Context-Based Entity Resolution

2014 ◽  
pp. 67-86
Keyword(s):  
High Precision ◽  
Entity Resolution ◽  
Efficient Algorithms ◽  
Experimental Results ◽  
Context Information ◽  
Prior Work ◽  
Insufficient Information ◽  
Data Objects ◽  
Er Algorithm

Prior work of entity resolution involves expensive similarity comparison and clustering approaches. Additionally, the quality of entity resolution may be low due to insufficient information. To address these problems, by adopting context information of data objects, the authors present a novel framework of entity resolution, Context-Based Entity Description (CED), to make context information help entity resolution. In this framework, each entity is described by a set of CEDs. During entity resolution, objects are only compared with CEDs to determine its corresponding entity. Additionally, the authors propose efficient algorithms for CED discovery, maintenance, and CED-based entity resolution. The authors experimentally evaluated the CED-based ER algorithm on the real DBLP datasets, and the experimental results show that this algorithm can achieve both high precision and recall as well as outperform existing methods.

Development of Liquid Tunable Diffractive/Refractive Hybrid Lens Based on Combination of Diamond Turning and Soft Lithography

2009 ◽  
Vol 74 ◽  
pp. 85-88
Author(s):  
Hui Min Leung ◽  
Hong Bin Yu ◽  
Guang Ya Zhou ◽  
A. Senthil Kumar ◽  
Fook Siong Chau
Keyword(s):  
Surface Quality ◽  
High Precision ◽  
Soft Lithography ◽  
Fresnel Lens ◽  
Green Laser ◽  
Diamond Turning ◽  
Fabrication Process ◽  
Experimental Results ◽  
Refractive Lens

A liquid tunable diffractive/refractive hybrid lens which combines the use of high precision diamond turning and soft lithography is developed in this work. This diffractive/refractive hybrid lens comprises a Fresnel lens and a tunable refractive lens automatically aligned during the fabrication process. Multiple PDMS hybrid lens devices can be fabricated from the diamond-turned master mould and AFM results show that the surface quality of the PDMS lenses meets the requirements for optical purposes. The hybrid lens is tested with a green laser (λ = 532nm) and experimental results demonstrate a tunability of more than 20mm.

scholarly journals How the Multiplicity of Suggested Information Affects the Behavior of a User in a Recommender System

Electronics ◽  
2021 ◽  
Vol 10 (6) ◽  
pp. 741
Author(s):  
Yuseok Ban ◽  
Kyungjae Lee
Keyword(s):  
High Precision ◽  
Recommender System ◽  
Visual Information ◽  
Experimental Results ◽  
Supplementary Information ◽  
Digital Platform ◽  
Different Types ◽  
Types Of Information

Many researchers have suggested improving the retention of a user in the digital platform using a recommender system. Recent studies show that there are many potential ways to assist users to find interesting items, other than high-precision rating predictions. In this paper, we study how the diverse types of information suggested to a user can influence their behavior. The types have been divided into visual information, evaluative information, categorial information, and narrational information. Based on our experimental results, we analyze how different types of supplementary information affect the performance of a recommender in terms of encouraging users to click more items or spend more time in the digital platform.

Hybrid features prediction model of movie quality using Multi-machine learning techniques for effective business resource planning

2021 ◽  
Vol 40 (5) ◽  
pp. 9361-9382 ◽  
Author(s):  
Naeem Iqbal ◽  
Rashid Ahmad ◽  
Faisal Jamil ◽  
Do-Hyeun Kim
Keyword(s):  
Machine Learning ◽  
Social Media ◽  
Resource Planning ◽  
Experimental Results ◽  
Quality Prediction ◽  
Classification Models ◽  
Hybrid Features ◽  
Social Media Data ◽  
Media Data

