Knowledge Service System Research Articles

DESIGN AND CONSTRUCTION OF A KNOWLEDGE SERVICE SYSTEM FOR GLOBAL LAND COVER SPATIOTEMPORAL CHANGE

Abstract. Global land cover (GLC) change reflect the distribution and evolution process of various material types on the earth's surface. It is an important basic data for global natural resources survey and ecological environment research. Although many sets of GLC information service systems have been developed at home and abroad, but the knowledge stock of GLC has not been sufficiently mined, problems such as the knowledge sharing service of spatiotemporal change of GLC have not been solved. This paper reports how to design and construct a GLC spatiotemporal change knowledge service system, which provides users with accurate and in-time knowledge services for GLC spatiotemporal change through knowledge visualization, browsing and querying, knowledge recommendation, knowledge diagnosis, knowledge sharing, process simulation, knowledge graph building and spatiotemporal deduction.

Behavior Recognition of Squid Jigger Based on Deep Learning

In recent years, with the development of pelagic fishing, the working environment and monitoring of crew (squid jigger) members have become increasingly important. However, traditional methods of pelagic human observers suffer from high costs, low coverage, poor timeliness, and susceptibility to subjective factors. In contrast, the Electronic Monitoring System (EMS) has advantages such as continuous operation under various weather conditions; more objective, transparent, and efficient data; and less interference with fishing operations. This paper shows how the 3DCNN model, LSTM+ResNet model, and TimeSformer model are applied to video-classification tasks, and for the first time, they are applied to an EMS. In addition, this paper tests and compares the application effects of the three models on video classification, and discusses the advantages and challenges of using them for video recognition. Through experiments, we obtained the accuracy and relevant indicators of video recognition using different models. The research results show that when NUM_FRAMES is set to 8, the LSTM+ResNet-50 model has the best performance, with an accuracy of 88.47%, an F1 score of 0.8881, and an map score of 0.8133. Analyzing the EMS for pelagic fishing can improve China’s performance level and management efficiency in pelagic fishing, and promote the development of the fishery knowledge service system and smart fishery engineering.

Multilingual Knowledge Organization of Cultural Routes: The Case of the Grand Canal

ABSTRACTThis study collects heterogeneous information from multiple sources related to the Grand Canal, a cultural route in China, to construct a multilingual ontology of the Grand Canal. The research designs a data translation, optimization, and multilingual ontology construction method to reveal the internal and external characteristics and associations of the Grand Canal, which can provide users with multilingual and ordered knowledge of the cultural route, providing a feasible solution for digital preservation and global sharing of the cultural routes. On this basis, a multilingual knowledge service system is built.

Metodologia de desenho cultural a partir da perspectiva da filosofia cultural: um caso de ningbo

Abstract: Cultural design integrates cultural content into the design process. It is an important means to realize the innovation of traditional culture in inheritance. Cultural design behavior is subtly influenced by cultural philosophy. Specifically, cultural environment analysis, cultural semantic association and cultural imagery extraction, from the perspective of cultural philosophy, are helpful in realizing the explicitness of designers’ implicit knowledge in the process of encoding and decoding cultural genes. We select Ningbo as a sample to deeply mine the regional cultural genes, explore the generation mode of cultural design, and further propose a framework for building a cultural design knowledge service system. So as to provide methodological guidance for regional cultural design practice to build sustainable cultural design capabilities.

Characteristics Of The Knowledge Service System On The Behavior Of Preventing The Transmission Of COVID-19 In The City Of Ternate

Since the COVID-19 pandemic hit the whole world including Indonesia, there has been a change in habits in living life for all parties, including health service providers, especially hospitals, which are the last bastion in the fight against the COVID-19 pandemic. The type of research used in this study is a descriptive quantitative method, which is carried out on a set of objects which usually aims to see the characteristics in order to determine the extent of knowledge, attitudes, family support and use of media towards the knowledge service system about the behavior of preventing transmission of Covid-19 patients in Indonesia. community in Ternate City. The population in this study was all Covid-19 data recorded in medical records at the City Health Center in 2020, as many as 118 civid 19 sufferers. The sampling technique was carried out by the total sample method. The research was carried out in 2020. The results of the univariate analysis describe the distribution of respondents based on demographic characteristics (gender, education level, occupation, knowledge, family support attitudes and preventive behavior), with COVID-19 disease.

