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Community detection is a fundamental problem in social network analysis. There are a large number of community detection algorithms in the literature. However, many previous algorithms only focus on the structure of the network, and ignore the attributes of the users (e.g., the location attributes of the users). In this paper, we study the community detection problem in the context of location-based...
Social Networking Services rise rapidly in recent years, and gradually penetrate into the user groups all over the world. Sina Microblogging is one of the important applications and has more than 500 million registered users. Huge number of users on the platform and the mass content, provide effective corpus for information mining in groups of users. In this paper, more than 1.6 million user-generated...
GPS-enabled mobile devices such as smart phones and tablets are extremely popular today. Billions of such devices are currently in use. The application and research potentials of these devices are limitless, but how accurate are these devices? The research team used Average Euclidean Error (AEE), Root Mean Square Error (RMSE), and Central Error (CE) to define and calculate the accuracy and precision...
In this paper we propose a solution which highlights key sentences in lecture video transcripts based on acoustic analysis. The basic idea is that a good lecturer knows when and where to emphasize when giving a lecture and these emphases can be detected by acoustic features of the speech, such as energy, pitch, speaking rate, etc. The selected key sentences are then specially marked in the lecture...
High-dimensional crowdsourced data collected from a large number of users may produc3 rich knowledge for our society but also bring unprecedented privacy threats to participants. Recently differential privacy has been proposed as an effective means to mitigate privacy concerns. However, existing work on differential privacy suffers from the "curse of high-dimensionality" (data with multiple...
In online social networks (OSNs), highly-connected users are generally more capable to trigger viral diffusion. However, recent research demonstrates that ordinary users who only have a few connections can also cause large-scale diffusion. In this paper, we study the relation between the global spreading influence and the local connections of users to theoretically explain this phenomenon. We focus...
Discriminant Neighborhood Embedding (DNE) is one of the most popular methods for dimensionality reduction, which constructs an adjacency graph to preserve the local structure of original data in the subspace. However, there exist two shortcomings, first, DNE just constructs an adjacency graph, which may not achieve the goal of balancing the within-class and between-class samples. Second, DNE cannot...
Automatic prediction of continuous level emotional state requires selection of suitable affective features to develop a regression system based on supervised machine learning. This paper investigates the performance of low-level dynamic features for predicting two common dimensions of emotional state, namely, valence and arousal instantaneously. Low-complexity features are extracted from audio and...
Sentiment is the only things that separate human and machine. To simulate the feelings for machines many researchers have been trying to create method and automated the process to extract opinion of particular news, product or life entity. Sentiment Analysis (SA) is a combination of opinions, emotions and subjectivity of a text. Currently SA is the most demanding task in Natural Language Processing...
Meeting is a gathering of people to exchange information and plan joint activities for achieving a goal through verbal interactions. In a good meeting, participants' ideas are heard, decisions are made through discussions and activities are focused on desired results. The challenging part is to mine the most relevant interaction pattern from the meeting. Tree structures are not able to capture all...
With the growing interests in social networking, the interaction of social actors evolved to a source of knowledge in which it become possible to perform context aware reasoning. The information extraction from social networking specially Twitter and Facebook is on of the problem in this area. To extract text from social networking, we need several lexical features and large scale word clustering...
The emotion recognition has become a hot research topic in different domains: Human-Machine-Interaction, Natural Language processing etc. Recent research in the domain of Human Computer Interaction aims at recognizing the user's emotional state to give a smooth interface between humans and computers and to improve their interaction. In this paper we propose an emotion recognition system based on the...
Twitter, a well-liked online social networking site, facilitates millions of users on a daily basis to dispatch and orate quick 140-character notes named tweets. Nowadays, twitter is cogitated as the fastest and popular intermediate of communication and is used to follow latest events. Tweets pertaining to a specific event can be effortlessly found using keyword matching, but there are numerous tweets...
The opinion mining is very much essential in e-commerce websites, furthermore advantageous with individual. An ever increasing amount of results are stored in the web as well as the amount of people would acquiring items from web are increasing. As a result, the users' reviews or posts are increasing day by day. The reviews toward shipper sites express their feeling. Any organization for example,...
Animation rendering node is the key component of distributed animation rendering system, which offers rendering service. The performance of animation rendering node has great impact on user's experience. This paper uses DTMC-based model checking methodology to evaluate animation rendering node's performance. Based on the analysis of animation rendering node's working process, the probability of steady-state...
Interactions between industry and academia are seen as one of the key elements of the quality of higher education and a key element of the system of innovation of the nations. However, there is a widely noted gap between industry needs and the education that new engineers receive. This manuscript presents an open co-working space implemented by the Universidad de Ingenieria y Tecnologia equipped with...
This study is proposed to determine lab practice preferences for computer-based laboratory exercises. A quantitative data is collected through survey questionnaires among computer engineering's students and lecturers of Universiti Teknologi MARA Pulau Pinang. The survey items focus on four aspects; which are lab conduction, lab assessment, lab report writing and submission. A total of 87 correspondents...
Domain adaptation has achieved promising results in many areas, such as image classification and object recognition. Although a lot of algorithms have been proposed to solve the task with different domain distributions, it remains a challenge for multi-source unsupervised domain adaptation. In addition, most of the existing algorithms learn a classifier on the source domain and predict the labels...
The Ultra-DIMM constituted by DRAM and Flash memory is a promising solution used to tackle the challenges existing in traditional DRAM in terms of energy consuming and scalability. In this hybrid memory system, DRAM is used as the data buffer of Flash memory due to the performance and endurance gaps between main memory and Flash. However, the inconsistency of access granularity between the main memory...
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