Personal Information System Research Articles

Health, Food and User's Profile Ontologies for Personalized Information Retrieval

As we aim to retrieve personalized information to user's queries related to food, health and nutrition domains such as “Is apple good for people with heart diseases?”, “How much honey can be taken by a diabetic patient?”, “What are the health benefits of eating pineapple?” and “What are the fruits that contain the daily need quantity of calcium?” The information retrieval system needs to integrate ontologies from different domains such as food, nutrition, health (diseases, body parts, body functions) and recipe in order to answer such kind of queries. In addition, to support multilingual queries, the system and ontologies require aggregation of information from multi-level ontologies. Also, to achieve high relevancy and coverage we need to use ontologies that have comprehensive and rich vocabularies. Moreover, to make effective use for the annotation, ontologies concept names should be unique and self-contained. The main focus of this paper is to integrate ontologies from food, health and nutrition domains to help the personalized information systems to retrieve food and heath recommendations based on the user's health conditions and food preferences. Such ontologies that satisfy these requirements do not explicitly exist. Therefore, we were challenged to develop these ontologies by creating, integrating and reusing some of the existing ontologies to meet our requirements.

Deep Analysis of Data Mining Method in Personalized Information System of University Library

In order to discuss the application method and execution process of data mining in personalized information system establishment of university library, the thesis introduces existing condition of university library and insufficiency of the information service system. At the same time, data mining technology is introduced to simply describe the data mining process and introduce two top applications of the data mining technology in personalized library information system, namely student interest guidance quality and establishment of relevancy rule. Furthermore, more classical algorithms (FP-growth algorithm and K-mean clustering algorithm) are introduced in the data mining technology in detail. The data mining technology is a new data processing method. Nowadays, as for high flux reactor data analysis, data mining technology becomes more and more important in the construction process of personalized library information system.

디지털 포렌식 기법을 활용한 효율적인 개인정보 감사 대상 선정 방안 연구

최근 대량의 개인정보 유출 사고가 잇따라 발생하고 있으며, 외부 해킹과 더불어 내부직원 및 외주업체 직원에 의한 개인정보 유출사고가 증가하고 있다. 이에 따라 기업에서는 내부 보안을 강화하고, 개인정보 처리 업무를 위탁한 수탁사를 대상으로 개인정보의 분실, 도난, 유출 위험을 최소화하기 위해 정기적인 조사 및 점검을 통한 개인정보 감사를 진행하고 있다. 그러나 수탁사의 다양한 업무환경으로 인해 한정된 시간 동안 모든 개인정보 취급 PC를 정밀 조사하는데 어려움이 있다. 따라서 개인정보의 유출 위험성이 높은 고위험군을 식별하여 점검 대상을 효과적으로 선정하는 것이 필요하다. 본 논문에서는 디지털 포렌식 기법을 활용하여 사용자 행위 기반의 고위험군 선정 방안을 제안한다. 또한, 이를 활용하기 위한 도구를 설계 및 구현하였고, 실험 결과를 통해 효과를 입증한다. Recently the leak of personal information from in-house and contract-managed companies has been continually increasing, which leads a regular observation on outsourcing companies that perform the personal information management system to prevent dangers from the leakage, stolen and loss of personal information. However, analyzing many numbers of computers in limited time has found few difficulties in some circumstances-such as outsourcing companies that own computers that have personal information system or task continuities that being related to company's profits. For the reason, it is necessary to select an object of examination through identifying a high-risk of personal data leak. In this paper, this study will formulate a proposal for the selection of high-risk subjects, which is based on the user interface, by digital forensic. The study designs the integrated analysis tool and demonstrates the effects of the tool through the test results.

Seamless personal health information system in cloud computing.

