Internet Information Services Research Articles

Legal Risk Prevention for Personalized Recommendation Algorithms

Abstract Personalized recommendation algorithms, designed to cater to users’ individualized preferences and enhance the efficiency of Internet information services, have inadvertently precipitated significant legal risks, notably the potential for user privacy breaches. This development necessitates prompt and appropriate legal responses. This paper presents an approach utilizing cosine similarity and Pearson correlation to establish a set of nearest neighbors, facilitating the identification and querying of the closest users based on similarity metrics. Subsequently, we implement a collaborative filtering recommendation algorithm tailored to these personalized settings. We thoroughly evaluate the legal risks associated with the application of customized recommendation algorithms, supplemented by detailed case analyses. The Pareto chart of risk crisis factors reveals that the frequency of issues related to policy legislation and technical concerns are 165 and 95, respectively, cumulatively accounting for 46.68% of the probability share—nearly half of all identified factors. This highlights the critical need for focused attention in these areas. Furthermore, our analysis calculates the probability and severity of data leakage across various paths within the recommendation process. Results indicate severities of 0.029, 0.0333, 0.0409, 0.0447, 0.0481, and 0.165, with the most significant vulnerability appearing in the final recommendation phase to the user, underscoring the imperative to prioritize data privacy in this module. In response, we propose modifications to the existing models to incorporate principles of differential privacy, aiming to mitigate these legal risks and enhance the security and reliability of personalized recommendation algorithms. This initiative is essential for aligning technological advancements with stringent privacy standards and legal requirements.

MPCM: Multi-modal User Portrait Classification Model Based on Collaborative Learning

A social-media user portrait is an important means of improving the quality of an Internet information service. Current user profiling methods do not discriminate the emotional differences of users of different genders and ages on social media against a background of multi-modality and a lack of domain sentiment labels. This paper adopts the sentiment analysis of images and text to improve label classification, incorporating gender and age differences in the sentiment analysis of multi-modal social-media user profiles. In the absence of domain sentiment labels, instance transfer learning technology is used to express the learning method with the sentiment of text and images; the semantic association learning of multi-modal data of graphics and text is realized; and a multi-modal attention mechanism is introduced to establish the hidden image and text. Alignment relationships are used to address the semantic and modal gaps between modalities. A multi-modal user portrait label classification model (MPCM) is constructed. In an analysis of the sentiment data of User users on Facebook, Twitter, and News, the MPCM method is compared with the naive Bayes, Latent Dirichlet Allocation, Tweet-LDA and LUBD-CM(3) methods in terms of accuracy, precision, recall and the FL-score. At a 95% confidence, the performance is improved by 1% to 4% by using the MPCM method.

Development of fixed broadband Internet access in Ukraine

Nowadays, the level of accessibility to Internet resources and information services to the population is considered the most essential characteristic of the state’s economic development. The United Nations (UN) includes citizens’ right to access the Internet in the list of basic human rights. In order to ensure the provision of broadband access to every citizen throughout the country, the state faces the task of creating the appropriate telecommunications infrastructure. The article considers the task of developing (modernizing) the subscriber segment (level) of the fixed broadband access network (FBA) to the Internet based on the G.fast telecommunications technology according to the ITU-T Recommendation G.9700. The technical characteristics of access network options using multi-pair metal cables of the type TPP-10x2x0.4 and «twisted pair» Cat.5e 10x2x0.5 are being studied. Obtained comparative characteristics of the access speed depending on the frequency and transient characteristics of the cables, power of additive, and transient interference. A significant result is a study of the effectiveness of the implementation of technology for compensation of transient interference between «Vectoring» systems in G.fast transmission systems according to the ITU-T Recommendation G.993. Studies prove that using a cable of the type «Twisted pair» UTP Cat.5e 10x2x0.5 ensures a higher speed of operation than using a cable of the type TPP-10x2x0.4. Without the use of the Vectoring «Twisted pair» UTP Cat.5e 10x2x0.5 transient interference compensation system, it provides 400-500 Mbps FBA speed with a cable length of up to 250 m, which is higher than the TPP cable. The obtained results make it possible to develop economically attractive strategies for the development of FBA networks, taking into account the existing features of the networks. Modernization of the network using G.fast technology can significantly improve access to high-speed Internet for millions of Ukrainian citizens, contributing to the country’s digital transformation and increasing its competitiveness in the global market.

