Information Search Efficiency Research Articles

The differential impact of active learning on children's memory.

Successful active learning has often been quantified with respect to either the efficiency of information search or the accuracy of subsequent recall. In this article, we explored the hypothesis that children's memory is influenced by the types of information search strategies they implement, which may emphasize different aspects of the task stimuli. As a consequence, younger children's well-documented search inefficiency may turn out to be advantageous and result in better memory for some aspects of the task. In the current experiment, 5- to 10-year-old children (N = 124) played (active condition) or observed an agent play (passive condition) 20-questions games, and were then tested for their memory of several different aspects of the game both immediately after and a week later. Children showed overall improved recall in the active condition. Search efficiency was positively related to recall of the game's solution, but did not significantly impact performance on the other memory tests. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Formation of Information Culture of Higher Education Students in the Digital age

The purpose of the article is to analyze the features of the "information culture" of society and the individual in the digital era, as well as to determine the ways of its formation among students of higher education, in particular, specialties from the field of knowledge 02 "Culture and art"; to propose the content of the educational discipline "Information culture and academic integrity" from the experience of its teaching at the National Academy of Managerial Staff of Culture and Arts. The research methodology consists in the application of general scientific methods, namely: methods of terminological and comparative analysis, synthesis, generalization, system and activity approach, which makes it possible to achieve the set goal. The scientific novelty of the article. The work emphasizes the importance of teaching the educational discipline "Information culture and academic integrity" from the point of view of the competence approach, in the context of the formation of "information" and "digital" competence. Thus, focusing on the features of the modern stage of development of the information society, its digitalization. Examples of the formulation of information and digital competences prescribed in the requirements for "graduate competences" and "learning outcomes" in the approved Standards of higher education of the first (bachelor) level in specialties – 022 "Design", 023 "Fine art, decorative art" were selected and analyzed , restoration", 024 "Choreography", 025 "Musical art", 026 "Scenic art", 028 "Management of socio-cultural activities", 029 "Information, library and archival work" and in the relevant educational and professional programs in these specialties at the National Academy of Managerial Staff of Culture and Arts. The main content modules of the educational discipline program are defined. Emphasis is placed on the formation of the minimum efficiency of information search, critically evaluating sources of information, determining their authority and reliability, and academically fair use of other people's educational, scientific, and creative achievements. To use modern possibilities of information and communication technologies virtuously and effectively. Conclusions. The article proves the practicality of introducing the educational discipline "Information culture and academic integrity" as a mandatory educational component of the OPP, aimed at forming general and professional competencies in students of higher education majoring in the knowledge 02 "Culture and art." Recommendations for the meaningful content of the educational discipline and the use of game-based online learning methods have been determined. Focused attention on the need to develop the ability to work with information in the era of the information, digital society. Keywords:. information culture, information literacy, information competence, digital competence, academic integrity, Standards of higher education.

Research on the generality of icon sizes based on visual attention

AbstractIcon size is one of the key factors affecting the efficiency of information search. The advent of the era of intelligent interaction has made it difficult for icon design to meet the requirements of noncontact, large information volume, and high precision proposed by natural interaction technology in the future. At the same time, with the continuous improvement of display technology, the display resolution has been increased from 720 P to 8 K. Different sizes of display carriers use different resolutions. In order for icons to have efficient recognition at different display resolutions, it is necessary to obtain the best proportional relationship between icon size and display resolution. This paper summarizes the existing relevant research, calculates the ratio of recommended icon size and display resolution as the research variables, and comprehensively evaluates the recommended optimal ratio range of 1:641–1:334 through eye movement, EEG and behavioral response experiments and entropy‐weight TOPSIS method, providing a reference for icon design in various forms of interactive interfaces in the future.

Research on Keyword Extraction Algorithm in English Text Based on Cluster Analysis.

