Set Of Information Sources Research Articles

Social System Inference From Noisy Observations

This article studies social system inference from a single noisy trajectory of public evolving opinions, wherein observation noise leads to the statistical dependence of samples on time and coordinates. We first propose a cyber-social system that comprises individuals in a social network and a set of information sources in a cyber layer, whose opinion dynamics explicitly takes the asymmetric cognitive bias including confirmation bias and negativity bias and the process noise into account. Based on the proposed cyber-social model, we then study the sample complexity of least-square auto-regressive model estimation, which governs the length of a single observed trajectory that is sufficient for the identified model to achieve the prescribed levels of accuracy and confidence (PAC). Building on the identified social model, we then investigate social inference, with a particular focus on the weighted network topology and the model parameters of asymmetric cognitive bias. Finally, the theoretical results and the effectiveness of the proposed inference framework are validated by the U.S. Senate Member Ideology data.

Information Support of Statistic Research of Budget Investments’ Impact on Socio-Ecological and Economic Development of the Russian Federation regions

Purpose of the study is to estimate the information support on budget investments and analyze the sources of their formation from the standpoint of completeness and reliability of information for their use as an information base for a statistical study of the impact of budget investments on the social, environmental and economic development of the regions of the Russian Federation. The main directions for assessing the information security of the research are: studying the requirements and basic standards for information; specifics and structures of formed information flows; analysis of information resources, including their parameters and characteristics describing their properties and purpose; determination of units of main information elements, their grouping by formation sources, by main users, by formation system.Materials and methods. The research used the theoretical methods: analysis, synthesis, grouping of sources of information on budget investments.Results. The conducted research allowed making a conclusion on a high degree of information security of a rather extensive, multidimensional set of information sources and resources on budget investments. This paper is the basis for the formation of a categorical instrument of statistical research on budget investments. The information array of data on budget investments is aimed at analytical procedures that can be carried out by types, sorts, forms of implementation, budget levels and budget investments realization stages including regional sectioning.Conclusion. The conducted research has a high degree of practical value due to its aim at direction on elaboration of tools for state management of budget investments. Rapid development of forms and resource chances of the formed information flows on budget investments determined by realization of requirements to the publication of data by state bodies and local self-government bodies which have become more often placed on the Internet as data arrays in the format ensuring their automatic processing to be reused in terms of free use.

Information sources used by charterers to select shipowners

This study aims to identify the information search behaviour of charterers in selecting shipowners within a business-to-business framework. It focuses on charterers' information sources and how different factors (individual, organisational, and purchase-related) affect the information search since this construct is a major component of comprehensive theories of organisational buying behaviour. Understanding the buying behaviour of charterers also helps marketers to increase customer satisfaction. The analysis is based on questionnaire responses from 141 firms that have recently chartered vessels. From a principal components analysis, the study identified eight sets of information sources, of which impersonal, e-mails and reference-based information were the most important. The results show that the business-to-business information sources used by ship charterers vary significantly according to organisation size, centralisation, type of purchase, purchase complexity and experience. Further analyses revealed a significant relationship between these factors and business-to-business information sources, specifically between the importance of the purchase, perceived risk, formalisation, standardisation, personal stake, specialisation, and use of information resources. Finally, the study revealed a significant relationship between business-to-business information sources and customer satisfaction.

Критерии многокритериального выбора конфигурации телекоммуникационной сети системы непрерывного мониторинга с подвижными средствами наблюдения

The article proposes criteria for multi-criteria selection of the configuration of the telecommunications network of a structural-dynamic continuous monitoring system. The mobility of the components of the monitoring system leads to periodic (or permanent) changes in the topology of the telecommunications network, through which data is transmitted in the monitoring system. Destabilizing effects of both natural and artificial origin also lead to forced changes in the topology of the telecommunications network. To select the configuration of the telecommunications network (a set of information sources, information consumers, data transmission network, and optimally formed information channels) both during the initial construction of the system and during the operation of the system of continuous monitoring for the detection of objects (on a given territory at a given time with a given probability), it is proposed to apply three criteria. The first criterion is the time of configuration formation, the second is the radius of resistance to destabilizing influences, and the third is an indicator of the continuity of information interaction between the elements of the system.