Analysis and Design of Standard Knowledge Service System based on Deep Learning

The development of information technology has changed the mode of communication of social information, and this change has put forward new requirements on the contents, methods and even objects of information science research. Knowledge service in the information service process can extract knowledge and information content from various explicit and implicit knowledge resources according to people’s needs, build knowledge networks, and provide knowledge content or solutions for users’ problems. Hence, it is very important to investigate how to analyze and design the advanced standard knowledge service system based on deep learning. To this end, we firstly introduce the typical deep learning networks of convolutional neural network (CNN) for the knowledge service system, and then employ the CNN to implement the knowledge classification based on deep learning. Finally, some simulation results on the knowledge service system are presented to validate the proposed studies in this paper.

Construction of Mental Health Knowledge Service Model Based on Online Medical Community

This paper discusses a common mental disorder prevention mode to improve residents' mental health quality and achieve the “comprehensive and fine-grained” mental health education knowledge service. The construction of mental health knowledge service model is conducive to accurately grasp the group cognition and psychological changes and take the initiative to make decisions. This paper analyzes the needs of mental health education knowledge service system and combs the research status of applying information technology and artificial intelligence to mental health education at home and abroad, the resource data of five major online medical communities at home and abroad were screened and mined, and the mental health feature tags of college students were extracted. Based on the existing mental health diagnosis experience database and multisource text, reuse and optimize ontology integration method to systematically construct mental health education ontology. Taking mental illness as an example, the rule base is constructed and the personalized recommendation service of mental health is realized. The service model can infer and output all kinds of diagnosis and treatment knowledge to provide users with intelligent mental health education knowledge services.

Agricultural Information Management Data Model Construction Based on Cloud Computing and Semantic Technology

In order to improve the data retrieval and mining ability of agricultural information management system, an agricultural information management data model based on cloud computing and semantic technology was proposed. Fuzzy C-means algorithm is used for adaptive fusion and clustering of semantic association features of distributed data in large-scale information management systems; feature compressors are used to reduce the storage space dimension of large-scale information management system to improve the target data mining capability and adaptive scheduling capability of information management system. The registration rate improves than the traditional method by 12.46% and computational cost by 23.76%. This method has higher accuracy in storage data mining and retrieval for large information management systems and superior performance than the traditional method. The introduction of the concept and technical methods of related data is the best practice to realize the fine disclosure, standardized description, semantic organization, and in-depth integration of massive agricultural science and technology information resources, which will play an important role in improving the visibility, visibility, and accessibility of agricultural information resources. It is innovative in the construction of the multidimensional semantic-related model and field knowledge service system driven by related data.

A Smart Healthcare Knowledge Service Framework for Hierarchical Medical Treatment System.

This paper reveals the research hotspots and development directions of case-based reasoning in the field of health care, and proposes the framework and key technologies of medical knowledge service systems based on case-based reasoning (CBR) in the big data environment. The 2124 articles on medical CBR in the Web of Science were visualized and analyzed using a bibliometrics method, and a CBR-based knowledge service system framework was constructed in the medical Internet of all people, things and data resources environment. An intelligent construction method for the clinical medical case base and the gray case knowledge reasoning model were proposed. A cloud-edge collaboration knowledge service system was developed and applied in a pilot project. Compared with other diagnostic tools, the system provides case-based explanations for its predicted results, making it easier for physicians to understand and accept, so that they can make better decisions. The results show that the system has good interpretability, has better acceptance than the common intelligent decision support system, and strongly supports physician auxiliary diagnosis and treatment as well as clinical teaching.

Based on the new old crowd digital currency consciousness Design of knowledge service system

China is facing the rapid development of digital technology torrent and the increasingly serious aging population problem, the development of technology has led to a digital economy and cashless society. While people conveniently carry out economic activities through digital means, social problems such as network fraud, theft of others' privacy, digital divide and other social problems have gradually become prominent. Older people are more likely to fall victim to digital isolation and online fraud due to their ability (especially cognitive ability) decline and behavioral fixation, derailment from the experiences learned in the cash society, and lack of appropriate digital citizenship education. Starting from the concept of service design and starting from the current situation of the demand of people aged 50-70 (referred to as the new elderly people), the content framework of the new elderly people in the era of digital economy is summarized, and a sustainable knowledge service system of "people-contact-environment" interaction is constructed with mobile applications as the carrier.