How to facilitate users to quickly and accurately search for the text information they need is a current research hotspot. Text clustering can improve the efficiency of information search and is an effective text retrieval method. Keyword extraction and cluster center point selection are key issues in text clustering research. Common keyword extraction algorithms can be divided into three categories: semantic-based algorithms, machine learning-based algorithms, and statistical model-based algorithms. There are three common methods for selecting cluster centers: randomly selecting the initial cluster center point, manually specifying the cluster center point, and selecting the cluster center point according to the similarity between the points to be clustered. The randomly selected initial cluster center points may contain “outliers,” and the clustering results are locally optimal. Manually specifying the cluster center points will be very subjective because each person's understanding of the text set is different, and it is not suitable for the case of a large number of text sets. Selecting the cluster center points according to the similarity between the points to be clustered can make the selected cluster center points distributed in each class and be as close as possible to the class center points, but it takes a long time to calculate the cluster centers. Aiming at this problem, this paper proposes a keyword extraction algorithm based on cluster analysis. The results show that the algorithm does not rely on background knowledge bases, dictionaries, etc., and obtains statistical parameters and builds models through training. Experiments show that the keyword extraction algorithm has high accuracy and can quickly extract the subject content of an English translation.

РАЗРАБОТКА АЛГОРИТМОВ ИНТЕЛЛЕКТУАЛЬНОГО СЕРВИСА ПОИСКА И МОНИТОРИНГА ИНФОРМАЦИИ

This paper describes the problem of strategic analysis and the choice of directions for the developmentof an innovative enterprise in the conditions of transition to the 6th technological order andindustry 4.0. In these conditions, search and analytical processing of information cannot be fully performedwithout the use of automated information and analytical systems, including those based on artificialintelligence. During the analysis, the main priority functions that the developed services shouldprovide were identified. The main difficulties in the development of these services are identified, such as:pre-processing of data and automated checking of the relevance of databases. To effectively solve thetasks set, the intelligent monitoring and information retrieval service should use an integrated approach,taking into account the effectiveness of applying methods for individual subtasks, and ensure high efficiencyof implementing all stages of the intelligent monitoring procedure. In this regard, this paper describesnot only the development of a general intelligent search algorithm, but also individual blockalgorithms necessary to ensure the priority functions of the service being developed. The paper presentsthe following algorithms: an information search algorithm necessary to solve the problem of full-textsearch of documents within the database of information resources of the information and analyticalcomplex; an algorithm for the procedure for entering new documents; an algorithm for pre-processingdata that includes stemming and removing punctuation marks for subsequent text analysis; an algorithmfor evaluating the ranking and relevance of information, including vectorization of documents; an algorithmfor clustering information search results based on the Kohonen neural network; the algorithm forchecking the relevance of information is to check whether the local copy of the document corresponds tothe current version on the source's web resource. The Python programming language for the implementationof the presented algorithm is proposed and justified. The system provides automated continuousmonitoring with a high frequency of sending a request without the participation of an operator, whichwill increase the quality and efficiency of information search in conditions of a large volume of unstructuredinformation.

Malicious attacks on the web and crawling of information data by Python technology

AbstractOn the Internet full of big data, crawlers can greatly improve the efficiency of information search. This paper briefly introduced Python and the hacker attack technology and crawler program based on Python. After that, the web hacker attack program was embedded into the crawler program to crawl the deeper hidden information restricted by permission. Then, the conventional crawler program, C language crawler program, and Python‐based crawler program were tested. The results showed that the normal crawler program failed to crawl the complete information data when facing the web page with permission restriction; the C language crawler program has a low efficiency though it could crawl the hidden information; the Python‐based crawler program obtained the complete information data after bypassing the permission by Structured Query Language (SQL) injection of the web hacker attack module. To sum up, applying Python can write crawler programs in a relatively simple way and embed a hacker attack program to crawl the hidden information on the web.

Eye tracking analysis of airport flight information display system (FIDS) to improve the information search efficiency

Air transportation is one mode of transport with a large economic contribution to Indonesia (38,12%). The airport must ensure to provide the best service, especially the efficiency of information given. Flight Information Display System (FIDS) is one substantial information system in the airport and aims to increase communication efficiency about the flight information. Based on the preliminary research, the airport’s FIDS showed different visual design one to another. Therefore, this research aims to analyze it to improve information search efficiency. The research used full factorial design as the experimental design method, eye tracker as the data gathering, and mixed-design ANOVA with post hoc test as the data analysis. We involved 3 factors that have a strong correlation with FIDS searching time efficiency: color combination of background and text, row arrangement, and column arrangement. As the measure, time to first fixation and total fixation used to indicate the information search efficiency. Data analysis generated 2 variables that improved information search efficiency on both data, except the row arrangement (only on Total Fixation data). The intended variable levels are dark color background and light color text, row arrangement based on the alphabetic order of the “Flight” column, and column arrangement “Flight-Time-Destination”.

