A Novel Filtering Recommendation Algorithm for User Emergency Information Adoption

2021 ◽  
Vol 15 ◽  
pp. 1133-1140
Author(s):  
Xiaoying Yao ◽  
Chunnian Liu ◽  
Yingfei Zhu
Keyword(s):  
Feature Vector ◽  
Temporal Information ◽  
Characteristic Matrix ◽  
Actual Situation ◽  
Recommendation Algorithm ◽  
Emergency Case ◽  
User Context ◽  
Case Data ◽  
Information Adoption

Emergency case data resources are widely distributed and heterogeneous. At the same time, the command of emergency field needs the cooperation of multiple departments. Therefore, it is urgent to establish an emergency analysis and mining platform, realize the sharing and collaboration of emergency data resources among multiple departments, and assist emergency command and scheduling. According to the actual situation of the current emergency, a similarity measure method (TCRD) is proposed to solve this problem by adding temporal information to reflect information adoption, which integrates user context information and temporal information. Firstly, the temporal information of historical adoption behavior is expressed as a binary coded characteristic matrix, and then the characteristic matrix is mapped into a feature vector by using restricted Boltzmann machine, and finally added to the similarity measurement formula. The improved TCRD method can measure the similarity more accurately, and further improve the quality of emergency information adoption recommendation results.

Model and Method for Contributor’s Quality Assessment in Community Image Tagging Systems

2018 ◽  
pp. 45-51
Author(s):  
A. V. Ponomarev
Keyword(s):  
Large Scale ◽  
Wide Spectrum ◽  
Preference Relation ◽  
Pairwise Comparison ◽  
Ground Truth ◽  
Comparison Method ◽  
Characteristic Matrix ◽  
Image Tagging ◽  
Proposed Model

Introduction: Large-scale human-computer systems involving people of various skills and motivation into the information processing process are currently used in a wide spectrum of applications. An acute problem in such systems is assessing the expected quality of each contributor; for example, in order to penalize incompetent or inaccurate ones and to promote diligent ones.Purpose: To develop a method of assessing the expected contributor’s quality in community tagging systems. This method should only use generally unreliable and incomplete information provided by contributors (with ground truth tags unknown).Results:A mathematical model is proposed for community image tagging (including the model of a contributor), along with a method of assessing the expected contributor’s quality. The method is based on comparing tag sets provided by different contributors for the same images, being a modification of pairwise comparison method with preference relation replaced by a special domination characteristic. Expected contributors’ quality is evaluated as a positive eigenvector of a pairwise domination characteristic matrix. Community tagging simulation has confirmed that the proposed method allows you to adequately estimate the expected quality of community tagging system contributors (provided that the contributors' behavior fits the proposed model).Practical relevance: The obtained results can be used in the development of systems based on coordinated efforts of community (primarily, community tagging systems). 

Research and Application on Screen Soft Proofing Technology in Printing Quality Control

2012 ◽  
Vol 262 ◽  
pp. 263-268
Author(s):  
Zhan Jun Si ◽  
Jia Wang ◽  
Chong Gu
Keyword(s):  
Quality Control ◽  
Good Effect ◽  
Color Management ◽  
Actual Situation ◽  
Testing Scheme ◽  
Printing Quality ◽  
Display Technology ◽  
Soft Proofing ◽  
Display Performance

In recent years, screen soft proofing has matured with the development of color management and display technology, and it has become the direction of printing development and the key of promotion. This article aimed at raising a testing scheme of display performance and adjusting scheme of corresponding display parameters, on this account to test the professional display’s performance, adjust display parameters and make color management. At the same time with reflecting the actual situation of display, a stable and accurate color reproduction environment was provided for screen soft proofing. After that, evaluations were carried out to evaluate printing quality of screen soft proofing on the condition that display’s performance was good, consequently the differences between proofing effects and final printing were studied. The result shows that this testing scheme of display performance can reflect the truth of display which is tested in this paper, the display after adjusted and color management according to this scheme shows good effect in the ability of screen analog proofing original, it can approach the requirements of the printing proofing.

Optimized Collaborative Filtering Recommendation Based on User’s Social Relationships

2014 ◽  
Vol 1044-1045 ◽  
pp. 1484-1488
Author(s):  
Yue Kun Fan ◽  
Xin Ye Li ◽  
Meng Meng Cao
Keyword(s):  
Collaborative Filtering ◽  
Social Relationships ◽  
Digital Libraries ◽  
Social Relationship ◽  
Nearest Neighbor ◽  
Mean Absolute Error ◽  
Absolute Error ◽  
Personalized Recommendation ◽  
Recommendation Algorithm