Noncontact ECG measurement has gained popularity these days due to its noninvasive and conveniences to be applied on daily life. This approach does not require any direct contact between patient's skin and sensor for physiological signal measurement. The noncontact ECG measurement is integrated with mobile healthcare system for health status monitoring. Mobile phone acts as the personal health information system displaying health status and body mass index (BMI) tracking. Besides that, it plays an important role being the medical guidance providing medical knowledge database including symptom checker and health fitness guidance. At the same time, the system also features some unique medical functions that cater to the living demand of the patients or users, including regular medication reminders, alert alarm, medical guidance, appointment scheduling. Lastly, we demonstrate mobile healthcare system with web application for extended uses, thus health data are clouded into web server system and web database storage. This allows remote health status monitoring easily and so forth it promotes a cost effective personal healthcare system.

Bringing Relevance, Applicability and Engagement into 1st Year B.Com Curricula

Most B.Com degrees, recognising the fundamental role of information and communication technology (ICT) in business and society, require students to take an introductory course in Information Systems (IS). Most IS courses offered to first year B.Com students are simply introductory courses originally designed for intended IS majors. These provide a broad, but arguably superficial introduction to the various elements of ICT, failing to situate technology within the modern business world or everyday life of the average B.Com student. Students inevitably treat the course simply as a requirement for graduation, and take little of value with them either into their university or working life. Taking accessibility of content, relevance and real world application as a departure point, an introductory IS course was radically redesigned, moving away from chapter-based textbook coverage. Instead, an integrated theme-based approach guiding students from engaged reflection on personal information systems towards an understanding of the impact of ICT in business and society has been developed. With typical enrolment ranging between 550 and 750 students, a learning management system with forum participation and online quizzes, small group tutorials, guided self-study tasks and informal social networking was central to the redesign. This paper examines the motivation and rationale behind the course redesign. Preliminary data analysis of course evaluations, lecturer interviews and focus groups from the first action research cycle is presented. Early results and anecdotal evidence suggest higher levels of student participation, deeper engagement with concepts and content, and increased interest in IS as a major.

The Personal Information of Label Algorithm in Space Management System Research

Tag technology how to combine with personal information management model is a personal space management information system of data management and sharing of the premise, based on information search in the traditional personal information management efficiency is low, can't share problem, put forward based on the tag tree organization of local data, based on a tag cloud organization model and the algorithm of global data, to construct a distributed and integrated data environment. System performance test results show that the proposed algorithm can effectively improve the precision of personal space management information system, reduce the response time.

Predicting personal information system adoption using an integrated diffusion model

The purpose of this study is to develop a research model that integrates the relationship between innovation characteristics (innovation diffusion theory) and technology characteristics (task-technology fit model). With the research model, the current study investigates the adoption of the “personal information system,” a concept that we develop in the context of mobile technologies. In this paper, we performed the first quantitative test of the model by integrating the innovation diffusion and task-technology fit models. Further, we proposed a theoretical definition of “personal information systems” by highlighting the differences in the types of tasks across individual users’ needs. To test our research model, 202 college students were surveyed. Partial least squares (PLS) structural equation modeling was employed to analyze our data, and these analyses provided empirical support for the proposed hypotheses. Quality, compatibility, cost, and relative advantage were found to be important indicators of the intention to adopt due to their impact on the intended communication, information, transaction, and entertainment tasks, while compatibility, relative advantage, and complexity had a direct impact on the intention to adopt.

Personalized News Portals

In this study, we investigated the impact of personalized news web portals on selective exposure. Results from analyses of secondary survey data from national random samples of U.S. adults show a positive relationship between personalized news and increased exposure to offline news. Users of personalized news report viewing more sources and categories of news online compared with nonusers. Partisan users of personalized news do not report increased partisan news exposure. No difference in preferences for perspective sharing or challenging news sources is found between personalized news users and nonusers. The implications for future research on personalized information systems and selective exposure are discussed.

