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Due to the spread of unreliable online information on social network services (SNS), the users are faced with a difficult problem for determining if the information is trustworthy or not. At present, the users should make a decision overall by themselves for trustworthiness of information. Therefore, we need a way to systematically evaluate trustworthiness of information on SNS. In this paper, we...
In this paper we come up with a novel approach for the early detection of events in blog entries. The detection of trend is already discussed pretty often. Nevertheless, in our understanding the detection of events goes one step further. The presented algorithms detects unique happenings at a given point in time by perceiving unusual frequent occurrences of words or word groups. We introduce an implementation...
As described in Michael Lewis' Money ball: The Art of Winning an Unfair Game, a baseball player's On Base Percentage is a good metric for rating players' usefulness or productivity. What metrics can be used for gauging a professor's performance? Is there a correlation between salary and these metrics? Are these metrics more accurate for certain fields of study? Is the currently popular practice of...
In recent years, wireless communication technologies and accurate positioning devices enable us to enjoy various types of location-based services. However, revealing users location information to potentially untrusted LBS providers is one of the most significant privacy threats in location-based services. The dummy-based privacy-preserving approach is a popular technology that can protect real trajectories...
Using page-level metrics of a randomly selected group of 15,625 among the top 100,000 Face book check-in locations which rank high in terms of customer engagement, we explore if the short-term dynamical information on these metrics could deliver, via a clustering approach, some new insights for marketing decision making. Using a highly-scalable clustering algorithm, statistical methods, and combinatorial...
We propose a Cloud Advisor framework that couples two salient features: trustworthiness and transparency measurement. It provides a mechanism to measure trustworthiness based on the history of the cloud provider taking into account evidence support and to measure transparency based on the Cloud Controls Matrix (CCM) framework. The selection process is based on a set of assurance requirements that...
Reforms in the educational system emphasize more on continuous assessment. The descriptive examination question paper when compared to objective question paper acts as a better aid in continuous assessment for testing the progress of a student under various cognitive levels at different stages of learning. Unfortunately, assessment of descriptive answers is found to be tedious and time consuming by...
Colleges and universities are increasingly interested in tracking student progress as they monitor and work to improve their retention and graduation rates. Ideally, early indicators of student progress, or lack thereof, can be used to provide appropriate interventions that increase the likelihood of student success. In this paper we present a framework that uses machine learning, and in particular,...
In this paper we explore and analyse the heterogeneity existent within a seemingly homogenous sample of online consumer behaviours in terms of their demographic profile. The data from a sample of 371 survey respondents is clustered using various distance functions and a clustering algorithm. In doing so, the respondents are clustered based on their response profiles to online behaviour questions rather...
Collaborative filtering (CF) over large datasets requires significant computing power. Due to this data owning organizations often outsource the computation of CF (including some abstraction of the data itself) to a public cloud infrastructure. However, this leads to the question of how to verify the integrity of the outsourced computation. In this paper, we develop verification mechanisms for two...
Cassuto and Blaum proposed new error correcting codes which are called symbol-pair codes. They gave a coding framework for channels whose outputs are overlapping pairs of symbols in storage applications. It is called symbol-pair read channel. The pair distance and pair error are used in symbol-pair read channel. Cassuto et al. and showed Yaakobi et al. presented decoding algorithms for symbol-pair...
There are many examples in the literature of scorecards derived from clinical data. These scorecards are proposed for use by health professionals to stratify patients into risk categories and are often compared using receiver operating characteristic (ROC) curves and their associated areas (AUC). This paper analyses random scorecards and shows that the underlying distributions and therefore statistical...
Adverse drug reactions (ADRs) are a main cause of hospitalization and deaths worldwide. These unanticipated episodes are generally infrequent, but almost all existing ADR signaling techniques are designed to use dataset extracted from spontaneous reporting systems or employed a predefined type of information (e.g., drugs), which suffer from failures to detect unexpected and latent ADRs. In this paper,...
High-dimensional torus networks are becoming common in flagship HPC systems, with five of the top ten systems in June 2014 having networks with more than three dimensions. Although such networks combine performance with scalability at reasonable cost, the challenge of how to achieve optimal performance remains. Tools are needed to help understand how well the traffic is distributed among the many...
Data grids provide distributed resources for dealing with large scale applications generating huge volume of data that require to be efficiently managed, shared and analyzed. Data replication is a useful technique to solve these tasks since it allows minimizing data access time through creating many replicas and storing them in appropriate locations. Several replication strategies have been proposed...
Penetration graph is a kind of attack graph which is widely used in penetration testing. It is an import tool to analyze security vulnerabilities in the network. However, the previous research on the generation methods of penetration graph have met a lot of challenges. Some methods are out of date and not applicable for practical scenarios, some may possibly leave out the import attack paths, some...
Improving resilience against failures and targeted attacks is an important aspect of network design. The resilience and cost of networks are two opposing objectives in which a designer should consider when building networks. We develop a heuristic algorithm that balances the centrality of networks by adding a set of links that minimizes the variance of graph centrality measures in a least costly fashion...
This work is part of the “eSience” project, which is realized in the framework of Tempus project, coordinated by Bordeau university and financed by the European Union. The “eSience” project aims to create a network of online labs in the maghrebian countries.
Along with the increasing popularity of social web sites, users rely more on the trustworthiness information for many online activities among users. However, such social network data often suffers from severe data sparsity and aren't able to provide users with enough information. Therefore, trust prediction has emerged as an important topic in social network research. Nowadays, trust prediction is...
Collaborative Filtering (CF) is one of the most successful recommendation techniques. Regardless of its success, it still suffers from some weaknesses such as data sparsity and user cold-start problems, resulting in poor recommendation accuracy and reduced coverage. Trust-based recommendation methods incorporate the additional information from the user's social trust network into collaborative filtering...
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