Currently collaborative filtering is widely used in e-commerce, digital libraries and other areas of personalized recommendation service system. Nearest-neighbor algorithm is the earliest proposed and the main collaborative filtering recommendation algorithm, but the data sparsity and cold-start problems seriously affect the recommendation quality. To solve these problems, A collaborative filtering recommendation algorithm based on users' social relationships is proposed. 0n the basis of traditional filtering recommendation technology, it combines with the interested objects of user's social relationship and takes the advantage of the tags to projects marked by users and their interested objects to improve the methods of recommendation. The experimental results of MAE ((Mean Absolute Error)) verify that this method can get better quality of recommendation.

scholarly journals Analysis on the Innovative Ways of Employment and Entrepreneurship Guidance in Higher Vocational Colleges Under the Education of "Three All-round Education"

2020 ◽  
Vol 4 (10) ◽  
Author(s):  
Linman Zhang
Keyword(s):  
Actual Situation ◽  
Curriculum Innovation ◽  
Staff Education ◽  
New Era ◽  
Comprehensive Education ◽  
Teaching Reform ◽  
Educational Concept ◽  
Vocational Colleges ◽  
Education Concept

The educational concept of "Three All-round Education" emphasizes all-staff education, full-process education, and all-round education. At present, this education concept has been applied in many courses and is a new era curriculum, one of the important ideological guidelines for teaching reform. As far as the employment and entrepreneurship guidance work and teaching in higher vocational colleges are concerned, this is an important guiding course for solving the employment and entrepreneurship problems of higher vocational graduates in the new era. The quality of course teaching must be ensured and guided by the concept of "three comprehensive education". It is of great significance for curriculum innovation and development. This article introduces the basic connotation of the "Three Comprehensive Education", analyzes the necessity of the application of the "Three Comprehensive Education" concept in the employment and entrepreneurship guidance work of higher vocational colleges, and explores the actual situation of the employment and entrepreneurship guidance work in the higher vocational colleges. This is the innovation path of employment and entrepreneurship guidance work in higher vocational colleges under the education of "Three All-round Education".

scholarly journals Improved Bidirectional CABOSFV Based on Multi-Adjustment Clustering and Simulated Annealing

2016 ◽  
Vol 16 (6) ◽  
pp. 27-42 ◽  
Author(s):  
Minghan Yang ◽  
Xuedong Gao ◽  
Ling Li
Keyword(s):  
Simulated Annealing ◽  
Data Clustering ◽  
Time Complexity ◽  
Clustering Algorithm ◽  
Feature Vector ◽  
Parameter Determination ◽  
Data Sets ◽  
Parameter Vector ◽  
Clustering Validity

Abstract Although Clustering Algorithm Based on Sparse Feature Vector (CABOSFV) and its related algorithms are efficient for high dimensional sparse data clustering, there exist several imperfections. Such imperfections as subjective parameter designation and order sensibility of clustering process would eventually aggravate the time complexity and quality of the algorithm. This paper proposes a parameter adjustment method of Bidirectional CABOSFV for optimization purpose. By optimizing Parameter Vector (PV) and Parameter Selection Vector (PSV) with the objective function of clustering validity, an improved Bidirectional CABOSFV algorithm using simulated annealing is proposed, which circumvents the requirement of initial parameter determination. The experiments on UCI data sets show that the proposed algorithm, which can perform multi-adjustment clustering, has a higher accurateness than single adjustment clustering, along with a decreased time complexity through iterations.

Product Recommendation Algorithm for Score Prediction Based on Joint Feature Vector Extraction

2021 ◽  
Author(s):  
Jian-hua LI ◽  
Chen-xi ZHANG ◽  
Chun-li LEI ◽  
Hong ZHANG ◽  
Lin-long CHEN
Keyword(s):  
Feature Vector ◽  
Recommendation Algorithm ◽  
Product Recommendation

Automatically Evolving Texture Image Descriptors using the Multi-tree Representation in Genetic Programming using Few Instances

2020 ◽  
pp. 1-34
Author(s):  
Harith Al-Sahaf ◽  
Ausama Al-Sahaf ◽  
Bing Xue ◽  
Mengjie Zhang
Keyword(s):  
Genetic Programming ◽  
Feature Vector ◽  
Local Binary Patterns ◽  
Texture Image ◽  
Tree Representation ◽  
Line Segments ◽  
Image Descriptor ◽  
Image Descriptors ◽  
The Cost

The performance of image classification is highly dependent on the quality of the extracted features that are used to build a model. Designing such features usually requires prior knowledge of the domain and is often undertaken by a domain expert who, if available, is very costly to employ. Automating the process of designing such features can largely reduce the cost and efforts associated with this task. Image descriptors, such as local binary patterns, have emerged in computer vision, and aim at detecting keypoints, e.g., corners, line-segments and shapes, in an image and extracting features from those keypoints. In this paper, genetic programming (GP) is used to automatically evolve an image descriptor using only two instances per class by utilising a multi-tree program representation. The automatically evolved descriptor operates directly on the raw pixel values of an image and generates the corresponding feature vector. Seven well-known datasets were adapted to the few-shot setting and used to assess the performance of the proposed method and compared against six hand-crafted and one evolutionary computation-based image descriptor as well as three convolutional neural network (CNN) based methods. The experimental results show that the new method has significantly outperformed the competitor image descriptors and CNN-based methods. Furthermore, different patterns have been identified from analysing the evolved programs.

