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Nowadays, a hot challenge for supermarket chains is to offer personalized services to their customers. Market basket prediction, i.e., supplying the customer a shopping list for the next purchase according to her current needs, is one of these services. Current approaches are not capable of capturing at the same time the different factors influencing the customer's decision process: co-occurrence,...
It is very crucial for news aggregator websites which are recent in the market to actively engage its existing users. A recommendation system would help to tackle such a problem. However, due to the lack of sufficient amount of data, most of the state-of-the-art methods perform poorly in terms of recommending relevant news items to the users. In this paper, we propose a novel approach for Item-based...
Data-driven analytics and decision-making have been essential for numerous applications in our society. To transform the data into a source of rich intelligence and support decision-making, data-driven analytics often need to aggregate intelligence from multiple sources and disaggregate signals into significant constituents. Though many existing approaches perform these two tasks respectively, there...
Information networks such as social networks, publication networks, and the World Wide Web are ubiquitous in the real world. Traditionally, adjacency matrices are used to represent the networks. However, adjacency matrices are too sparse and too high dimensional when the scale of the networks is large. Network embedding, which aims to learn low-dimensional continuous representations for nodes, has...
Networks naturally capture a host of real-world interactions, from social interactions and email communication to brain activity. However, graphs are not always directly observed, especially in scientific domains, such as neuroscience, where monitored brain activity is often captured as time series. How can we efficiently infer networks from time series data (e.g., model the functional organization...
Graph data management and mining in HPC environments has been a widely discussed issue in recent times. In this talk I will describe the use of Partitioned Global Address Space languages for graph data mining and management. I will first discuss the rationale behind X10 based graph libraries and graph database benchmarks using ScaleGraph and XGDBench as examples. Next, I will take Acacia which is...
Given a stream of heterogeneous edges, comprising different types of nodes and edges, which arrive in an interleaved fashion to multiple different graphs evolving simultaneously, how can we spot the anomalous graphs in real-time using only constant memory? This problem is motivated by and generalizes from its application in security to host-level advanced persistent threat (APT) detection. In this...
Traditionally, the time-to-fill metric is used as a scorecard for past performance. An organization may use time to fill to assess the performance of its internal recruiting team, or as a way to set service level agreements with outsourced recruiting partners. By first developing a set of quantifiable job features and then applying survival analysis to historical time-to-fill data, we build a predictor...
Finding the best candidates to match a set of job requirements can be viewed as both an art and a science. In this paper, we conduct an empirical study using actual job candidates and job applicants. We compare the ranked lists generated by executive recruiting experts with the list generated by three search strategies: one using crowdworkers in a gamified environment, a second using information retrieval-based...
Multilayer network analysis has become a vital tool for understanding different relationships and their interactions in a complex system, where each layer in a multilayer network depicts the topological structure of a group of nodes corresponding to a particular relationship. The interactions among different layers imply how the interplay of different relations on the topology of each layer. For a...
A scalable method for mining graph patterns stable under subsampling is proposed. The existing subsample stability and robustness measures are not antimonotonic according to definitions known so far. We study a broader notion of antimonotonicity for graph patterns, so that measures of subsample stability become antimonotonic. Then we propose gSOFIA for mining the most subsample-stable graph patterns...
Motivation: Transcription-regulatory elements (TREs) are critical modulators of gene transcription, with promoters and enhancers being major hubs for gene regulation. Of these, enhancers are distal regulatory elements, typically short 50–150 basepairs DNA regions and are identified via the large numbers of genomic regions displaying enhancer-like chromatin features, such as histone modifications at...
The number of triangles in a graph is useful to deduce a plethora of important features of the network that the graph is modeling. However, finding the exact value of this number is computationally expensive. Hence, a number of approximation algorithms based on random sampling of edges, or wedges (adjacent edge pairs) have been proposed for estimating this value. We argue that for large sparse graphs...
Alternative feature generation for quantitative image analysis is proposed. The proposed method reorganize Deep Convolutional Neural Networks to learn representation in Triplet Network. The features are compared with texture features using series of classifiers in a Gamma image classification task that contains visual information but has no known suitable features. Experiment show that features from...
Previous work has developed a remarkably low cost method which allows IoT devices to securely join domestic WiFi networks. Implementation of this method has uncovered a weakness in that only controllers (usually smart phones) capable of programmatically controlling hotspot mode can successfully implement the protocol. It is demonstrated that this weakness greatly compromises the open nature of this...
Conventionally power flow of transmission and distribution network is calculated separately. With the increasing penetration level of distributed generation (DG), such as photovoltaic and wind power, voltage and power characteristics of tie bus become complicated. The tight coupling problem appears between transmission and distribution network. As a consequence, the power flow calculation must be...
Circuit level energy metering is becoming increasingly important in energy savings and demand response applications. While smart meters efficiently monitor the residential energy consumption and make it available to the users, they fail to provide circuit level power consumption. In this study, an array of Giant Magneto Resistive (GMR) sensors are deployed on circuit breakers as stick-on sensors to...
Based on the inductive power transfer (IPT), the contactless approach allows safe and comfortable operations of battery charging for Electric Vehicles (EVs). In this paper, a contactless system particularly suitable for E-bike battery charging is proposed. A practical realization of the system has been carried out, aiming at the system evaluation in terms of working and efficiency. Through a phase...
The use of fossil energy has caused air pollution, energy crises, and it is not environmentally friendly. So, that is necessary to find alternative energy from biomass materials. Indonesia has the potential of developing alternative energy with a huge natural resource. Examples of mass bio energy developed such as: Jatropha, Palm, and Nyamplung (Calophyllum inophyllum L) oils. To assist the development...
Wireless power transfer technology offers significant improvement in convenience and electric safety for electric vehicle (EV) charging. Our research aims at novel designs that considerably reduce size and cost while increasing the coupling coefficient and improving the misalignment capability. We will first introduce the basics of wireless power transfer followed by discussion of a double-sided LCC...
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