Research on Hybrid Recommendation Model for Personalized Recommendation Scenarios

One of the five types of Internet information service recommendation technologies is the personalized recommendation algorithm, and knowledge graphs are frequently used in these algorithms. RippleNet is a personalized recommendation model based on knowledge graphs, but it is susceptible to localization issues in user portrait updating. In this study, we propose NRH (Node2vec-side and RippleNet Hybrid Model), a hybrid recommendation model based on RippleNet that uses Node2vec-side for item portrait modeling and explores potential association relationships of items; the user portrait is split into two parts, namely, a static history portrait and a dynamic preference portrait; the NRH model adopts a hybrid recommendation approach based on collaborative filtering and a knowledge graph to obtain the user’s preferences on three publicly accessible datasets; and comparison experiments with the mainstream model are lastly carried out. The AUC and ACC increased, respectively, by 0.9% to 29.5% and 1.6% to 31.4% in the MovieLens-1M dataset, by 1.5% to 17.1% and 4.4% to 18.7% in the Book-Crossing dataset, and by 0.8% to 27.9% and 2.9% to 24.1% in the Last.FM dataset. The RippleNet model was used for comparison experiments comparing suggestion diversity. According to the experimental findings, the NRH model performs better in accuracy and variety than the popular customized knowledge graph recommendation algorithms now in use.

APPLICATION OF E-LEARNING AS A LEARNING MEDIUM FOR INFORMATION TECHNOLOGY

With advances in internet network technology, information and communication services are no longer constrained by time and place constraints. Online learning emphasizes distance learning to provide the best educational process possible. Online learning is a type of information technology advancement that can be used as a teaching aid. In this work, the authors use descriptive research techniques to conduct a more in-depth analysis of the theories and trends in advances in online learning. The University of Illinois at Urbana-Champaign is a pioneer in the development of online education. In a computer-based education system, the University of Illinois has started e-learning by utilizing a computer called PLATO. The e-learning classroom learning model is a significant development in the teaching and learning process because it can reduce variations in teaching strategies and course materials and increase the consistency of learning. To prepare, with the help of technology, when everything shifts to the digital era, both in terms of methods and content, online learning systems are very important.

China's algorithmic regulations: Public-facing communication is needed

China has recently finalized its first algorithmic regulations—The Internet Information Service Algorithmic Recommendation Management Provisions. The Provisions request technology companies to remove discriminatory or biased user tags or refrain from generating or fuelling fake news via algorithms. Under the guidance of the Provisions, Internet users will also be able to choose whether and to what extent they wish to receive algorithmic recommendations. However, what is missing from the Provisions is information on how individual users should report potential abuse to the authorities, above and beyond the channels provided by technology companies. To shed light on the issue, this article discusses the need for a public-facing platform that could allow people to timely and effectively communicate with authorities who can help address their algorithmic security concerns, as opposed to relying on solutions provided by Internet companies that might be the very source of their issues.

An Information‐Resilient Big‐Data Workbench with PDP‐DREAM Software

ABSTRACTPORTAL‐DOORS Project DREAM Software, available as an open‐source C#‐centric codebase from a Github public repository at PDP‐DREAM, implements the PDP‐DREAM principles and PDP‐FAIR metrics with web‐enabled workbench software for distributed data repositories in the Nexus‐PORTAL‐DOORS‐Scribe Cyberinfrastructure. PDP‐DREAM Software has been developed for Microsoft platform technologies with ASP.NET Core, SQL Server, and Internet Information Server. As a web‐enabled workbench, PDP‐DREAM provides many features for big data management with tools and services to support information resilience in defense of truth in science and integrity in research.

Time Series Anomaly Detection Model Based on Multi-Features.

For Internet information services, it is very important to closely monitor a large number of key time series data generated by core business for anomaly detection. Although there have been many anomaly detection models in recent years, its practical application is still a big challenge. The model usually needs repeated iteration and parameter adjustment; and for different types of time series data, we need to select different models. Therefore, this paper proposes an anomaly detection model based on time series. The model first designs the statistical features, fitting features, and time-frequency domain features for the time series, and then uses the random forest integration model to automatically select the appropriate features for anomaly classification. In addition, this paper presents an anomaly evaluation index ADC score with timeliness window, which adds the time delay factor of anomaly detection on the basis of F1-score. We use the KPI time series, a representative key performance index in the industry, as the experimental data. It is found that the ADC score of the anomaly detection model in this paper reaches the level of 0.7–0.8, which can meet the needs of practical application.