Data protection in the personal data processing

Processing of personal data, which is obligatory for any institution or organization, requires implementation of personal data processing information systems and definitely their security. The majority of existing information security methods and techniques is focused on the security of corporate information systems resources. Such techniques do not always take into account the special requirements for data processing. This fully applies to the processing of personal data protection, the security of which is provided by the current legislation. Approaches to the protection of personal data processed in automated information systems were discussed. The classification of threats to personal data that may occur when processing them in automated systems was brought. We considered the aims and methods of minimizing such threats including comprehensive measures to protect personal data. The ways and means of personal protection methods of personal data were considered. The priorities of forming the overall personal data protection system were defined.

Interaction Design for Complex Cognitive Activities with Visual Representations: A Pattern-Based Approach

This paper is concerned with interaction design for visualization-based computational tools that support the performance of complex cognitive activities, such as analytical reasoning, sense making, decision making, problem solving, learning, planning, and knowledge discovery. In this paper, a number of foundational concepts related to interaction and complex cognitive activities are syncretized into a coherent theoretical framework. This framework is general, in the sense that it is applicable to all technologies, platforms, tools, users, activities, and visual representations. Included in the framework is a catalog of 32 fundamental epistemic action patterns, with each action pattern being characterized and examined in terms of its utility in supporting different complex cognitive activities. This catalog of action patterns is comprehensive, covering a broad range of interactions that are performed by a diverse group of users for all kinds of tasks and activities. The presented framework is also generative, in that it can stimulate creativity and innovation in research and design for a number of domains and disciplines, including data and information visualization, visual analytics, digital libraries, health informatics, learning sciences and technologies, personal information management, decision support, information systems, and knowledge management.

Development of a personal bibliographic information system

Purpose – The aim of this paper is to propose the bibliographic information system “Personal eLibrary bgMath”. This is a system for the organisation, storage and usage of digitalised literature. It supports the user in organising his/her publications and his/her library of electronic issues. The system is very convenient, especially for scientific literature.Design/methodology/approach – The methodology to design a database storing information about publications and other literature is presented. The entity‐relationship model of the database is described. The relational tables, obtained after the transformation of the created ER model into a relational model, are given. The paper contains the description of the forms implementing two basic tasks of the presented program, i.e. input and search for publications. The database is implemented by means of the database management system Microsoft Access 2007.Findings – The system Personal eLibrary bgMath allows easy manipulation of materials (papers, dissertatio...

ONTOLOGICAL APPROACH FOR IMPROVING SEMANTIC WEB SEARCH RESULTS

we propose personalized information system to provide more user-oriented information considering context information such as a personal profile based, location based and click based. Our system can provide associated search results from relations between the objects using context ontologies modeling created by the categorized layers data. Based on the similarities between item descriptions and user profiles, and the semantic relations between concepts, content based and collaborative recommendation models are supported by the system. User defined rules based on the ontology description of the service and interoperates within any service domain that has an ontology description.

Measuring the privacy of user profiles in personalized information systems

Personalized information systems are information-filtering systems that endeavor to tailor information-exchange functionality to the specific interests of their users. The ability of these systems to profile users is, on the one hand, what enables such intelligent functionality, but on the other, the source of innumerable privacy risks. In this paper, we justify and interpret KL divergence as a criterion for quantifying the privacy of user profiles. Our criterion, which emerged from previous work in the domain of information retrieval, is here thoroughly examined by adopting the beautiful perspective of the method of types and large deviation theory, and under the assumption of two distinct adversary models. In particular, we first elaborate on the intimate connection between Jaynes’ celebrated method of entropy maximization and the use of entropies and divergences as measures of privacy; and secondly, we interpret our privacy metric as false positives and negatives in a binary hypothesis testing.

