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Internet and Social media are widely used by terrorist organizations to spread their ideas and recruit foreign fighters. The aim of SAFFRON project is to build a system able to support early detection of foreign fighters' recruitment by terrorist groups in Europe. It consists in studying recruitment communication strategies on social media (e.g. narrations, argumentative tropes and myths used), and...
Aspect-based sentiment analysis summarizes what people like and dislike from reviews of products or services. In this paper, we adapt the first rank research at SemEval 2016 to improve the performance of aspect-based sentiment analysis for Indonesian restaurant reviews. We use six steps for aspect-based sentiment analysis i.e.: preprocess the reviews, aspect extraction, aspect categorization, sentiment...
For many students, course recommendation is a troublesome problem. To choose satisfying courses when they only have a little of information about the courses, they have to turn to common course schedule systems for help, but the result is disappointing. To solve the problem, the method of scoring similarity of courses and clustering courses based on course descriptions is presented. Different from...
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...
A set of actors may take part in numerous categories of real-life social networks. For instance an actor may take part in a mobile social network and a friendship network. The interactions between actors in the mobile social network may not be reproduced in the friendship one. We accept that overlaying networks with different kinds of interactions assists on detecting interesting patterns. The main...
Along with the popularity of the internet, contents inside web databases also increase quickly. These data, hidden behind the query interfaces, are called deep web. These contents normally are not collected by the search engines. Many deep web contents related applications, like contents collection, topic-focused crawling, and data integration, are based on understanding the schema of these query...
With the popularity of social media (e.g., Facebook and Flicker), users can easily share their check-in records and photos during their trips. In view of the huge number of user historical mobility records in social media, we aim to discover travel experiences to facilitate trip planning. When planning a trip, users always have specific preferences regarding their trips. Instead of restricting users...
Frameworks are popularly used to reduce implementation complexity and improve productivity. Unfortunately, most frameworks are quite complex and not well documented. Hence, correctly and effectively programming with Framework is still a great challenge. One of the significant obstacles for us to smoothly use Framework is the complicated attribute value configuration of XML files. To overcome these...
Log analysis plays an important role for computer failure diagnosis. With the ever increasing size and complexity of logs, the task of analyzing logs has become cumbersome to carry out manually. For this reason, recent research has focused on automatic analysis techniques for large log files. However, log messages are texts with certain formats and it is very challenging for automatic analysis to...
Big data technologies are becoming widely used, not only for recording but also for analyzing human generated data. Indeed, the recent development in systems and technologies provided many areas with data processing technologies to extract meaningful information from massive amounts of data. A good example of areas where the generated data is voluminous is eLearning, e.g. Massive Open Online Courses...
Aspect extraction is one of the most important tasks for text mining. Semi-supervised methods have been proposed to solve this problem. However, the seed terms have to be given in advance in these methods. The current methods categorize the aspects without expanding more aspects terms. And most of the methods are based on English corpus, there is a great space for the research on the aspect extraction...
Image categorization is the process of categorizing the images into its respective class or bins. It is still challenging problem in computer vision key area. The existing methodologies for image categorization like semantic modelling approaches, neural network approaches does not provides an accurate solution. This is due to inefficient feature extraction and their processing. Deep Learning is a...
Social media has now become a pervasive global communication channel. Many applications and platforms have become available for users to post messages, follow friends and share experiences. Due to the high frequency with which users update their states, a large amount of data is being generated around the world every second. By analyzing this data, valuable patterns can be extracted such as the distribution...
The upsurge in the use of Context Aware Devices in various gadgets has led to the generation of massive mobility data. These gadgets tracks and records particulars of moving objects such as location, time, waypoints etc. in to various geographical databases. The data are recorded in the form of trajectories. Identification of the moving pattern is very much useful for setting up of the architectural...
There has been incredible growth of events over the internet in recent years. Google has become the giant source of knowledge for any event which has happened or happening over the internet. Some networking sites such as face book, micro blogging sites such as twitter are evolved with time and became the highly used sites over the internet. Various E-commerce websites such as Amazon, Ebay, Flipkart...
In the quest of developing more accurate methodologies for Earth Observation (EO) image retrieval, visualization and information content exploration, a deep understanding of the data being analyzed is needed. In this paper we propose a simple but efficient visual data mining methodology that can be used for these tasks. Our solution consists in a patch-based feature extraction to derive image features...
In China, the technology of information extraction is widely used in many fields and the most notable one is medical science. Chinese electronic medical records(CEMRs) contain tremendous information and is of great value, however, free text like CEMRs cannot be directly used for analysis. In order to extract valuable information from CEMRs, this paper put forward a method to extract key information...
Digital imaging plays an important role in many human activities, such as agriculture and forest management, earth sciences, urban planning, weather forecasting, medical imaging and so on. Processing, exploring and visualizing the inconceivable volumes of such images has turned out to be progressively troublesome. The Content-Based Image Retrieval (CBIR) remains an important issue that finds potential...
Opinion target extraction aims to find the object to which an opinion is expressed. It is helpful in getting a comprehensive understanding about public opinions on hot spot social events. In Chinese microblog posts analysis, due to the absence of words with emotional tendency (opinion words), traditional approaches relying on opinion words are not suitable. In this paper, we propose an unsupervised...
Retrieving information based on the users’ preferences and profiles represent a challenging issue to overcome. Moreover, in the public transport field, this task becomes increasingly complex due to the heterogeneous data fetched from various sources. Though, ontologies have emerged in retrieving information field to reduce this complexity. This paper describes a visual framework aiming...
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