Real World Evidence: welcome to reality!

Real World Data (RWD) constitute a set of information sources on which the very current line of research of Real World Evidence (RWE) is based. RWE studies are based on data from observational studies, administrative databases, population or disease registers, insurance registers, electronic medical records, population health surveys and, more recently, social media and data from mobile devices and apps. While Randomized Clinical Trials (RCTs) answer the question “Can it work?” “Is it safe?” RWDs are more interested in answering the question “Does it work?”. We therefore move from a question of “efficacy / safety” to one of “effectiveness”. RWE studies allow to evaluate the safety of a treatment in a longer period than that of the RCTs, verify its quality and cost effectiveness, allow us to trace the natural history of a disease conditioned or not by a treatment, give us relevant information on compliance and on adherence to treatments and allow us to identify service models and patient preferences. Given the exciting perspective that the “real” vision of things outlines, AMD has decided to keep up with the times by forming a Group of work on “Real World Evidence”. The activities that the RWE Working Group is already promoting and carrying out are: 1) support for the publication of clinical cases; 2) support for the drafting of research protocols; 3) analysis of the Annals database. Addressing Real World Evidence in the widest possible way by collaborating with interested AMD Members, aligning with the need to give a concrete face to things, represents the vision of this Group. “Welcome to reality”! KEY WORD Real World Data, Real World Evidence, effectiveness.

Information Sources Used By Charterers to Select Shipowners

This study aims to identify the information search behaviour of charterers in selecting shipowners within a business-to-business framework. It focuses on charterers' information sources and how different factors (individual, organisational, and purchase-related) affect the information search since this construct is a major component of comprehensive theories of organisational buying behaviour. Understanding the buying behaviour of charterers also helps marketers to increase customer satisfaction. The analysis is based on questionnaire responses from 141 firms that have recently chartered vessels. From a principal components analysis, the study identified eight sets of information sources, of which impersonal, e-mails and reference-based information were the most important. The results show that the business-to-business information sources used by ship charterers vary significantly according to organisation size, centralisation, type of purchase, purchase complexity and experience. Further analyses revealed a significant relationship between these factors and business-to-business information sources, specifically between the importance of the purchase, perceived risk, formalisation, standardisation, personal stake, specialisation, and use of information resources. Finally, the study revealed a significant relationship between business-to-business information sources and customer satisfaction.

On Inference of Network Topology and Confirmation Bias in Cyber-Social Networks

This article studies topology inference, from agent states, of a directed cyber-social network with opinion spreading dynamics model that explicitly takes confirmation bias into account. The cyber-social network comprises a set of partially connected directed network of agents at the social level, and a set of information sources at the cyber layer. The necessary and sufficient conditions for the existence of exact inference solution are characterized. A method for exact inference, when it is possible, of entire network topology as well as confirmation bias model parameters is proposed for the case where the bias mentioned earlier follows a piece-wise linear model. The particular case of no confirmation bias is analyzed in detail. For the setting where the model of confirmation bias is unknown, an algorithm that approximates the network topology, building on the exact inference method, is presented. This algorithm can exactly infer the weighted communication from the neighbors to the non-followers of information sources. Numerical simulations demonstrate the effectiveness of the proposed methods for different scenarios.

