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Improving and assessing knowledge on a topic is need of the current generation. In the traditional system, experts create assessments manually by reading articles and generating questions on a topic. However, it is very effort and time consuming to read and create questions for every article. Therefore, learners find it difficult to assess their knowledge on a topic owing to no- or low-availability...
The amount of data circulating on the Internet is increasing day by day. With the increasing use of social media in particular, the importance of analyzing these data is increasing. The use of machine learning approaches to analyze large amounts of data is still popular today. Today, the social network Facebook is the most popular social networking sites. In this study, some data taken on Facebook...
This article presents a survey of the factors that indicate evasion in distance education, as well as the data mining techniques that are being used in the detection of evasion. As a methodology, we have used the systematic review, analyzing the works published in the last five years. The result indicated that there are multiple factors that influence evasion, which were systematized in four dimensions,...
In big data environment, the performance of the focused crawler has a great impact on the results of crawling. In order to improve the efficiency and accuracy of focused crawler, this paper proposed a combination method of HTML analysis and text density and multi-reference factors similarity calculation method based on the basic principle and key technologies of focused crawler. The proposed method...
With the Internet applications become more complex and diverse, simple network traffic matrix estimation or approximation methods such as gravity model are no longer adequate. In this paper, we advocate a novel approach of approximating traffic matrices with multiple low-rank matrices. We build the theory behind the MULTI-LOW-RANK approximation and discuss the conditions under which it is better than...
The article is devoted to the study of the method of self-learning of an artificial intelligence, based on the use of software tools for collecting information from various Internet resources. There is developed a web crawler that analyzes Internet resources for the presence of false articles by data mining methods based on an artificial intelligence and by self-learning through the mechanism of neural...
The article deals with the development of technology for extraction and processing of statistical information of private sector of regional healthcare. The concept of data mining from various sources in the Internet, methods of extraction and integration of information about medical organizations of private sector of regional healthcare are presented.
In the era of the Internet, people are active in multiple online services, and they usually have accounts on more than one online service. Each account is a virtual identity of the user. In order to trace individual's online behavior at any time and any places, linking virtual identities belonging to the same natural person across different online service domains is very important. Existing methods...
With the rapid development of Internet, how to obtain valuable information from massive messages has become a major problem we need to be solved in the information explosive era. This paper introduces the development route of information extraction technology, and discusses four categories of Chinese entity relation extraction technologies in depth. Finally, the advantages and disadvantages of different...
In this paper, the significance role of data warehouse designing for textual anti-plagiarism system is investigated. The paper covers the central issues of data warehousing modeling including: (1) formulating the data representation, (2) establishing the foundations of storage structure, (3) proposing corresponding architecture allowing to store, update and manage data. Consequently, two levels are...
Wikis are widely used collaborative environments as sources of information and knowledge. The facilitate students to engage in collaboration and share information among members and enable collaborative learning. In particular, Wikis play an important role in capstone projects. Wikis aid in various project related tasks and aid to organize information and share. Mining project Wikis is critical to...
With the evolution of internet, there has been an unprecedented and unlimited growth in volume, velocity, veracity and variety of the data and the complexity of data attributes is on the rise. Further, in the domain of internet, data is not geo-centric any longer and multiple locations are contributing to the data acquisition technologies including but not limited to packet captures, data logs, routing...
The rapid development of the Internet has brought great convenience to users, but it also brought a lot of troubles to the users' information privacy exposure. This study selects the basic information of 300 users on FACEBOOK social media to cluster analysis. The data sets of users are divided into five groups by experiment, and the clustering results are classified and then discussed. By the analysis...
Synonyms extraction is a fundamental research, which is helpful to text mining and information retrieval. In this paper, we propose method to extract synonymy from text, the method employs spectral clustering and word2vec. First, the word2vec model is trained by a large-scale English Wikipedia corpus. Then, we extract keywords from a text and use the trained model to generate similarities among these...
Knowledge graph technology belongs to the field of artificial intelligence. It is widely used in semantic search and intelligent question answering. Construction of Uyghur's knowledge graph has the great value of Uyghur information processing and Uyghur application software development. Firstly, this paper describes the definition and structure of the knowledge graph, then it reviews the related research...
User profiling is a typical big data service created and utilized by an increasing number of Internet venders, which maintains a customized model of interests or essential attributes of their existing users by looking for insights into their behaviors. The Internet industry's best practices indicate that user profiles can help venders much more sufficiently understand their customers. As a result,...
With the rapid development of the Internet, massive Internet text data has brought new opportunities and challenges to the research of entity relation extraction. Open entity relation extraction overcomes the shortage of traditional methods, that relation types need to be predefined and plenty of training data need to be labeled in advance. A lot of work have been done for English Open ERE, and now...
It is believed that technology will take over the day to day life of human begin. No one can remain isolated from the adaptation of technology. Hence it is the need of the hour to introduce a technology which will do the day to day life tasks in human life with smart and intelligent way. Hence, this paper critically discuss the emergence and progress of Internet of Every Things (IoET) as the next...
Conflagration is one of the major disasters that threatens human life and property. If the proper action is not taken in detecting the symptom of conflagration events ahead of time, the number of such disasters will keep increasing. An effective solution in this context will alleviate many fire-related global problems to a great extent. Although fire detectors are not available in many places, WiFi...
In this paper, we propose a new version of the LBRW (Learning based Random Walk), LBRW-Co, for predicting users co-occurrence based on mobility homophily and social links. More precisely, we analyze and mine jointly spatio-temporal and social features with the aim to predict and rank users co-occurrences. Experiments are performed on the Foursquare LBSN with accurate and refined measurements. Experimental...
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