Improving Adaptation Rules Quality Using Genetic Programming

Personalized Information System (PIS) aims to provide tailored services to users in various contexts. The aim of such system is to help users find relevant content easier and faster. To achieve such behaviour, the system needs a user model providing information about users, e.g., about their interests, skills, background and custom information while ensuring their adaptation to the needs and preferences of each user. This system is able to learn about the preferences of individual users and to tailor the content, interface, and behaviour to the user preferences. In fact, the diversity of contexts and the proliferation of profiles make personalization a very sophisticated process. Personalization is a major challenge for the information system. In fact, its quality and its adaptation to the user's preferences represent a key of success of these systems. In this context, this paper presents a personalized method based on the principle of genetic programming by extracting the best adaptation rules.

Do Operating Systems Affect Perceptions of Smartphone Advantages and Drawbacks?

Introduction Smartphones are becoming ubiquitous (Smith, 2011), and mobile internet services are extensively used for various sorts of applications (Gerpott, Thomas, & Weichert, 2012), including ecollaboration (Jones, 2012), e-learning (Cheong, Bruno, & Cheong, 2012; Wong, Boticki, Sun, & Looi, 2011), games (Ho & Tu, 2012), and much more. Although technology acceptance and diffusion of innovation are one of the most studied areas in information systems research (Jeyaraj, Rottman, & Lacity, 2006; Rogers, 2003; Venkatesh, Morris, Davis, & Davis, 2003), very little research has been conducted about smartphone applications' adoption (Verkasalo, Lopez-Nicolas, Molina-Castillo, & Bouwman, 2010). One of the major decisions that prospective consumers of a smartphone have to make is choosing its operating system. The decision, which operating system to choose, is based on their own perceptions, as well as perceptions and recommendations of others, while their opportunities to extensively try the devices beforehand are limited. It is important to investigate the perceptions of smartphone holders, who have been using the devices for a while. In order to gain a deeper understanding of the effects of operating systems on users' perceptions of advantages and disadvantages of smartphones, existing users of smartphone devices were selected for this empirical study. Currently, the most prevailing operating systems are Apple's iOS and Google's Android. Therefore, this study compared these two operating systems. There are more factors involved in the selection decision of a smartphone, such as the available content and applications (Laugesen & Yuan, 2010), or ideological considerations, like using free and open source software (FOSS) and open standards (Subramanian & White, 2012). However, these issues are beyond the scope of this paper, which focuses on the perceived advantages and drawbacks of smartphone operating systems by people who have already bought them, and have been using them for a while. This study contributes to the informing science transdiscipline (Cohen, 1999, 2009; Gill & Bhattacherjee, 2009; Gill & Cohen, 2009) by providing insights regarding the effects of operating systems on users' perceptions of their personal mobile information system, i.e., advantages and drawbacks of their smartphone. This empirical study is important, because only a few studies examined the adoption of smartphones, and most of them (e.g., Cheong et al., 2012) focused on smartphone applications, unlike this study that considers the device. Theoretical Context and Hypothesis Development The global research question of this study is whether operating systems affect smartphone possessors' perceptions of advantages and drawbacks of their device usage, when compared with consuming the same services via a computer. This study investigates three specific research questions (RQ), which originate from the global one: RQ1: Which sorts of perceptions of smartphone advantages and drawbacks are affected by its operating system? This question is elaborated in the subsection versus operating-system-related characteristics. RQ2: Are there of smartphone possessors' perceptions of advantages and drawbacks of their device usage? This question is developed in the subsection gender differences RQ3: Does the of possession of the smartphone affect its possessors' perceptions of advantages and drawbacks of their device usage? This question is explained in the subsection period of possession. General versus Operating-System-Related Characteristics When comparing the consumption of mobile internet services via a smartphone with consumption of the same services via a computer, there are two main sorts of characteristics that should be considered separately: general characteristics of smartphone use, and characteristics that are affected or determined by the operating system. …

Interpreting the Computer Fraud and Abuse Act

Computers play an integral role in today’s society. While computers provide many benefits, they are increasingly used as tools for wrongdoing, causing estimated losses of billions of dollars each year. Computer hackers can, among other things, fraudulently alter accounts, steal business or personal information, and corrupt or disable computer systems. Congress enacted and has repeatedly amended the Computer Fraud and Abuse Act (“CFAA”) to combat the increasing proliferation of computer crimes. This article argues that the Courts of Appeals have not adequately interpreted the foundational terms of the Act and recommends an interpretation of the Act that builds upon the narrower definitions to comprehensively define the scope of the Act’s coverage.