Resource Classification and Knowledge Aggregation of Library and Information Based on Data Mining

The traditional knowledge service systems have nonuniform data structures. Some data are structured, while some are semi-structured and even non-structured. Big data technology helps to optimize the integration and retrieval of the massive data on library and information (L&I), making it possible to classify the resources and optimize the configuration of L&I resource platforms according to user demand. Therefore, this paper introduces the new information service model of big data resources and knowledge services to the processing of L&I data. Firstly, the data storage structure and relationship model of the L&I resource platform were established, and used to sample and integrate the keywords of resource retrieval. Next, an L&I resource classification model was constructed based on support vector machine (SVM), and applied to extract and quantify the attributes of the keywords of resource retrieval. After that, a knowledge aggregation model was developed for a complex network of multiple L&I resource platforms. Experimental results demonstrate the effectiveness of the proposed knowledge aggregation model. The research findings provide a reference for the application of data mining in resource classification.

Construction of the knowledge service model of a port supply chain enterprise in a big data environment

In the context of the rapid development of big data and artificial intelligence, knowledge service theory and big data technology are applied to build a smart port supply chain knowledge service model. This model provides a personalized, intelligent, and diversified knowledge-based service system platform solution to port supply chain enterprises, helping to realize port supply chain transformation and upgrading and intelligent integrated operations. This paper analyses and summarizes the research status on knowledge service demand and port supply chain knowledge service during the development and operation of the port supply chain and applies big data and artificial intelligence technologies such as knowledge matching, knowledge fusion, and natural language processing. A port supply chain knowledge service model including knowledge acquisition, knowledge organization and knowledge service modules is constructed. The ontology method is used to construct the ontology knowledge base of the port supply chain, and based on this, computational reasoning experiments are performed. The experiments show that ontology technology demonstrates effectiveness and superiority in constructing a knowledge service system model for the port supply chain in terms of knowledge representation and knowledge reasoning.

Knowledge Service Model of Port Supply Chain Enterprise Based on Ontology

Under the background of the development of port industry and information age, with the help of the knowledge service theory system and ontology technology to build a smart port supply chain knowledge service model to provide a personalized, intelligent, and diversified knowledge-based service system platform solution to port supply chain enterprises, which is of great significance to realization of port supply chain transformation and upgrading and intelligent integrated operation. Based on the analysis of the demand for knowledge service and the research status of knowledge service in port supply chain during the development and operation of port supply chain, this paper uses ontology technology to build domain ontology knowledge base, which is used to dismantle and integrate the massive digital resources in port supply chain, integrate various multi-source heterogeneous data resources, and standardize the form of knowledge sharing organization. On the basis of this, the paper carries on the calculation and reasoning experiment to the port supply chain ontology. The experiment shows that the ontology technology has good effectiveness and superiority in the knowledge representation and knowledge reasoning of constructing the port supply chain knowledge service system model.

Research on the Construction of Knowledge Service Model of Port Supply Chain Enterprise in Big Data Environment

In the context of the rapid development of big data and artificial intelligence, with the help of the knowledge service theory system and big data technology to build a smart port supply chain knowledge service model to provide a personalized, intelligent, and diversified knowledge-based service system platform solution to port supply chain enterprises, which is of great significance to realization of port supply chain transformation and upgrading and intelligent integrated operation. This paper analyzes and summarizes the research status of knowledge service demand and port supply chain knowledge service during the development and operation of port supply chain, and applies big data and artificial intelligence technologies such as knowledge matching, knowledge fusion, and natural language processing. The port supply chain knowledge service model including knowledge acquisition, knowledge organization and knowledge service modules is constructed. Ontology method is used to construct the ontology knowledge base of port supply chain, and based on this, computational reasoning experiments are performed. The experiments show that the ontology technology shows good effectiveness and superiority in constructing the knowledge service system model of the port supply chain in terms of knowledge representation and knowledge reasoning.

Process Knowledge Recommendation System for Mechanical Product Design

To solve the problems of high time cost caused by the low efficiency of knowledge acquisition, this paper proposes a knowledge service framework based on case set. Three knowledge retrieval methods are designed based on parts keywords, customer orders and manufacturing processes. Additionally, a VSM-based (vetor space model) knowledge recommender method is proposed by using similarity matching algorithm to improve the efficiency of knowledge acquisition and transfer. Finally, application scenarios and evaluation of the proposed approach in a mechanical product design project are given to illustrate the application effect of knowledge service system.