Quality prediction plays an essential role in the business outcome of the product. Due to the business interest of the concept, it has extensively been studied in the last few years. Advancement in machine learning (ML) techniques and with the advent of robust and sophisticated ML algorithms, it is required to analyze the factors influencing the success of the movies. This paper presents a hybrid features prediction model based on pre-released and social media data features using multiple ML techniques to predict the quality of the pre-released movies for effective business resource planning. This study aims to integrate pre-released and social media data features to form a hybrid features-based movie quality prediction (MQP) model. The proposed model comprises of two different experimental models; (i) predict movies quality using the original set of features and (ii) develop a subset of features based on principle component analysis technique to predict movies success class. This work employ and implement different ML-based classification models, such as Decision Tree (DT), Support Vector Machines with the linear and quadratic kernel (L-SVM and Q-SVM), Logistic Regression (LR), Bagged Tree (BT) and Boosted Tree (BOT), to predict the quality of the movies. Different performance measures are utilized to evaluate the performance of the proposed ML-based classification models, such as Accuracy (AC), Precision (PR), Recall (RE), and F-Measure (FM). The experimental results reveal that BT and BOT classifiers performed accurately and produced high accuracy compared to other classifiers, such as DT, LR, LSVM, and Q-SVM. The BT and BOT classifiers achieved an accuracy of 90.1% and 89.7%, which shows an efficiency of the proposed MQP model compared to other state-of-art- techniques. The proposed work is also compared with existing prediction models, and experimental results indicate that the proposed MQP model performed slightly better compared to other models. The experimental results will help the movies industry to formulate business resources effectively, such as investment, number of screens, and release date planning, etc.

scholarly journals Identification of the State of Electrical Appliances with the Use of a Pulse Signal Generator

Energies ◽  
2021 ◽  
Vol 14 (3) ◽  
pp. 673
Author(s):  
Augustyn Wójcik ◽  
Piotr Bilski ◽  
Robert Łukaszewski ◽  
Krzysztof Dowalla ◽  
Ryszard Kowalik
Keyword(s):  
Measurement System ◽  
Cross Correlation ◽  
Pulse Signal ◽  
Signal Generator ◽  
Experimental Results ◽  
The Novel ◽  
End User ◽  
Standard Classification ◽  
Electrical Appliance

The paper presents the novel HF-GEN method for determining the characteristics of Electrical Appliance (EA) operating in the end-user environment. The method includes a measurement system that uses a pulse signal generator to improve the quality of EA identification. Its structure and the principles of operation are presented. A method for determining the characteristics of the current signals’ transients using the cross-correlation is described. Its result is the appliance signature with a set of features characterizing its state of operation. The quality of the obtained signature is evaluated in the standard classification task with the aim of identifying the particular appliance’s state based on the analysis of features by three independent algorithms. Experimental results for 15 EAs categories show the usefulness of the proposed approach.

scholarly journals Contour Detection for Fibre of Preserved Szechuan Pickle Based on Dilated Convolution

2019 ◽  
Vol 9 (13) ◽  
pp. 2684 ◽  
Author(s):  
Hongyang Li ◽  
Lizhuang Liu ◽  
Zhenqi Han ◽  
Dan Zhao
Keyword(s):  
Edge Detection ◽  
State Of The Art ◽  
Contour Detection ◽  
Experimental Results ◽  
Contour Method ◽  
Class Differences ◽  
Dilated Convolution ◽  
The Mean ◽  
Art Performance

Peeling fibre is an indispensable process in the production of preserved Szechuan pickle, the accuracy of which can significantly influence the quality of the products, and thus the contour method of fibre detection, as a core algorithm of the automatic peeling device, is studied. The fibre contour is a kind of non-salient contour, characterized by big intra-class differences and small inter-class differences, meaning that the feature of the contour is not discriminative. The method called dilated-holistically-nested edge detection (Dilated-HED) is proposed to detect the fibre contour, which is built based on the HED network and dilated convolution. The experimental results for our dataset show that the Pixel Accuracy (PA) is 99.52% and the Mean Intersection over Union (MIoU) is 49.99%, achieving state-of-the-art performance.