scholarly journals Video Quality of Experience Metric for Dynamic Adaptive Streaming Services Using DASH Standard and Deep Spatial-Temporal Representation of Video

2020 ◽  
Vol 10 (5) ◽  
pp. 1793
Author(s):  
Lina Du ◽  
Li Zhuo ◽  
Jiafeng Li ◽  
Jing Zhang ◽  
Xiaoguang Li ◽  
...  
Keyword(s):  
Video Compression ◽  
Quality Of Experience ◽  
Feature Vector ◽  
Video Quality ◽  
Superior Performance ◽  
Adaptive Streaming ◽  
Input Feature ◽  
Streaming Services ◽  
Content Characteristics

DASH (Dynamic Adaptive Streaming over HTTP (HyperText Transfer Protocol)) as a universal unified multimedia streaming standard selects the appropriate video bitrate to improve the user’s Quality of Experience (QoE) according to network conditions, client status, etc. Considering that the quantitative expression of the user’s QoE is also a difficult point in itself, this paper researched the distortion caused due to video compression, network transmission and other aspects, and then proposes a video QoE metric for dynamic adaptive streaming services. Three-Dimensional Convolutional Neural Networks (3D CNN) and Long Short-Term Memory (LSTM) are used together to extract the deep spatial-temporal features to represent the content characteristics of the video. While accounting for the fluctuation in the quality of a video caused by bitrate switching on the QoE, other factors such as video content characteristics, video quality and video fluency, are combined to form the input feature vector. The ridge regression method is adopted to establish a QoE metric that enables to dynamically describe the relationship between the input feature vector and the value of the Mean Opinion Score (MOS). The experimental results on different datasets demonstrate that the prediction accuracy of the proposed method can achieve superior performance over the state-of-the-art methods, which proves the proposed QoE model can effectively guide the client’s bitrate selection in dynamic adaptive streaming media services.

scholarly journals Ethics of Timeliness in Confucianism

MANUSYA ◽  
2009 ◽  
Vol 12 (2) ◽  
pp. 46-62
Author(s):  
Sarinya Arunkhajornsak
Keyword(s):  
Crucial Role ◽  
Time Change ◽  
Confucian Ethics ◽  
Actual Situation ◽  
Human Beings ◽  
Moral Practice ◽  
Intellectual Capacity ◽  
The Analects

By exploring Confucius’ attitude towards time, change, and transformation in the “Analects”, this paper aims to illustrate that temporality plays a crucial role in Confucian ethics. Confucius uses the notion of timeliness as an ethical guide in self-cultivation and moral practice in order to harmonize human beings with all the events of change. This paper argues that timely sagehood is a key quality of the junzi or “excellent person.” To be a timely sage, a junzi must cultivate the virtue of yi. This paper presents a conceptualization of “yi” in the “Analects” and proposes that its meanings limited to “righteousness” and “appropriateness” in the sense of morality, legitimacy and justice, include a sense of timeliness, namely, the quality of timely action and the inner intellectual capacity of a junzi to evaluate and work out the appropriate course of an action in an actual situation.

scholarly journals Research of Personalized Course Recommended Algorithm based on the Hybrid Recommendation

2018 ◽  
Vol 173 ◽  
pp. 03067
Author(s):  
Qing Yang ◽  
Peiling Yuan ◽  
Xi Zhu
Keyword(s):  
Collaborative Filtering ◽  
Association Rule ◽  
High Performance ◽  
Recommendation Algorithm ◽  
Filtering Algorithm ◽  
Collaborative Filtering Algorithm ◽  
Elective Course ◽  
Recommended Algorithm ◽  
Hybrid Recommendation

This paper presents a personalized course recommended algorithm based on the hybrid recommendation. The recommendation algorithm uses the improved NewApriori algorithm to implements the association rule recommendation, and the user-based collaborative filtering algorithm is the main part of the algorithm. The hybrid algorithm adds the weight to the recommendation result of the user-based collaborative filtering and association rule recommendation, implementing a hybrid recommendation algorithm based on both of them. It has solved the problem of data sparsity and cold-start partially and provides a academic reference for the design of high performance elective system. The experiment uses the student scores data of a college as the test set and analyzes results and recommended quality of personalized elective course. According to the results of the experimental results, the quality of the improved hybrid recommendation algorithm is better.

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