WeChat knowledge service system of university library based on SoLoMo: A holistic design framework

In this study, we develop a WeChat knowledge service system (WKSS) in university library based on SoLoMo. The aim is to build a comprehensive, open, mobile and smart knowledge service environment. It can realise the interaction between the three users, library and knowledge, and promote the dissemination and sharing of knowledge. By referencing the Internet frontier concept SoLoMo, this study designs a new mobile smart service system, including the system architecture design, the content design and the data association design. Then, this study develops the system, including the running environment configuration, the development of workflow, the core module and the system implementation. This system enables the provision of accurate, specific and more personalised service to each user. It also includes a portable mobile terminal to increase the accuracy of context awareness and enhance user convenience. This study makes up for the shortcomings of the library and increases the functions of personalisation, mobility and intelligence. It extends the way of mobile service in libraries and provides readers with better library mobile services, which was liked by readers.

Intelligent Knowledge Service System Based on Depression Monitoring of College Students

The number of college students suffering from depression has increased in recent years. In order to help the college student administration departments understand students' psychological state of depression better and keep college students mentally healthy through mental health services, this paper studies an intelligent monitoring system for depression. Different from previous researches, this study, based on the cloud services platform, incorporates three indicators closely related to depression-sleeping, exercise and heart rate-into the monitoring database subsystem and establishes a relatively macroscopic intelligent knowledge service system for depression monitoring of college students. It uses the Mobile Material Link Device (MMLD) to collect data and information to monitor and analyze the changes in the depression status of college students dynamically, which also provides timely warnings and a chain of personalized intelligent knowledge services based on individuals’ depression status.

Enlightenment of Living Library to Knowledge Service of University Library

Living library is a brand new service way that has emerged in the library community at home and abroad in recent years. “Living library” is to take the "people" as "books" to build the new way of library knowledge services. The “borrowing” of “books” is to make face-to-face communication with people with expertise, providing “borrowing experts” for readers to answer questions and discuss with them, and provide a wide range of knowledge services and intellectual help for readers. At present, this kind of service has been tried in China. In the context of vigorously advocating knowledge services, the living library project can provide reference for the improvement of the knowledge service system of university libraries.

The Research and Practice of Professional Knowledge Sharing and Service: A Case Study of the Geography, Resources, and Ecology Knowledge Service System

Knowledge Sharing and Service is one effective way to eliminate knowledge poverty and promote social development. Existing knowledge sharing and service is mainly provided in some organizations or specific social groups. Besides, a knowledge sharing and service system about geography, natural resources and ecology has not been reported. We proposed a public welfare professional knowledge-sharing and service platform for all members of society in geography, natural resources and ecology. The construction of a knowledge-sharing and service platform is based on five aspects of work: analysis of user requirements, setting standards and drafting policies, aggregating knowledge resources, the technical realization and the maintenance of service. Knowledge resources can be aggregated by using a “two-step” strategy. A knowledge-sharing and service system can be implemented by using “four-tier” structures that are comprised of resources, resource access, application and service, based on the Hadoop-distributed cluster architecture. It has been proven that adhering to the idea of co-building and co-sharing, and using the mechanism of “payment is equal to benefit” can effectively promote the gathering of knowledge resources, and arouse the enthusiasm of all members of society to participate in knowledge sharing and service, to achieve the objective of narrowing the knowledge gap between social groups.

The Problem-Solving Agricultural Knowledge Service System for Farm Households

With the advancement of agricultural modernization of China, farmer’s demand of agricultural service has turned from the traditional agricultural information service to the problem-solving mode gradually. Professional, personalized knowledge service is required. How to use Internet-thinking to construct problem-solving agricultural science and technology knowledge service system which is used to solve all kinds of problems in the process of agricultural production for farmers is the core content of our development. In this paper, system architecture and some major function features are introduced. Through the running of the system, the problems in the system are analyzed and the optimal solutions are proposed. Scientific and technological progress and innovation is the guarantee of the sustainable development of agriculture. With the advance of agricultural modernization, demand of china farmers of agricultural science and technology service has from the traditional agricultural information services, gradually turned to the purpose of problem-solving mode. How to effectively use the mobile Internet to provide fast, efficient, professional and personalized service for the majority of farmers, break the agricultural expert system affiliation, bring together experts in different fields to realize agricultural experts and farmers 24 hours face-to-face information interaction, realize the precision agriculture technology service, effectively solve the problem of farmers’ fields of production is the core content of the development of this system.