The workload capacity of semantic search in convergent thinking.

2021 ◽  
Author(s):  
Linlin Shang ◽  
Daniel R. Little ◽  
Margaret E. Webb ◽  
Ami Eidels ◽  
Cheng-Ta Yang
Keyword(s):  
Semantic Search ◽  
Convergent Thinking ◽  
Workload Capacity

Variations Across the Menstrual Cycle in EEG Activity During Thinking and Mental Relaxation

1999 ◽  
Vol 13 (3) ◽  
pp. 163-172 ◽  
Author(s):  
R. Krug ◽  
M. Mölle ◽  
H.L. Fehm ◽  
J. Born
Keyword(s):  
Menstrual Cycle ◽  
Divergent Thinking ◽  
Spectral Power ◽  
Plasma Concentrations ◽  
Task Demands ◽  
Menstrual Phase ◽  
Convergent Thinking ◽  
Eeg Activity ◽  
Dimensional Complexity ◽  
Mental Relaxation

Abstract Previous studies have indicated: (1) peak performance on tests of divergent creative thinking during the ovulatory phase of the menstrual cycle; (2) compared to convergent analytical thinking, divergent thinking was found to be associated with a distinctly increased dimensional complexity of ongoing EEG activity. Based on these findings, we hypothesized that cortical information processing during the ovulatory phase is characterized by an increased EEG dimensionality. Each of 16 women was tested on 3 occasions: during the ovulatory phase, the luteal phase, and menses. Presence of the phases was confirmed by determination of plasma concentrations of estradiol, progesterone, and luteinizing hormone. The EEG was recorded while the women performed: (1) tasks of divergent thinking; (2) tasks of convergent thinking; and (3) during mental relaxation. In addition to EEG dimensional complexity, conventional spectral power analysis was performed. Behavioral data confirmed enhanced creative performance during the ovulatory phase while convergent thinking did not vary across cycle phases. EEG complexity was higher during divergent than convergent thought, but this difference remained unaffected by the menstrual phase. Influences of the menstrual phase on EEG activity were most obvious during mental relaxation. In this condition, women during the ovulatory phase displayed highest EEG dimensionality as compared with the other cycle phases, with this effect being most prominent over the central and parietal cortex. Concurrently, power within the alpha frequency band as well as theta power at frontal and parietal leads were lower during the luteal than ovulatory phase. EEG results indicate that task demands of thinking overrode effects of menstrual cycle. However, with a less demanding situation, an ovulatory increase in EEG dimensionality became prominent suggesting a loosening of associative habits during this phase.

Framework for Semantic Search Enabled Software Component Repository (SSESCR)

2018 ◽  
Author(s):  
Vishnu Sharma ◽  
Vijay Singh Rathore ◽  
Chandikaditya Kumawat
Keyword(s):  
Software Quality ◽  
Software Reuse ◽  
Development Time ◽  
Software Component ◽  
Semantic Search ◽  
Easy Access ◽  
Software Components ◽  
Efficient Search ◽  
Systematic Reuse ◽  
New System

Software reuse can improve software quality with the reducing cost and development time. Systematic reuse plan enhances cohesion and reduces coupling for better testability and maintainability. Software reuse approach can be adopted at the highest extent if relevant software components can be easily searched, adapted and integrated into new system. Large software industries hold their own well managed component libraries containing well tested software component with the project category based classification .Access to these repositories are very limited. Software reuse is facing so many problems and still not so popular. This is due to issues of general access, efficient search and adoption of software component. This paper propose a framework which resolves all of the above issues with providing easy access to components, efficient incremental semantics based search, repository management, versioning of components.

