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Nowadays, many technology-based applications and systems embedded with cybercrimes threats and risks. Our communities lack the basic skills to secure against a smart cybercrime threats. This study conducted to test and evaluate the current cybercrime risks and awareness in Alnamas area, a district in the Southern part of Saudi Arabia. The study targeted a set of users who are highly familiar in using...
User attribution process based on human inherent dynamics and preference is one area of research that is capable of elucidating and capturing human dynamics on the Internet. Prior works on user attribution concentrated on behavioral biometrics, 1-to-1 user identification process without consideration for individual preference and human inherent temporal tendencies, which is capable of providing a...
The paper explores the main directions in which the augmented reality and the Web can change the approach in power engineering and significantly improving it. These innovations facilitate, in a user-friendly way, the availability of real-time data, fast processed information, assistance and guidance at any time and in any place along the entire energy chain. A step-by-step implementation of AR applications...
In the age of big data, "Internet plus traffic" pattern, which is deeply integrated new generation information technology with transportation, has become the effective method to improve urban traffic. Combined the problems existed in technology integration with innovative application of traffic big data, this paper puts forward transformation strategy of traffic planning technology from...
This research work presents new trends in cyber threats, and it also quantifies user awareness of web threats and attacks. Using an online questionnaire information for the analysis of whether individuals had adequate knowledge of internet threats and attacks in order to safeguard themselves was obtained. The survey showed that many users lack an adequate understanding of what to do and what not to...
Online reviews are becoming one of the vital components of e-commerce in recent years as so many people consider having different opinions prior to buying online products or apprehending any online service. Nowadays, in the era of web 2.0, it is completely understandable that people rely on online reviews more than ever while taking a decision. However, guaranteeing the authenticity of these sensitive...
In this work, we discuss utility of Restricted Boltzmann Machine (RBM) in face-deidentification challenge. GRBM is a generative modeling technique and its unsupervised learning provides vantage of using raw faces data. Faces are deidentified by reconstructed face images from the trained GRBM model. The reconstructed image uses random information from the stochastic units which makes it hard to re-identify...
Behavior-based tracking is an unobtrusive technique that allows observers on the Internet to monitor user activities over long periods of time - in spite of changing IP addresses. Our technique uses semi-supervised machine learning, which allows observers to track users without the need for multiple labeled training sessions. We present evaluation results obtained on a realistic dataset that contains...
Wikipedia is one of the fastest growing websites and a primary source of knowledge on the Internet. Being a wiki, its content is crowd-sourced by the users. This has many benefits and it is one of the main reasons it has grown to reach more than 5 million articles in its English version. Nevertheless, this also raises issues, like the overlinking of articles, which are difficult to deal with by editors...
Comparable corpora contain significant quantities of useful data for Natural Language Processing tasks, especially in the area of Machine Translation. They are mainly the source of parallel text fragments. This paper investigates how to effectively extract bilingual texts from comparable corpora relying on a small-size parallel training corpus. We propose a new technique to filter non parallel articles...
Scholarships and financial aids in modern universities are the basic administrative plans to ensure and promote the completion of academic training and studies for students. Traditional grants allocation procedures are based on manual determination, which costs lots of human resources. In this paper, we investigate an assistance model for helping improve the scheme of granting. We first collect students...
The fifth Dialog State Tracking Challenge (DSTC5) introduces a new cross-language dialog state tracking scenario, where the participants are asked to build their trackers based on the English training corpus, while evaluating them with the unlabeled Chinese corpus. Although the computer-generated translations for both English and Chinese corpus are provided in the dataset, these translations contain...
Named Data Networking (NDN) ambitions the rank of Future Internet Architecture in uniquely addressing content items by their name. In NDN, routers forward Interests for content after finding Longest-Prefix Matches (LPM) of content names in their Forwarding Information Base (FIB). However, the scalability of this structure is challenged by the huge global Internet namespace. In this paper, we propose...
Many telecommunication companies today have actively started to transform the way they do business, going beyond communication infrastructure providers are repositioning themselves as data-driven service providers to create new revenue streams. In this paper, we present a novel industrial application where a scalable Big data approach combined with deep learning is used successfully to classify massive...
This electronic document is a “live” template and already defines the components of your paper [title, text, heads, etc.] in its style sheet. Sentiment classification is one of the research hot spots of Natural Language Processing. Compared with English and Chinese, it is hard for Tibetan to do some research of sentiment analysis because of the situation that we are lack of related sentiment corpus...
The study investigated accessibility to and utilization of electronic resources among pre-service teachers in the National Open University of Nigeria (NOUN). Survey research design was used to carry out the study. Two hundred and thirty eighty (238) undergraduate students studying to obtain Bachelor of Education (B.Ed.) by distance were purposively sampled from Ibadan Study Centre of the institution...
The availability of rich datasets is a pre-requisite for proposing robust sentiment analysis systems. A variety of such datasets exists in English language. However, it is rare or nonexistent for the Arabic language except for a recent LABR dataset, which consists of a little bit over 63,000 book reviews extracted from. Goodreads. com. We introduce BRAD 1.0, the largest Book Reviews in Arabic Dataset...
This paper presents initial research on English-to-Tigrinya statistical machine translation (SMT). Tigrinya is a highly inflected Semitic language spoken in Eritrea and Ethiopia. Translation involving morphologically complex languages is challenged by factors including data sparseness, word alignment and language model. We try to address these problems through morphological segmentation of Tigrinya...
This work focuses on two specific types of sentimental information analysis for traditional Chinese words, i.e., valence represents the degree of pleasant and unpleasant feelings (i.e., sentiment orientation), and arousal represents the degree of excitement and calm (i.e., sentiment strength). To address it, we proposed supervised ensemble learning models to assign appropriate real valued ratings...
This paper presents the IALP 2016 shared task on Dimensional Sentiment Analysis for Chinese Words (DSAW) which seeks to identify a real-value sentiment score of Chinese words in the both valence and arousal dimensions. Valence represents the degree of pleasant and unpleasant (or positive and negative) feelings, and arousal represents the degree of excitement and calm. Of the 22 teams registered for...
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