Development Of Search Systems Research Articles

Enhancing Online Search Security Through Bayesian Trust Network Implementation

The article focuses on the development of an information search and protection system based on a Bayesian trust network as a measure of document relevance to the user’s query. The result is the development of search system structures and algorithms with relevance evaluation when searching the Internet, the implementation of data transmission with an adaptive database for storing decisions. If the need arises, when the goal set before the user cannot be achieved without involving additional information, the adaptive database sends a request to the search system, which in turn collects the necessary information. Mathematical formalization of the definition of relevant decisions was carried out. A graph was modelled, which was built based on Bayesian Trust Networks (BTN) in the GeNIe application package.

A Framework for the Construction of Ontology for ICT Experts

Systems that help to find answers to suitable experts have received the attention of many researchers. Pioneer researchers on the development of search system for experts emphasized the importance of a search system that required returning a list prioritizing the names of individuals. Among the issues raised related to locating experts are, the critical problem of maintaining up-to-date information in the expert database and the inadequacy in expert finding systems in returning search results that are expected to account for not only the list of the names of the experts, but any information related to the experts and those involved with them. In the last decade, researchers have examined the search for experts from various research perspectives such as expert tracking system and construction of expert profiles involving ontology. This paper aims to describe a new approach in designing a framework for the construction of ontology that will be used in the directory of ICT experts. The researchers propose to incorporate thesaurus in their construction of ontology on ICT experts by providing a profile of the experts including their social profile and whatever concerns that may be associated with the expert. The researchers constructed the ontology on ICT experts by extracting information from sources such as their resumes and personal web sites to obtain the index glossary of words that characterized experts to be used in the directory of experts system. In this study, the standards contained in the Performance Evaluation System of the National University of Malaysia are used to extract information on the academicians in the Faculty of Information Science and Technology. The researchers employed the index glossary, metadata of experts and integrate appropriate taxonomy, thesaurus and classification schemes; such as Association for Computing Machinery (ACM) taxonomy, web classification schemes such as Standard Industrial Classification (SIC), North American Industry Classification System (NAICS) to enrich the ontology of ICT expertise. The proposed framework aims at helping users find information on the expert they require and at the same time obtain other information related to the experts from various perspectives encompassing research, consultancy, links with research partners, other interest related to a particular field and other resources. With a semantically driven directory of ICT experts, matters related to ICT can be referred to the right experts. The framework will be validated by developing the directory of ICT experts prototype and by involving domain experts to evaluate the content of the ontology constructed. In addition, the researchers will evaluate the search results of users who will use the prototype to search for ICT experts.

Examination of relevance criteria choices and the information search process

PurposeThe purpose of this paper is to examine changes in relevance assessments, specifically the selection of relevance criteria by subjects as they move through the information search process.Design/methodology/approachThe paper examines the relevance criteria choices of 39 subjects in relation to search stage. Subjects were assigned a specific search task in a controlled test. Statistics were collected and analyzed using descriptive statistics and the chi‐square goodness‐of‐fit tests.FindingsThe statistically significant findings identified a number of commonly reported relevance criteria, which varied over an information search process for relevant and partially relevant judgments. These results provide statistical confirmations of previous studies, and extend these findings identifying specific criteria for both relevant and partially relevant judgments.Research limitations/implicationsThe study only examines a short duration search process and since the convenience sample of subjects were from similar backgrounds and were assigned similar tasks, the study did not explicitly examine the impact of contextual factors such as user experience, background or task in relation to relevance criteria choices.Practical implicationsThe paper has implications for the development of search systems which are adaptive and recognize the cognitive changes which occur during the information search process. Examining and identifying relevance criteria beyond topicality and the importance of those criteria to a user can help in the generation of better search queries.Originality/valueThe paper adds more rigorous statistical analysis to the study of relevance criteria and the information search process.

Development of Searching system for Fire Areas in Forests and Fields utilizing MODIS data

Development of Searching system for Fire Areas in Forests and Fields utilizing MODIS data

COLLABORATIVE FILTERING: A NEW APPROACH TO SEARCHING DIGITAL LIBRARIES

At Oregon State University (OSU), the School of Electrical Engineering and Computer Science (EECS) and the OSU Libraries are working together on a project to improve the effectiveness and accessibility of digital information created and collected by academic libraries. This project focuses on making digital resources more accessible through an innovative search interface that incorporates collaborative filtering. New approaches to search interfaces will help make the growing wealth of online content more accessible and useful. This paper discusses the problem, explains how collaborative filtering works, describes the System for Electronic Recommendation Filtering (SERF), and then presents initial results from an installation in the OSU Libraries. The productive collaboration at OSU between the Libraries and EECS portends the future of development of search systems; by working together, we can harness the expertise of librarians, computer scientists, and information users to develop more useful search interfaces and increase access to the libraries’ resources and services.

携帯端末を援用した罹災者発見システム(レスキューシステム・レスキュー工学1)

携帯端末を援用した罹災者発見システム(レスキューシステム・レスキュー工学1)