How can dense results be differentiated in comprehensive evaluations? A hybrid information filtering model

2021 ◽  
pp. 107658
Author(s):  
Lu-Tao Zhao ◽  
Wen-Jing Wang ◽  
Da-Kuan Li
Keyword(s):  
Information Filtering ◽  
Comprehensive Evaluations

scholarly journals Who Likes What Kind of News? The Relationship Between Characteristics of Media Consumers and News Interest

SAGE Open ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 215824402110030
Author(s):  
Kai Kaspar ◽  
Lisa Anna Marie Fuchs
Keyword(s):  
Big Five ◽  
Information Filtering ◽  
Personal Characteristics ◽  
Self Esteem ◽  
Big Five Personality ◽  
Regression Analyses ◽  
Uses And Gratification ◽  
German Speaking ◽  
Explained Variance ◽  
The Relationship

Stimulated by the uses-and-gratification approach, this study examined the joint relation of several consumer characteristics to news interest. In total, 1,546 German-speaking participants rated their interest in 15 major news categories and several personal characteristics, including gender, age, the Big Five personality traits, self-esteem, as well as general positive and negative affect. Regression analyses examined the amount of interindividual variance in news interest that can be explained by this set of consumer characteristics. Overall, the amount of explained variance differed remarkably across news categories, ranging from 4% for entertainment-related news to 25% for news about technology. The most powerful explaining variables were participants’ gender, age, openness to experiences, and their amount of general positive affect. The results suggest that news interest should be defined and operationalized as a concept with multiple facets covering a huge range of content. Also, the results are important for media producers and journalists with respect to the conflict between increased need gratification of consumers and information filtering via personalized news content.

Trust and fuzzy inference based cross domain serendipitous item recommendations (TFCDSRS)

2021 ◽  
pp. 1-13
Author(s):  
Richa ◽  
Punam Bedi
Keyword(s):  
Fuzzy Inference ◽  
Mean Absolute Error ◽  
Information Filtering ◽  
Absolute Error ◽  
User Acceptance ◽  
Decision Making Process ◽  
End User ◽  
Cross Domain ◽  
F Measure ◽  
Filtering Approach

Recommender System (RS) is an information filtering approach that helps the overburdened user with information in his decision making process and suggests items which might be interesting to him. While presenting recommendation to the user, accuracy of the presented list is always a concern for the researchers. However, in recent years, the focus has now shifted to include the unexpectedness and novel items in the list along with accuracy of the recommended items. To increase the user acceptance, it is important to provide potentially interesting items which are not so obvious and different from the items that the end user has rated. In this work, we have proposed a model that generates serendipitous item recommendation and also takes care of accuracy as well as the sparsity issues. Literature suggests that there are various components that help to achieve the objective of serendipitous recommendations. In this paper, fuzzy inference based approach is used for the serendipity computation because the definitions of the components overlap. Moreover, to improve the accuracy and sparsity issues in the recommendation process, cross domain and trust based approaches are incorporated. A prototype of the system is developed for the tourism domain and the performance is measured using mean absolute error (MAE), root mean square error (RMSE), unexpectedness, precision, recall and F-measure.

scholarly journals Recommender systems in model-driven engineering

2021 ◽  
Author(s):  
Lissette Almonte ◽  
Esther Guerra ◽  
Iván Cantador ◽  
Juan de Lara
Keyword(s):  
Recommender Systems ◽  
Information Filtering ◽  
Research Work ◽  
Model Driven Engineering ◽  
Video Broadcasting ◽  
Model Driven ◽  
Challenges And Opportunities ◽  
Mapping Review ◽  
Development Processes ◽  
Systematic Mapping Review

AbstractRecommender systems are information filtering systems used in many online applications like music and video broadcasting and e-commerce platforms. They are also increasingly being applied to facilitate software engineering activities. Following this trend, we are witnessing a growing research interest on recommendation approaches that assist with modelling tasks and model-based development processes. In this paper, we report on a systematic mapping review (based on the analysis of 66 papers) that classifies the existing research work on recommender systems for model-driven engineering (MDE). This study aims to serve as a guide for tool builders and researchers in understanding the MDE tasks that might be subject to recommendations, the applicable recommendation techniques and evaluation methods, and the open challenges and opportunities in this field of research.

Information Filtering via Improved Similarity Definition

2010 ◽  
Vol 27 (6) ◽  
pp. 068903 ◽  
Author(s):  
Pan Xin ◽  
Deng Gui-Shi ◽  
Liu Jian-Guo
Keyword(s):  
Information Filtering

scholarly journals Gravity Effects on Information Filtering and Network Evolving

PLoS ONE ◽  
2014 ◽  
Vol 9 (3) ◽  
pp. e91070 ◽  
Author(s):  
Jin-Hu Liu ◽  
Zi-Ke Zhang ◽  
Lingjiao Chen ◽  
Chuang Liu ◽  
Chengcheng Yang ◽  
...  
Keyword(s):  
Information Filtering ◽  
Gravity Effects

Network Security Isolation System Based on Information Filtering

2014 ◽  
Vol 707 ◽  
pp. 458-461 ◽  
Author(s):  
Dong Ming Zhao ◽  
Kai Feng Zhu
Keyword(s):  
Network Security ◽  
Human Life ◽  
Information Filtering ◽  
Internet Technology ◽  
Isolation System ◽  
Core Technology ◽  
Internal Network ◽  
Security Problem ◽  
New Business ◽  
Fierce Competition

Internet technology as the cutting-edge of the current information technology, it has penetrated into every aspect of human life, more and more government agencies, enterprises are using Internet to improve their office efficiency and to establish new business operation model, in order to improve its reaction ability in fierce competition. Internet has brought convenience for people to work, while the security problem of network also will follow. The internal network not only needs to ensure the security of their data, but also needs to exchange data with the external network, then by adopting network security isolation system which takes gatekeeper technology as its core technology, so that we can ensure that internal network and external network will have physical isolation at any time, meanwhile, according to business needs, it also has multiple forms of information and data’s exchanges.

scholarly journals Application of Filtration System in the Network Security

2012 ◽  
Vol 4 ◽  
pp. 38-42
Author(s):  
Jin Liang Bian
Keyword(s):  
Network Security ◽  
Information Filtering ◽  
System Structure ◽  
Estimation Methods ◽  
The Internet ◽  
Key Technology ◽  
Network Information ◽  
Filtration System

With the Internet spread and deepening of the application, the development of enterprises Internet and e-commerce business has become an inevitable trend. Network security has drawn more and more attention. Therefore, it is necessary to monitor network information real-timely by using an effective information filtering systems in the network security. So the paper discussed the system structure, the estimation methods and key technology of the Network Information Filtering System in the general and in detail.

Finite Time Decentralized Cubature Information Filtering with Directed Graph

2020 ◽  
Author(s):  
Yuan Liang ◽  
Tinghui Xin ◽  
Sibo Hu ◽  
Xiwang Dong ◽  
Qingdong Li ◽  
...  
Keyword(s):  
Directed Graph ◽  
Finite Time ◽  
Information Filtering
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