Quickest Search and Learning Over Correlated Sequences: Theory and Application

Consider a set of information sources, each generating a sequence of independent and identically distributed random variables over time. Each information source generates its data according to one of the two possible distributions F <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">0</sub> or F <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sub> . Due to potential physical couplings that govern the information sources, the underlying distribution of each sequence depends on those of the rest. Hence, the underlying distributions form a dependence kernel. Due to uncertainties in the physical models, however, the dependence kernel is not fully known. The objective is to design a sequential decision-making procedure that identifies a sequence generated according to F <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sub> with the fewest number of measurements. Earlier analyses of such search problems have demonstrated that the optimal design of the sequential rules strongly hinges on knowing the dependence kernel precisely. Motivated by the premise that the dependence kernel is not known, this paper designs a sequential inference mechanism that forms two intertwined inferential decisions for identifying a sequence of interest and learning the parameters of the dependence kernel. This paper devises three strategies that place different levels of emphasis on each of these inference goals. Optimal decision rules are characterized, and their performance is evaluated analytically. Also, the application of the proposed framework to wideband spectrum sensing is discussed. Finally, numerical evaluations are provided to compare the performance of the framework to those of the relevant existing literature.

The paradox of cultural and media convergence. Segmenting the European tourist market by information sources and motivations

AbstractThe globalization of markets has led destination marketing organizations to question whether their marketing strategies should appeal to cultural convergence or divergence, both in the media to be used (information sources) and in the content to be communicated (related to travel motivations). The purpose of this study is to investigate the “cultural convergence” and “media convergence” using data from a computer‐assisted web interviewing survey on 17 European countries. The methodology uses multiple correspondence analysis, factor analysis, and cluster analysis to segment the market. The results identify both phenomenon (convergence and divergence) by culture (blocks of countries), media (set of information sources), and content (motivations). The 17 European countries were segmented by information sources into Ensurers, Ensurers with digital exploration, and Low‐social media users and by motivations into Adventures and Pleasure, Socializing, and Rest with Knowledge. An overall understanding of these segments and the paradoxical cultural and media convergence will serve as a tool for destination marketing organizations in the development of their segmenting and communication strategies, as they will be able to know what social media to use to best reach each culture and what content to communicate based on the European consumers' individual motivations.

A neural feature extraction model for classification of firms and prediction of outsourcing success: advantage of using relational sources of information for new suppliers

Clustering is a family of classification techniques, often preceding further analysis or application in a number of fields like data analysis, strategy selection, supplier selection, etc. Data based neural techniques are gaining popularity in clustering applications due to flexibility and adaptability. Kohonen’s Self Organizing Map (SOM) is often used when the objects to be clustered have many attributes. In both supervised and un-supervised modes, Kohonen’s map exhibit good capability to extract a classification which assigns highest weight to the most important attribute. In this paper, we have applied SOM for classification of firms based on their sources of information for new suppliers/customers. Additional data regarding the outsourcing success of the firms’ is added to see if there is an association between a particular set of information sources and the probability of firms’ success to outsource to partner firms. Using data from World Bank BEEPS survey of German industries, we could produce three distinct clusters of industries. When successful outsourcing data were included, it still showed three clusters. The hits were obtained using specific support vector for identification of clusters. We found evidence of associations between relational sources and firms’ ability to outsource successfully.

Stage-driven information seeking process: Value and uncertainty of work tasks from initiation to resolution

The stage-driven information seeking process to reduce uncertainty and increase value is systematically validated with real users (n=60) with real work tasks from social sciences and applied sciences domains in a UK and Danish university. A broad set of information sources are applied and core relevance criteria are measured. The research seeks to test the hypothesis that the information seeking process is seen as a dynamic and iterative development to reduce uncertainty through four stages until the problem is solved: (1) problem recognition: kind of problem, (2) problem definition: nature of the problem, (3) problem resolution: finding an answer to the problem, (4) solution statement: answer to the problem or how to deal with it. The hypothesis can be rejected in this case since there is no significant decrease in uncertainty level from stage 1 to 4.