Construction of information search behavior based on data mining

With the increasing maturity of Web 2.0–related technologies and the expansion of applications, a large number of social network services have emerged at home and abroad. These network platforms have greatly enriched the lives of netizens and become an important platform for studying user information behavior. At the same time, the development of technologies such as global positioning system technology, search engine, and data mining has made users’ data in the mobile social network platform receive extensive attention. This paper constructs a model of information search behavior based on data mining technology in mobile socialized networks and tests it with empirical methods. The results show that the usefulness of information plays a mediating role in the path of information usability impact on information search behavior. Product interaction and human-computer interaction can significantly affect the information search behavior. Trust plays a mediating role in the interaction of virtual community interaction (product interaction, interpersonal interaction, and human-computer interaction) on information search behavior. Using data mining technology to mine user needs, mining relevant data in search and mining information utilization, can improve user information search efficiency and efficiency. What’s more, it can provide basis and support for users and website decision-making.

The association between manifestations of intrapersonal conçict and the style of media consumption among students

Introduction. Media consumption is a factor for the emergence and resolution of intrapersonal conflicts. Both domestic and foreign researchers recognize the effect of media environment on the individual. The present study investigates the association between students’ style of media consumption and intrapersonal conflict.
 Materials and Methods. The empirical study of intrapersonal conflict and features of media consumption involved the first, second, and third-year students. The study employed the following techniques: (a) Life Meaning Orientation Test (D. A. Leont'ev); (b) Relation Between Values and Accessibility in Various Life Spheres (E. B. Fantalova); (c) Social Frustration Diagnostics (L. I. Wasserman, V. V. Boyko’s modification; (d) Quantitative Evaluation of Self-Esteem (P. A. Budassi); (e) Individual Style of Media Consumption and Motivational Structure of Information Activity (Yu. N. Dolgov, etc.). Correlation and factor analysis were used for data processing.
 Results. The study described intrapersonal conflicts peculiar to students, features of their style of media consumption, and also the association between these variables.
 Discussion. Students’ intrapersonal conflicts occur because of the contradiction between real and ideal self and also the significance and accessibility of values. The students’ style of media consumption is critical and purposeful when searching information. The findings revealed significant associations among the following parameters: (a) role conflict and compensatory, relaxational, and reactivating motives of media consumption and also the level of the efficiency of information search; (b) conflict between self-esteem and the level of the reflexive criticism of media consumption; (c) motivation for media consumption, the degree of involvement in the media environment and the conflict of unrealized desires. The results obtained suggest that the style of media consumption is a factor for interpersonal conflicts among students.

Sources of developmental change in the efficiency of information search.

Children are active learners: they learn not only from the information people offer and the evidence they happen to observe, but by actively seeking information. However, children's information search strategies are typically less efficient than those of adults. In two studies, we isolate potential sources of developmental change in how children (7- and 10-year-olds) and adults search for information. To do so, we develop a hierarchical version of the 20-questions game, in which participants either ask questions (Study 1) or test individual objects (Study 2) to discover which category of objects within a nested structure (e.g., animals, birds, or owls) has a novel property. We also develop a computational model of the task, which allows us to evaluate performance in quantitative terms. As expected, we find developmental improvement in the efficiency of information search. In addition, we show that participants' performance exceeds random search, but falls short of optimal performance. We find mixed support for the idea that children's inefficiency stems from difficulty thinking beyond the level of individual objects or hypotheses. Instead, we reveal a previously undocumented source of developmental change: Children are significantly more likely than adults to continue their search for information beyond the point at which a single hypothesis remains, and thus to ask questions and select objects associated with zero information gain. This suggests that one crucial source of developmental change in information search efficiency lies in children's "stopping rules." (PsycINFO Database Record

Children adapt their questions to achieve efficient search

One way to learn about the world is by asking questions. We investigate how younger children (7- to 8-year-olds), older children (9- to 11-year-olds), and young adults (17- to 18-year-olds) ask questions to identify the cause of an event. We find a developmental shift in children’s reliance on hypothesis-scanning questions (which test hypotheses directly) versus constraint-seeking questions (which reduce the space of hypotheses), but also that all age groups ask more constraint-seeking questions when hypothesis-scanning questions are least likely to pay off: When the solution is one among equally likely alternatives (Study 1) or when the problem is difficult (Studies 1 and 2). These findings are the first to demonstrate that even young children dynamically adapt their strategies for inquiry to increase the efficiency of information search.

