scholarly journals Research on Recommendation Operation Strategy of News and Information Products

2020 ◽  
Vol 2 (1) ◽  
Author(s):  
Yuxi Liu

<p>For China’s news industry, personalized recommendation of news and information products is beginning to take off, but it is growing rapidly. Excess information content and limited time and energy of users urgently need common numbers to balance. It is not the ultimate goal to blindly provide users with instant news content as media. With the rising status of users, the times have higher requirements for media. In today’s society, improving information processing ability is more important than the speed of information dissemination. Users are forbidden to keep copper in the information cage. Repeated bloody, violent, misleading and other information are distressing. How to solve information overload for news and information product operators? How to adjust operation strategy from the perspective of users? How to solve the relationship between technical algorithm and manual intervention? How can personalized recommendation promote the development of news industry?</p>

2019 ◽  
Vol 64 (1) ◽  
pp. 103-116
Author(s):  
ЛЕСЯ МУШКЕТИК

The oral folk prose of Transcarpathia is a valuable source of history and culture of the region. Supplementing the written sources, it has maintained popular attitudes towards events, giving assessments and interpretations that are often different from the official one. In the Ukrainian oral tradition, we find many words borrowed from other languages, in particular Hungarian, which reflects the long period of cohabitation as well as shared historical events and contacts. They also occur in local toponymic legends, which in their own way explain the origin of the local names and are closely linked with the life and culture of the region, contain a lot of ethnographic, historical, mythological, and other information. They are represented mainly by lexical borrowings, Hungarian proper names and realities, which were transformed, absorbed and modified in another system, and, among other things, has served the originality of the Transcarpathian folklore. The process of borrowing the Hungarianisms is marked by heterochronology and a significant degree of assimilation in the receiving environment. It is known about the long-lasting contacts of the Hungarians with Rus at the time of birth of the homeland - the Honfoglalás, as evidenced by the current geographical names associated with the heroes of the events of that time - the leaders of uprisings Attila, Almash, Prince Latorets (the legends Almashivka, About the Laborets and the White Horse Mukachevo Castle). In the names of toponymic legends and writings there are mentions of the famous Hungarian leaders, the leaders of the uprisings - King Matthias Corvinus, Prince Ferenc Rákóczi II, Lajos Kossuth (the legends Matyashivka, Bovtsar, Koshutova riberiya). Many names of villages, castles and rivers originate from Hungarian lexemes and are their derivatives, explaining the name itself (narratives Sevlyuskyy castle, Gotar, village Gedfork). The times of the Tatar invasion were reflected in the legends The Great Ravine Bovdogovanya and The village Goronda. Sometimes, the nomination is made up of two words - Ukrainian and Hungarian (Mount Goverla, Canyon Grobtedie). In legends, one can find mythological and legendary elements. The process of borrowing Hungarianisms into Ukrainian is marked by heterochronology, meanwhile borrowings remain unchanged only partially, and in general, they are assimilated in accordance with the phonetic and morphological rules of the Ukrainian language. Consequently, this is a creative process, caused by a number of different factors - social, ethnocultural, aesthetic, etc. In the course of time, events and characters in oral narratives are erased from human memory, so they can be mixed, modified and updated, adapting to new realities.


Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Chaohua Fang ◽  
Qiuyun Lu

With the rapid development of information technology and data science, as well as the innovative concept of “Internet+” education, personalized e-learning has received widespread attention in school education and family education. The development of education informatization has led to a rapid increase in the number of online learning users and an explosion in the number of learning resources, which makes learners face the dilemma of “information overload” and “learning lost” in the learning process. In the personalized learning resource recommendation system, the most critical thing is the construction of the learner model. Currently, most learner models generally have a lack of scientific focus that they have a single method of obtaining dimensions, feature attributes, and low computational complexity. These problems may lead to disagreement between the learner’s learning ability and the difficulty of the recommended learning resources and may lead to the cognitive overload or disorientation of learners in the learning process. The purpose of this paper is to construct a learner model to support the above problems and to strongly support individual learning resources recommendation by learning the resource model which effectively reduces the problem of cold start and sparsity in the recommended process. In this paper, we analyze the behavioral data of learners in the learning process and extract three features of learner’s cognitive ability, knowledge level, and preference for learning of learner model analysis. Among them, the preference model of the learner is constructed using the ontology, and the semantic relation between the knowledge is better understood, and the interest of the student learning is discovered.


2018 ◽  
Vol 7 (2) ◽  
pp. 112-118
Author(s):  
Febri Hadi ◽  
Hadi Syahputra ◽  
Yusvi Diana

The purpose of this research is to produce a system e-commerce in transact sales and reservations handicrafts rattan that is there the .Hopefully with a e-commerce this can save such as the operational costs , time and energy .E-commerce system is designed by using programming language html and php .To embellish of a display web used bootstraps .Of the system resulting can be concluded that is , ease in terms of the selling process products , information products , and the process of reservations intended products by consumers.