An ecological approach to the design of information systems

An ecological approach to the design of information systems

A knowledge-based approach for selecting information sources

AbstractThrough the Internet and the World-Wide Web, a vast number of information sources has become available, which offer information on various subjects by different providers, often in heterogeneous formats. This calls for tools and methods for building an advanced information-processing infrastructure. One issue in this area is the selection of suitable information sources in query answering. In this paper, we present a knowledge-based approach to this problem, in the setting where one among a set of information sources (prototypically, data repositories) should be selected for evaluating a user query. We use extended logic programs (ELPs) to represent rich descriptions of the information sources, an underlying domain theory, and user queries in a formal query language (here, XML-QL, but other languages can be handled as well). Moreover, we use ELPs for declarative query analysis and generation of a query description. Central to our approach are declarativesource-selection programs, for which we define syntax and semantics. Due to the structured nature of the considered data items, the semantics of such programs must carefully respect implicit context information in source-selection rules, and furthermore combine it with possible user preferences. A prototype implementation of our approach has been realized exploiting the DLV KR system and its PLP front-end for prioritized ELPs. We describe a representative example involving specific movie databases, and report about experimental results.

Information Quality Assurance by Lazy Exploration of Information Source Combinations Space in Open Multi-Agent Systems

Information quality assurance under the existence of uncertainty can be investigated in the context of soft security, where an agent maintains trustworthiness evaluations of its information sources to assist in the evaluation of incoming information quality from those sources. Since dependency inherently exists in a system where agents do not have self- sufficient sensing or data collection capabilities, finding an appropriate set of information sources is important for assuring the quality of information and for increasing the agent's goal achievement. This research proposes an approach for selecting information sources as partners. In order to increase the efficiency and the accuracy, we use trustworthiness, information cost and goal coverage as the metrics for information valuation while adopting a lazy exploration of information sources combination space. Experimental results show that the proposed approach increases the efficiency and results in quality information acquisition.

Zero-error network coding for acyclic networks

Consider transmitting a set of information sources through a communication network that consists of a number of nodes. Between certain pair of nodes, there exist communication channels on which information can be transmitted. At a node, one or more information sources may be generated, and each of them is multicast to a set of destination nodes on the network. In this paper, we study the problem of under what conditions a set of mutually independent information sources can be faithfully transmitted through a communication network, for which the connectivity among the nodes and the multicast requirements of the source information are arbitrary except that the connectivity does not form directed cycles. We obtain inner and outer bounds on the zero-error admissible coding rate region in term of the regions /spl Gamma//sub N//sup */ and /spl Gamma/~/sub N//sup */, which are fundamental regions in the entropy space defined by Yeung. The results in this paper can be regarded as zero-error network coding theorems for acyclic communication networks.

Expert systems should be more accurate than human experts: evaluation procedures from human judgement and decision making

Two procedures for the evaluation of the performances of expert systems are illustrated: one procedure evaluates predictive accuracy; the other procedure is complementary in that it uncovers the factors that contribute to predictive accuracy. Using these procedures, it is argued that expert systems should be more accurate than human experts in two senses. One sense is that expert systems must be more accurate to be cost-effective. Previous research is reviewed and original results are presented which show that simple statistical models typically perform better than human experts for the task of combining evidence from a given set of information sources. The results also suggest the second sense in which expert systems should be more accurate than human experts. They reveal that expert systems should share factors that contribute to human accuracy, but not factors that detract from human accuracy. Thus the thesis is that one should both require and expect systems to be more accurate than humans. >

A foundation of information geometry

AbstractThis paper proposes a new geometrical basic theory for the field of information science. the traditional theory for the information system is occupied fully by detailed discussions of the properties of a system, and the importance has not been recognized for the mutual relationship within a set of information systems. There are many cases in engineering where a set of information systems must be considered by a single model (for example, in the cases of statistical and system models). to discuss the properties of a model, the mutual relations among the elements must be described. In such a case, the geometrical structure among the information systems, which are elements of the model (e.g., distance, linearity and curvature), is important. This paper recognizes first the family of probability distributions as a manifold. Then it is shown that the structures such as Riemannian metric, α‐pseudo‐distance including a real parameter α, and α‐affine connection, can be introduced naturally. the differential geometrical structure of the space is described. Using the proposed method, the differential geometrical structure inherent in the set of information sources or set of systems can be recognized. the structure is related closely to the system identification problem (parameter estimation), approximation and robustness problems.