Development of a Knowledge Management System for the Basic Hand Tools and Machinery Using Ontology Technology

The purpose of this study was to develop a knowledge management system for basic hand tools and machinery using ontology technique for increasing information search efficiency and for practical use. Ontology technique was applied to help presenting the system in the form of semantic web using OWL and RAP languages that supported analyses in knowledge management process. The system was designed to meet users’ need. It was tested and evaluated by experts and users.The study showed that the system could help the users to efficiently use the right tools for the right jobs. According to the satisfaction evaluation, the experts and the users were very satisfied with the developed system. The satisfaction mean was 4.34 and the standard deviation was 0.54. This proved that the set hypothesis was true.

현대 소비자의 소비자정보역량: 전자제품 구매 시 정보탐색 효율성 및 효과성에 미치는 영향

This study aimed to measure consumer information competency, which indicates consumers` general ability to search and utilize information. The model of this study was constructed in order to identify how consumer information competency influences the efficiency and the effectiveness of external information search. The model was verified with related prior knowledge as a moderator variable in order to understand holistic consumer information search activity. The result of the study is as follows. First, the concept of consumer information competency was constructed with four sub-abilities: define, search, extract, and synthesis & use. The ability of define was the highest, as opposed to the ability of extract, which was the lowest. Second, consumer information competency was lower for women as well as for low family income. The sub-abilities of search and synthesis & use were lower for aging consumers. Third, consumer information competency has positive effects on information search efficiency and effectiveness. Moreover, the efficiency influences the effectiveness positively. Fourth, prior knowledge moderates the effect of consumer information competency to the efficiency. Only for consumers with high knowledge the efficiency has the effect of mediating between consumer information competency and the effectiveness.

A Machine Learning Technique for Semantic Search Engine

In this world of information technology revolution we human wants a way of automation in every field, but the intelligent technique behind the way how we visualize an information is not equivalent to how an computer system visualize .In web information content is simply a resource with some specific hyper-link path. In this paper we propose an idea of giving semantic to a web page so a system can understand the semantic behind the web page which automatically increases the efficiency of information search. So we represent a way of converting an ordinary Syntactic page into a Semantic web page with corresponding Ontology which would pave the way of advancement in Semantic Web Learning technology.

The impact of risk and affect on information search efficiency

We develop and test a theoretical framework of the joint influence of risk and affect on information search efficiency. Our framework proposes that information search is less efficient (i.e., less strategic) when risk is high, versus low. It further proposes that the influences of positive and negative affect on search efficiency are asymmetric and depend on the level of risk. Negative affect improves search efficiency when risk is high, but not when it is low. Positive affect degrades search efficiency when risk is low, but not when it is high. We find results consistent with our framework in two experiments. We discuss implications for affect research and for decision making in risky contexts, including financial statement auditing.

The Impacts of Station Symbols in Urban Rail-Transit Maps on the Information Search Efficiency

The Impacts of Station Symbols in Urban Rail-Transit Maps on the Information Search Efficiency

Hierarchical economic information filtering model concerning vendor selection

This paper proposes a new hierarchical economic information filtering model for vendor selection, consisting of three phases in which leading enterprises select their vendors, namely, the phase of collecting and releasing information, the phase of selecting vendors and the phase of dynamic rating of vendors. Rating and search criteria are different for the three levels of search. It analyses the weights for individual criteria and their relative importance in accordance with the hierarchical economic information filtering model, multiple rounds of feedback from the management staff in manufacturing industries and the method of analytical hierarchy process. Hierarchical economic information filtering model defines the information search criteria of vendor selection, which contributes to increasing information search efficiency, and reduces information search time and cost. Also, vendor information can be dynamically filtered, selected, treated and responded to real time. The establishment and application of this model can help to define tasks and foci in relation to selection and rating of vendors in varying phases. It might help leading enterprises to accommodate vendors dynamically in terms of the rating results, and avoid noisy information and data when selecting and rating vendors in different phases. It can be considered as an extension of filtering economic information in varying phases and modules.

Management Insights

Management Insights