The Internet Information Services Algorithm Recommendation Management (IISARM) Regulations in China

Article The Internet Information Services Algorithm Recommendation Management (IISARM) Regulations in China was published on August 1, 2022 in the journal Computer Law Review International (volume 23, issue 4).

Innovation and Development of Cultural and Creative Industries Based on Big Data for Industry 5.0

While art design is based on innovation and creativity, information technology is advancing by leaps and bounds for Industry 5.0. Big data technology has achieved breakthrough development, and the big data era that has followed has begun. Promoting the resources, technology, thinking big data is the general trend. It is an important expression of creative thinking, which is closely connected with art design and studies the relationship between design and art. As the starting point for research, the average growth rate of China's cultural and creative industries is as high as 26.08%, which is not only limited by the growth rate of traditional industries. More results show that, in 18 years, radio, television, and Internet information services, which are rapidly developing, accounted for 27.9%, 21.8%, and 20.3%, while the advertising, exhibition, tourism, and leisure industries have also steadily increased, and they accounted for 9.6% and 7.1% of the total share. These research results show that the design art and cultural and creative industries are complementary.

Reliability evaluation for deployment of multi service multi functional service oriented computing based on different techniques

Reliability evaluation of service-oriented computing against massive stresses of end users imputes greater emphasis on adaptability of different hosting techniques. As such, we propose to study the failure and reliability aspects of multi service-based web services by using Tomcat and Internet Information Service web server. The service roles such as broker, parent and service provider are segregated among different services. We present here in detail the architecture, a reliability evaluation framework, experimentally and statistically analysed results to establish the applicability of the proposed work. The overall assessment of such deployment in respective web servers highlights the dynamic nature of service reliability. The results shows that the reliability of Internet Information Service is better than Tomcat web server but the efficiency of processing massive request is comparatively poor than its counterpart. Also, the reliability of segregation of web service role is observed to be better than the merged roles.

Sharing Cellavision Blood Smear Images with Clinicians Via the Electronic Medical Record

BackgroundThe CellaVision automated system digitizes peripheral blood smears and performs blood cell differentials. These images are available for local review in hematology laboratories on computer monitors or they can be transmitted for remote review via telehematology. Clinicians such as hematologists who typically review their patient's peripheral blood smears often need to contact an offsite hematology hospital laboratory for this purpose, frequently during evening or weekend hours. To overcome this barrier, our institution sought to make CellaVision blood smear images available to clinicians and trainees in the electronic medical record (EMR). The images could therefore be viewed at any time and from any computer or mobile device which could access the EMR.TechnologyCellaVision DM96 (CellaVision AB, Lund, Sweden) digital hematology analyzers. Images hosted on a Microsoft SQL Server. Microsoft Internet Information Services 7 web server and ColdFusion 9 middleware. Sunquest laboratory information system. Cerner PowerChart EMR.DesignImage sharing was accomplished in 2 phases. For phase 1, a secure web portal (called “HemaVue”) was created to allow clinicians to access CellaVision digital images with associated metadata (i.e. patient unique identifiers, blood counts). CellaVision image data was archived daily and stored for 6 months. For phase 2, CellaVision instrument results were tagged with the test code “Image Differential Performed”. This code appeared in the patient result to inform the clinician this type of differential had been performed, as opposed to a manual or automated differential code. The HL7 message router transmitting results with this tag created a link in the EMR to the HemaVue website. This allowed clinicians to access CellaVision images from a patient's chart within the EMR.ResultsThe CellaVision image database contained 3.38 million images for 23,000 patients, comprising 12TB of data on per 6 month temporal storage. Database and website maintenance had to be internally supported. While clinicians were pleased with having access to blood smear images, they expressed dissatisfaction that images were not always available immediately, not retained indefinitely, not offered on all patients, and that the images were of isolated white blood cells only.ConclusionCellaVision images were able to be successfully unlocked from the vendor's server and subsequently made accessible for remote viewing by linking patients' laboratory results in the EMR to a custom built website. While such enterprise image sharing of digital blood images offered some improvement for clinicians seeking to review peripheral blood smears, enhancements will be required to make this more readily available for all patients at our institution. DisclosuresNo relevant conflicts of interest to declare.