Classification of means and methods of the Web semantic retrieval

2017 ◽  
pp. 030-050
Author(s):  
J.V. Rogushina ◽  
Keyword(s):  
Search Engines ◽  
Domain Knowledge ◽  
Information Needs ◽  
Web Search ◽  
User Interaction ◽  
Query Languages ◽  
Semantic Search ◽  
Semantic Retrieval ◽  
The Web

Problems associated with the improve ment of information retrieval for open environment are considered and the need for it’s semantization is grounded. Thecurrent state and prospects of development of semantic search engines that are focused on the Web information resources processing are analysed, the criteria for the classification of such systems are reviewed. In this analysis the significant attention is paid to the semantic search use of ontologies that contain knowledge about the subject area and the search users. The sources of ontological knowledge and methods of their processing for the improvement of the search procedures are considered. Examples of semantic search systems that use structured query languages (eg, SPARQL), lists of keywords and queries in natural language are proposed. Such criteria for the classification of semantic search engines like architecture, coupling, transparency, user context, modification requests, ontology structure, etc. are considered. Different ways of support of semantic and otology based modification of user queries that improve the completeness and accuracy of the search are analyzed. On base of analysis of the properties of existing semantic search engines in terms of these criteria, the areas for further improvement of these systems are selected: the development of metasearch systems, semantic modification of user requests, the determination of an user-acceptable transparency level of the search procedures, flexibility of domain knowledge management tools, increasing productivity and scalability. In addition, the development of means of semantic Web search needs in use of some external knowledge base which contains knowledge about the domain of user information needs, and in providing the users with the ability to independent selection of knowledge that is used in the search process. There is necessary to take into account the history of user interaction with the retrieval system and the search context for personalization of the query results and their ordering in accordance with the user information needs. All these aspects were taken into account in the design and implementation of semantic search engine "MAIPS" that is based on an ontological model of users and resources cooperation into the Web.

Method of semantic search and analysis of information

2020 ◽  
pp. 75-80
Author(s):  
A.L. Ogarok
Keyword(s):  
Computer Systems ◽  
Linguistic Analysis ◽  
Semantic Search ◽  
Textual Information ◽  
Formalized Description

The methodology of semantic search and analysis of information is considered. The results of the analysis of various approaches to solving the problem of a complete linguistic analysis of textual information in computer systems are presented. A formalized description of the method of semantic search and analysis of information is given.

scholarly journals A new measure of group decision-making efficiency

2020 ◽  
Vol 5 (1) ◽  
Author(s):  
Cheng-Ju Hsieh ◽  
Mario Fifić ◽  
Cheng-Ta Yang
Keyword(s):  
Decision Making ◽  
Information Processing ◽  
Group Decision Making ◽  
Group Decision ◽  
Detection Task ◽  
Detection Sensitivity ◽  
System Level ◽  
Workload Capacity ◽  
Individual Decisions ◽  
Collective Benefit

Abstract It has widely been accepted that aggregating group-level decisions is superior to individual decisions. As compared to individuals, groups tend to show a decision advantage in their response accuracy. However, there has been a lack of research exploring whether group decisions are more efficient than individual decisions with a faster information-processing speed. To investigate the relationship between accuracy and response time (RT) in group decision-making, we applied systems’ factorial technology, developed by Townsend and Nozawa (Journal of Mathematical Psychology 39, 321–359, 1995) and regarded as a theory-driven methodology, to study the information-processing properties. More specifically, we measured the workload capacity CAND(t), which only considers the correct responses, and the assessment function of capacity AAND(t), which considers the speed-accuracy trade-off, to make a strong inference about the system-level processing efficiency. A two-interval, forced-choice oddball detection task, where participants had to detect which interval contains an odd target, was conducted in Experiment 1. Then, in Experiment 2, a yes/no Gabor detection task was adopted, where participants had to detect the presence of a Gabor patch. Our results replicated previous findings using the accuracy-based measure: Group detection sensitivity was better than the detection sensitivity of the best individual, especially when the two individuals had similar detection sensitivities. On the other hand, both workload capacity measures, CAND(t) and AAND(t), showed evidence of supercapacity processing, thus suggesting a collective benefit. The ordered relationship between accuracy-based and RT-based collective benefit was limited to the AAND(t) of the correct and fast responses, which may help uncover the processing mechanism behind collective benefits. Our results suggested that AAND(t), which combines both accuracy and RT into inferences, can be regarded as a novel and diagnostic tool for studying the group decision-making process.

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