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There has been a surge in research interest in learning feature representation of networks in recent times. Researchers, motivated by the recent successes of embeddings in natural language processing and advances in deep learning, have explored various means for network embedding. Network embedding is useful as it can exploit off-the-shelf machine learning algorithms for network mining tasks like...
According to a report online [34], more than 200 million unique users search for jobs online every month. This incredibly large and fast growing demand has enticed software giants such as Google and Facebook to enter this space, which was previously dominated by companies such as LinkedIn, Indeed, Dice and CareerBuilder. Recently, Google released their “AIpowered Jobs Search Engine”, “Google For Jobs”...
Extracting stop purpose information from raw GPS data is a crucial task in most location-aware applications. With the continuous growth of GPS data collected from mobile devices, this task is becoming more and more interesting; a lot of recent research has focused on pedestrians (mobile phones) data, while the commercial vehicles sector is almost unexplored. In this paper we target the problem of...
User-generated mobile application reviews have become a gold mine for timely identifying functional defects in this type of software artifacts. In this work, we develop a hidden structural SVM model for extracting detailed defect descriptions from user reviews at the sentence level. Structured features and constraints are introduced to reduce the demand of exhaustive manual annotation at the sentence...
Understanding user query intent is a crucial task to Question-Answering area. With the development of online health services, online health communities generate huge amount of valuable medical Question-Answering data, where user intention can be mined. However, the queries posted by common users have many domain concepts and colloquial expressions, which make the understanding of user intents very...
Gene ontology (GO) defines terms and classes used to describe gene functions and relationships between them. GO has been the standard to describing the functions of specific genes in different model organisms. GO annotation which tags genes with GO terms has mostly been a manual and timeconsuming curation process. In this paper we describe the development and evaluation of an innovative predictive...
Opioid (e.g., heroin and morphine) addiction has become one of the largest and deadliest epidemics in the United States. To combat such deadly epidemic, there is an urgent need for novel tools and methodologies to gain new insights into the behavioral processes of opioid addiction and treatment. In this paper, we design and develop an intelligent system named iOPU to automate the detection of opioid...
In this paper, we propose a new discriminative dictionary learning framework, called robust Label Embedding Projective Dictionary Learning (LE-PDL), for data classification. LE-PDL can learn a discriminative dictionary and the blockdiagonal representations without using the l0-norm or l1-norm sparsity regularization, since the l0 or l1-norm constraint on the coding coefficients used in the existing...
The bag of words (BOW) represents a corpus in a matrix whose elements are the frequency of words. However, each row in the matrix is a very high-dimensional sparse vector. Dimension reduction (DR) is a popular method to address sparsity and high-dimensionality issues. Among different strategies to develop DR method, Unsupervised Feature Transformation (UFT) is a popular strategy to map all words on...
IP Addresses are a central part of packet- and flow-based network data. However, visualization and similarity computation of IP Addresses are challenging to due the missing natural order. This paper presents a novel similarity measure IP2Vec for IP Addresses that builds on ideas from Word2Vec, a popular approach in text mining. The key idea is to learn similarities by extracting available context...
Domain generation algorithms (DGAs) automatically generate large numbers of domain names in DNS domain fluxing for the purpose of command-and-control (C&C) communication. DGAs are immune to static prevention methods like blacklisting and sinkholing. Detection of DGAs in a live stream of queries in a DNS server is referred to as inline detection. Most of the previous approaches in the literature...
This paper presents a novel approach for activity recognition from accelerometer data. Existing approaches usually extract hand-crafted features that are used as input for classifiers. However, hand-crafted features are data dependent and could not be generalized for different application domains. To overcome these limitations, our approach relies on matrix factorization for dimensionality reduction...
Feature selection, as a fundamental component of building robust models, plays an important role in many machine learning and data mining tasks. Since acquiring labeled data is particularly expensive in both time and effort, unsupervised feature selection on unlabeled data has recently gained considerable attention. Without label information, unsupervised feature selection needs alternative criteria...
Feature selection is the process of selecting a subset of relevant features from the larger set of collected features. As the amount of available data grows with technology, feature selection becomes a more important part of the system-design process. In real-world applications, there are several costs associated with the collection, processing, and storage of data. Given that these costs can vary...
Advanced statistics have proved to be a crucial tool for basketball coaches in order to improve training skills. Indeed, the performance of the team can be further optimized by studying the behaviour of players under certain conditions. In the United States of America, companies such as STATS or Second Spectrum use a complex multi-camera setup to deliver advanced statistics to all NBA teams, but the...
The primary failure mechanism in brittle materials such as ceramics, granite and some metal alloys is through the presence of defects which result in crack formation and propagation under the application of load. We are interested in studying this process of crack propagation, interaction and coalescence, which degrades the strength of the specimen. Traditionally, engineering applications that study...
Crime prediction plays a crucial role in addressing crime, violence, conflict and insecurity in cities to promote good governance, appropriate urban planning and management. Plenty efforts have been made on developing crime prediction models by leveraging demographic data, but they failed to capture the dynamic nature of crimes in urban. Recently, with the development of new techniques for collecting...
Human mobility has been studied extensively in various biomedical contexts with applications in clinical rehabilitation, disease diagnosis, health risk prognosis, and general performance assessments. In this paper, we present ATOMHP (Analytical Technologies to Objectively Measure Human Performance) Kinect: a system to objectively quantify human performance using the Microsoft Kinect as a single camera...
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