Development of an Automated Management System for Agricultural Technologies in Horticulture

The implementation of intelligent technologies in industrial horticulture is possible with the help of an automated system for managing production processes. (Research purpose) To develop and substantiate the parameters of an automated management system for agricultural technologies in horticulture with the ability to conduct land inspections using a mobile application. (Materials and methods) ADO.NET driver Npqsql was used for work with the database. Dapper was used as Object Relational Mapping. The web application used the Model View Controller design pattern, and Bootstrap as the css framework. Data visualization from the database was carried out using cloud technology, placing the site using a set of Internet Information Services. Jquery (a set of JavaScript functions) served as the main framework for working with the client-side of the program code. The authors also used the PostgreSql database management system. The mobile application was created in the Android studio integrated environment. (Results and discussion) The authors developed an automated system for managing agricultural technologies. They formed the structure of the hardware and software base. They created the system ability to operate in a dialogue mode with the user through forms, based on the algorithm for choosing the optimal options for technological processes in the horticultural products production. A mobile application was implemented to conduct digital land inspections. They determined the procedure for conducting land inspections by agronomists using a mobile application. (Conclusions) The authors developed a system for the automated technologies formation and management in horticulture, which provided operational processing of information flows in real time, reflecting the characteristics of the plants’ growth and state in critical phases of development. They provided modern recording devices and a mobile application operation. They showed that the system automatically optimized machine technologies for the cultivation of horticultural crops according to biological (realization of the potential biological productivity of crops) and economic (increasing the efficiency of using production resources) criteria.

Utilization Of Information Technology In The Field Education (E-education)

The development of information technology makes it easy to communicate the exchange of information so that the place, time and distance are no longer an obstacle. The development of information technology so rapidly could not be separated from the development of computer engineering. Advances in computer and information technology also provides a positive impact on education. Application areas of computer technology and information technology are the most influential in the field of education is the use of computer networks and the Internet. With the internet information services to target students are not limited space, where time and distance. Through the internet information services can be provided as a source of learning, learning media can be studied according to the speed of learners. Media study is not limited to letters and pictures but can be combined with graphics, animations, video, audio together so that the media is better known as multimedia. Positive influence of Internet use for education in developing human resources education should be able to follow the development of science and technology applications. Applications include the industrial world so that graduates are able to meet the demands of the workplace competencies. Based on these facts one way to be able to follow the rapid development of science and technology is to always access the information up to date and all it can in the can over the internet. However, its implementation is still required in support of infrastructure and human resource capabilities well as providers, managers and information users.

Neural Network Web-Based Human Resource Management System Model (NNWBHRMSM)

As business activities are becoming increasing globally and as numerous firms expand their operations into overseas markets, there is need for human resource management (HRM) to ensure that they hire and keep good employees. From ages, firms/organizations have been having great problems in getting the right professionals into appropriate jobs and training. This research focuses at exploiting information technology in order to overcome these problems. The system, which is a network of inter–related processes, collects data from applicants through a web-based interface and matches with appropriate jobs. This prevents the frustration and some other problems inherent in the manual method of job recruitment, which is the traditional unstructured interview and knowledge based method for matching applicants to jobs. The proposed system is a neural network web-based human resource management system model running on Internet Information (IIS) server with capabilities for Active Server Page (ASP) and Microsoft Access; while Hypertext Markup Language (HTML) are used for authoring web pages. Finally, the system can run on the minimum Pentium machines with Windows XP operating system

Impact analysis of SYN flood DDOS attack on HAPROXY and NLB cluster-base web servers

<p>In recent, the high available internet service is main demand of the most people. However, online services occasionally become inaccessible due to various threats and attacks. Synchronization (SYN) flood Distributed Denial of Service (DDoS) is the most used and has a serious effect on the public network services. Hence, the outcome of this attack on the commonly utilized cluster-based web servers is systematically illustrated in this paper. Moreover, performance of Internet Information Service 10.0 (IIS 10.0) on Windows server 2016 and Apache 2 on Linux Ubuntu 16.04 server is evaluated efficiently. The performance measuring process is done on both Network Load Balancing (NLB) and High Available Proxy (HAProxy) in Windows and Linux environments respectively as methods for web server load balancing. Furthermore, stability, efficiency and responsiveness of the web servers are depended as the study evaluation metrics. Additionally, average CPU usage and throughput of the both mechanisms are measured in the proposed system. The results show that the IIS 10.0 cluster-based web servers are more responsiveness, efficiency and stable with and without SYN flood DDoS attack. Also, the performance of IIS 10.0 web server is better than of the Apache 2 in term of the average CPU usage and throughput.</p>