Empowering web portal users with personalized text mining services

Empowering web portal users with personalized text mining services

Evaluation by simulation to optimise information systems’ personalisation quality in logistics

Personalised information systems (PISs), related to different fields (travelling and mobility, production, logistics and so on), represent an object of many research and development perspectives. Using PISs, it becomes possible to supply the user only with the pertinent information that suits their preferences. Indeed, thanks to personalisation, the user may feel that a particular PIS is developed for them. This system adaptation becomes a necessity for the user's satisfaction. In this context, many studies were orientated toward the user modelling, the design methods of PIS and the personalisation algorithms, etc. but, the evaluation of these systems is neglected. Difficulties concerning context-centred evaluation appear. This paper is focused on the evaluation of the personalised information systems in order to optimise the personalisation quality according to several criteria. For such systems, it is important to envisage new adapted evaluation methods. An evaluation method using a PIS simulation model, called MetSim (Method evaluation per Simulation), is proposed. MetSim is also based on the case-based reasoning system to identify problems. This evaluation approach has been validated by applying it to assess PISs in the logistics field.

Acceptance of ERP Solutions in Maturity Use Phase

Enterprise resource planning (ERP) solutions have been implemented in a lot of organizations in the past few years. Notwithstanding the fact that ERP solutions benefit organizations only to the extent that users accept and use them, most studies regarding ERP solutions today refer to selection and implementation process. The most widely used model in the area of investigating user acceptance is technology acceptance model (TAM) proposed by Davis (1989). In this paper, the TAM was extended to measure groups of extended factors (personal characteristics and information literacy, system and technological characteristics and organizational-process characteristics) that influence ERP acceptance. Because ERP solutions are implemented in different organization types and by different methodology, the authors also analyze external factors importance regarding user acceptance of two global solutions – SAP and Microsoft Dynamics.

SVM을 활용한 악성 웹 페이지 분류

웹 페이지에서 다양한 서비스를 제공하면서 악성코드가 웹 페이지를 통해 배포되는 것도 늘어났다. 악성코드는 개인정보 유출, 시스템의 성능저하, 시스템의 좀비 피씨화 등의 피해를 입힌다. 이런 피해를 막으려면 악성코드가 있는 웹 페이지의 접근을 막아야 한다. 그런데 웹 페이지에 있는 악성코드는 난독화나 변형기법으로 위장하고 있어 기존 안티바이러스 소프트웨어가 사용하는 시그니처 방식의 접근법으로 찾아내기 어렵다. 이를 해결하기 위하여, 웹 페이지를 분석하여 악성 웹 페이지와 양성 웹 페이지를 구별하기 위한 특징을 추출하고, 기계 학습법으로 널리 사용되는 SVM을 통하여 악성 웹 페이지를 분류하는 방법을 제안한다. 제안하는 방법이 우수함을 실험을 통하여 보인다. 제안한 방법으로 악성 웹 페이지를 정확히 분류하면 웹 페이지를 통한악성코드의 배포를 막는데 이바지할 것이다. As web pages provide various services, the distribution of malware via the web pages is being also increased. Malware can make personal information leak, system mal-function and system be zombie. To protect this damages, we should block the malicious web pages. Because the malicious codes embedded in web pages are obfuscated or transformed, it is difficult to detect them using signature-based approaches which are used by current anti-virus software. To overcome this problem, we extracted features to classify malicious web pages and benign ones by analyzing web pages. And we propose a classification method using SVM which is widely used in machine learning. Experimental results show that the proposed method is better than other methods. The proposed method could classify malicious web pages correctly and be helpful to block the distribution of malicious codes.