis, blogs, mashups and folksonomies. The Internet is changing medicine and Web 2.0 is the current buzz word in the World Wide Web dictionary. Radiology in the Web 2.0 probably refers to...