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In our era, most of the communication between people is realized in the form of electronic messages and especially through smart mobile devices. As such, the written text exchanged suffers from bad use of punctuation, misspelling words, continuous chunk of several words without spaces, tables, internet addresses etc. which make traditional text analytics methods difficult or impossible to be applied...
One of the most interesting tasks in social network analysis is link prediction. There are a lot of studies dealing with link prediction task in the literature. In recent years, there is an increasing on link prediction methods trying to model network as more close to real networks such as heterogeneous, temporal and directed network models to gain better link prediction performance. Many of the existing...
Acquired immune deficiency syndrome (AIDS) is the last and the most life-threatening phase of Human Immunodeficiency Virus (HIV) disease. HIV attacks and heavily affects the immune system of the body which remains unable to resist the disease. HIV uses white blood cells to replicate itself and spreads everywhere in the body. The lifecycle of HIV disease, especially the replication stage must be prominently...
Link prediction is a well-known problem in field of social network analysis which intends to guess the likelihood of the occurrences of connections between nodes. By using the structure of the network up to a given time appearance of links in future can be predict. In the most of previous studies, for performing the link prediction task just according to the exploration of the state of the network...
Monitoring and management of large scale applications is already a complex task because of syntactic and unstructured nature of execution data. Traditional application monitoring and management solutions focused on employing analysis techniques on unstructured and syntactic log information become limited as unstructured information cannot be well utilized to find out related events information or...
This paper presents for the first time decision fusion for multimodal biometric system using social network analysis (SNA). The main challenge in the design of biometric systems, at present, lies in unavailability of high-quality data to ensure consistently high recognition results. Resorting to multimodal biometric partially solves the problem, however, issues with dimensionality reduction, classifier...
One of the issues with using social networks for analysis is the problem of having missing nodes in the network. Having missing nodes can significantly impact the results of the analysis, and should be avoided as much as possible. For social network analysis to be more effective for criminal networks, where there are likely missing nodes, the number of missing nodes needs to be reduced. This research...
Making investment decision on various available stocks in the market is a challenging task. Econometric and statistical models, as well as machine learning and data mining techniques, have proposed heuristic based solutions with limited long-range success. In practice, the capabilities and intelligence of financial experts is required to build a managed portfolio of stocks. However, for non-professional...
Between 2000 and 2010, the Canadian federal government disbursed $716 893 740 in research grants through the Natural Sciences and Engineering Research Council of Canada (NSERC)'s Research Partnerships Programs. This is only one branch, of one agency, in the immense bureaucracy of government funding. This study will examine the social networks which resulted from these research grants. Over this eleven...
The application of social network analysis (SNA) and mining in health care domains has recently received a considerable attention for its key role in understanding how doctors form communities, and how they are socially connected with each other. This understanding helps enhance organizational structures and process flows. In this paper, we show how SNA techniques can solve issues in the medical referral...
Recommender systems aim to facilitate World Wide Web users against information and product overloading. They are usually intermediate programs that try to predict users' preferences and items of their interest. In this paper, we present a hybrid framework that uses open source information such as web logs in combination with social network analysis and data mining, to extract useful information about...
The web has emerged rapidly into a valuable source of information. Web visitors leave trace behind them which is used by web site owners for knowledge discovery. The latter information guides site owners in deciding how to organize the information in their website and how to provide the best for their visitors in order to maximize their profit. Various mining techniques combined with machine learning...
Prediction is one of the most attractive aspects in data mining. Link prediction has recently attracted the attention of many researchers as an effective technique to be used in social network analysis to understand the associations between nodes in social communities. It has been shown in the literature that the link prediction technique is limited to predict the existence of the links in the future...
Searching for the right information over the Web is not straight-forward. In the era of high speed internet, high capacity networks, and interactive Web applications, it has become even easier for the users to publish data online. A huge amount of data is published over the internet; every data is in the form of web pages, news, blogs and other material, etc. Similarly, for search engines like Google...
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