Reinforcement Learning for Cloud Computing Digital Library

2014 ◽  
Vol 571-572 ◽  
pp. 105-108
Author(s):  
Lin Xu
Keyword(s):  
Artificial Intelligence ◽  
Cloud Computing ◽  
Reinforcement Learning ◽  
Digital Library ◽  
Learning Algorithms ◽  
Experimental Results ◽  
Current Status ◽  
Self Learning ◽  
New Framework

This paper proposes a new framework of combining reinforcement learning with cloud computing digital library. Unified self-learning algorithms, which includes reinforcement learning, artificial intelligence and etc, have led to many essential advances. Given the current status of highly-available models, analysts urgently desire the deployment of write-ahead logging. In this paper we examine how DNS can be applied to the investigation of superblocks, and introduce the reinforcement learning to improve the quality of current cloud computing digital library. The experimental results show that the method works more efficiency.

Comparison of Thresholding and Edge Detection Segmentation Techniques

2013 ◽  
Vol 860-863 ◽  
pp. 2783-2786
Author(s):  
Yu Bing Dong ◽  
Hai Yan Wang ◽  
Ming Jing Li
Keyword(s):  
Image Segmentation ◽  
Root Mean Square Error ◽  
Edge Detection ◽  
Mean Square Error ◽  
Root Mean Square ◽  
Experimental Results ◽  
Mean Square ◽  
Segmentation Method ◽  
Segmentation Algorithms

Edge detection and thresholding segmentation algorithms are presented and tested with variety of grayscale images in different fields. In order to analyze and evaluate the quality of image segmentation, Root Mean Square Error is used. The smaller error value is, the better image segmentation effect is. The experimental results show that a segmentation method is not suitable for all images segmentation.

Implementation of a High-Precision Ultrasonic Rain Gauge

2013 ◽  
Vol 300-301 ◽  
pp. 382-388
Author(s):  
Zhan Wei Xu ◽  
Gui Lin Zheng
Keyword(s):  
Theoretical Analysis ◽  
High Precision ◽  
Rain Gauge ◽  
Experimental Results ◽  
Full Description ◽  
Self Calibration ◽  
Velocity Of Ultrasound

A novel rain gauge based on acoustic self-calibration principle is proposed in the paper. Acoustic self-calibration principle can eliminate the uncertainty of the velocity of ultrasound and achieve accurate measurement of rainfall. The rain gauge not only overcomes the influence on the rainfall measurement under intensive rainfall conditions, but also improves the precision of rain gauge. Plenty of experiments have been done to validate the design. Both theoretical analysis and experimental results show the effectiveness of the rain gauge. A full description of the rain gauge and implementation are presented.

Friction and Tribological Considerations for Nanometer Range Machining

2001 ◽  
Author(s):  
Som Chattopadhyay
Keyword(s):  
Mathematical Model ◽  
High Precision ◽  
Local Deformation ◽  
Experimental Results ◽  
Precision Machining ◽  
Complex Motion ◽  
Positioning Accuracy ◽  
Nanometer Range ◽  
Motion Characteristic ◽  
Low Speeds

Abstract Positioning accuracy within the range of nanometers is required for high precision machining applications. The implementation of such a range is difficult through the slides because of (a) irregular nature of friction at the slider-guideway interface, and (b) complex motion characteristic at very low speeds. The complexity arises due to the local deformation at the interface prior to breakaway, which is known as microdynamics. In this work prior experimental results exhibiting microdynamics have been appraised, and mathematical model developed to understand this behavior.

scholarly journals Multimedia Quality Integration Using Piecewise Function

2011 ◽  
Vol 1 ◽  
pp. 375-380
Author(s):  
Shu Ai Wan ◽  
Kai Fang Yang ◽  
Hai Yong Zhou
Keyword(s):  
Visual Quality ◽  
Experimental Results ◽  
Integration Model ◽  
Quality Performance ◽  
Piecewise Function ◽  
Proposed Model ◽  
Constant Coefficients ◽  
Theoretical Analyses ◽  
Different Levels

In this paper the important issue of multimedia quality evaluation is concerned, given the unimodal quality of audio and video. Firstly, the quality integration model recommended in G.1070 is evaluated using experimental results. Theoretical analyses aide empirical observations suggest that the constant coefficients used in the G.1070 model should actually be piecewise adjusted for different levels of audio and visual quality. Then a piecewise function is proposed to perform multimedia quality integration under different levels of the audio and visual quality. Performance gain observed from experimental results substantiates the effectiveness of the proposed model.

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