2021 ◽  
Author(s):  
Richmond Takyi Hinneh ◽  
Alex Barimah Owusu

Abstract BackgroundIn an era of the global pandemic and social media dominance, trying to control the narrative on COVID-19 has been a challenging task for most governments particularly with news about the disease on various social media platforms. There have even been instances where people have sent false information about the number of confirmed cases, precautionary measures, drugs that boost the immune system which can threaten the lives of some users who are accessing this false information and misconceptions.Method This study analyzed spatial differences in Twitter misinformation on COVID-19 across 16 regions of Ghana by scraping 1,167 tweets from Twitter using API access. A total of 514 tweets were analyzed. The data were categorized into three namely; accurate information, misinformation, and other information. ResultsThe study results show that 72% of the tweets were accurate, 14% were misinformation and 14% represented other information. Among the regions, Greater Accra had the highest number of accurate information (45 tweets), and the Upper West Region recording the highest number of misinformation (12 tweets).ConclusionSpatial monitoring and management of information dissemination are useful for target setting and achievement of direct results in terms of diffusing misinformation and propagating accurate information. We, therefore, recommend official usage of Twitter for COVID-19 information dissemination as this usage will help offset possible misinformation from unformed individuals.


Author(s):  
P. Senthil Priya ◽  
N. Mathiyalagan

The agricultural sector is the largest and most critical economic sector and a developing country like India, with its economic backbone as agriculture, is highly dependent to sustain its population. To compete with other agricultural economies, a need exists to create effective linkage between the seat of agricultural production and market forces involved in the provision of goods to the consumers within India. A strong network communication must be established between the various stakeholders of agricultural trade to facilitate a balance between demand and supply. With the advent of mobile phones, internet, and other Information and Communication Technologies, new possibilities and multi-dimensional factors that create instant communication between the target groups have emerged and these ICT tools could be used as a source of agricultural information dissemination to the farmers. This paper analyses mobile based agricultural Market Information Services (MIS) that deliver critical market price information to farmers in Tamilnadu, India. The study also provides an overview of the ICT based mobile market linkage systems and analyses the operability of such projects. The study also assesses the benefits of such projects in providing relevant information to the farmers and the emerging opportunities for rural farmers to make constructive use of the e-agriculture projects.


2014 ◽  
Vol 989-994 ◽  
pp. 4996-4999 ◽  
Author(s):  
Yan Zhang

With the rapid development of electronic commerce, the problem of "information overload" leads to the difficulty that user can't search the required goods effectively , personalized recommendation technology has been applied in e-commerce and popularization. By using the method of qualitative analysis of the current e-commerce site, the paper compare the information retrieval, association rule, content-based filtering and collaborative filtering four main recommendation technologies and analysis the advantages and disadvantages in the application layer, the recommendation technologies are introduced to review e-commerce research hot topic in the field of personalized recommendation, and analysis the current domestic e-commerce personalized recommendation theory research and application status, finally propose the challenges faced by e-commerce personalized recommendation domain.


2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Biao Cai ◽  
Xiaowang Yang ◽  
Yusheng Huang ◽  
Hongjun Li ◽  
Qiang Sang

Recommendation systems are used when searching online databases. As such they are very important tools because they provide users with predictions of the outcomes of different potential choices and help users to avoid information overload. They can be used on e-commerce websites and have attracted considerable attention in the scientific community. To date, many personalized recommendation algorithms have aimed to improve recommendation accuracy from the perspective of vertex similarities, such as collaborative filtering and mass diffusion. However, diversity is also an important evaluation index in the recommendation algorithm. In order to study both the accuracy and diversity of a recommendation algorithm at the same time, this study introduced a “third dimension” to the commonly used user/product two-dimensional recommendation, and a recommendation algorithm is proposed that is based on a triangular area (TR algorithm). The proposed algorithm combines the Markov chain and collaborative filtering method to make recommendations for users by building a triangle model, making use of the triangulated area. Additionally, recommendation algorithms based on a triangulated area are parameter-free and are more suitable for applications in real environments. Furthermore, the experimental results showed that the TR algorithm had better performance on diversity and novelty for real datasets of MovieLens-100K and MovieLens-1M than did the other benchmark methods.


2015 ◽  
Vol 713-715 ◽  
pp. 1530-1533
Author(s):  
Yuan Zi He

Personalized recommendation offers a new way to solve the problem of information overload. In order to effectively build user model and improve the effect of personalized recommendation, this paper proposes a novel model for mining contextual information of non-structure text, and insects the contextual information into user model, which enriches user model. The experiment results shown that the model can greatly improve the recommendation performance when the model is applied to contextual data of the recommender system in hotel.


2012 ◽  
Vol 267 ◽  
pp. 79-82
Author(s):  
Pu Wang

Recommender systems have been successfully used to tackle the problem of information overload, where users of products have too many choices and overwhelming amount of information about each choice. Personalization is widely used in various fields to provide users with more suitable and personalized service. Many e-commerce web sites such as online shop retailers make use of recommendation systems. In order to make recommendations to a user, collaborative filtering is an important personalized recommendation technique applied widely in E-commerce. The collaborative approach faces the hard issue of cold start problem and the matrix sparsity problem. The paper presents a collaborative filtering personalized recommendation approach based on ontology in the special domain. The method combines ontology technology and item-based collaborative filtering. The given recommendation approach can tackle the traditional recommenders problems, such as matrix sparsity and cold start problems.


2020 ◽  
Vol 7 (3) ◽  
pp. p75
Author(s):  
Yueli Bao

In the new epoch, society is continuously advancing. With the accelerated development of network information dissemination, music education should satisfy the development of the times. Teaching methods should also be contemporary and innovative. With the introduction and development of quality concepts, music education is slowly improving. As a self-governing subject, it should be valued by teachers and students. Mr. Wu Guodong’s “Chinese National Music” concentrates on networked teaching and the “new teacher-training” of the new era. He strives to make more students experience the infinite charm of Chinese national music, build a distinct academic philosophy, and reshape the Chinese national spirit.


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