Algorithm Optimization for Cold Start of Collaborative Filtering System

With the development of network technology, the amount of information on the network has grown and expanded rapidly with an exponential law, and its information organization is heterogeneous, diverse, and distributed. With the vigorous development of Internet information services, the scale of its information resources has also exploded. For ordinary users, the problems of “information trek” and “information overload” on the Internet are becoming increasingly serious. In order to solve the problem of information overload, recommendation system has become an indispensable tool for today’s e-commerce platform, which can help users find valuable information quickly. Collaborative filtering-based recommendation algorithms have been widely applied and studied in recommendation systems. Although the collaborative filtering algorithm has been widely used, there are still problems such as data sparsity, scalability, and cold start, which seriously limit the quality of recommendations. Therefore, collaborative filtering algorithms face many challenges. Especially recommendation systems using collaborative filtering technology. This article discusses the cold start system, the cold start user, and the cold start scenario. Effective use of project content information and user personal information is one of the effective methods to solve the cold start problem, that is, a hybrid recommendation technology combining information filtering and collaborative filtering. This paper proposes a hybrid recommendation technology that can better solve the cold start problem.

Rancangan dan Pengujian Perangkat Lunak Menggunakan Web Service pada Sistem Informasi Akademik

The author conducted a study of the need to process and integrate data at High School with systems that already exist so that these systems can communicate unhindered difference platform and programming language used. Therefore, the author makes an Academic Information System software Using Web Services in order to connect the Academic Information System with the Financial Administration Information System. Forms of research by the author is the study of literature with data collection techniques of observation, interviews, and documentation. The method used is a Research and Development (R & D), whereas software design methods using Extreme Programming (XP) by implementing 4 practical way XP development, i.e, planning, design, coding, and testing. The results of this in the form of software design Academic Information Systems, Information Systems of Financial Administration, and Web Service. Academic Information System software using Sublime Text 2 application with PHP programming language, software Financial Administration Information System platform using Visual Studio 2012 with Visual Basic.NET programming language and web services created using ASP.NET Web Form Application with the programming language Visual Basic.NET and publish it by using the Internet Information Services (IIS) version 7.5.

The Effect Of India’s E-Commerce & Trade Due To Covid-19 Pandemic

The enforcement of group distancing, lockdowns and other dealings in answer to the COVID-19 virulent disease has led regulars to raise up online shopping, public media use, internet telephony and teleconferencing, and streaming of videos and films. This has resulted in spikes in business to consumer(B2C) sales and an increase in intensity in business to business (B2B) E-commerce. The expansion in B2C sales is mostly evident in online sales of check up supplies, household requisites and fare products. Query has further more better for internet and mobile information services. The net faculty and spectrum to accommodate the stint to online behaviour has urgently had to be adapted by in corporation operators and governments. Required has fallen however for a variety of military with a outsized online component, such as seeing the sights services.

SlimDna – An in-house expert system for STR profiling

At NFC the internally developed software for DNA analysis, SlimDna is used. It is complementary to the LIMS and keeps track of samples, sample batches, instrument files and generated data. The system communicates with the LIMS, instruments and other software. SlimDna includes four modules (Analysis, Control, Administration and Frequency calculation) and covers the entire analysis process from DNA extraction to reporting approved STR profiles to the LIMS. SlimDna is built with Microsoft Internet Information Services (IIS) as application server and the user interface consists of Windows clients. For data storage MySQL is used. The software has been implemented in different packages, STR typing being the latest. The system has streamlined the STR typing by providing, among other functions, automated evaluation of STR profiles, databases for observed variant alleles as well as tracking and logging of negative and positive controls. STR electropherograms from analysis of crime scene samples (around 30 000 per year) are evaluated by SlimDna according to set rules concerning for example stutter ratio, heterozygote balance and number of alleles per marker in order to define the profile as a single source genotype or a mixture. The SlimDna output is compared to a manual evaluation before the results are reported to the LIMS. This process saves nearly one minute hands-on time per sample compared to the previous Excel-based solution. For reference samples, SlimDna evaluates the majority (55%) of the samples without manual revision. SlimDna’s automated interpretation has proven to be very accurate and will soon replace more of the manual revisions. In the near future, we aim to develop SlimDna further, with for example a mixture module supporting the reporting officers in analysis.