• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.12
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• pp.5888-5903
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• 2019

The Relational ranking method applies authority-based ranking in relational dataset that can be modeled as graphs considering also their tuples' values. Authority directions from tuples that contain the given keywords and transfer to their corresponding neighboring nodes in accordance with their values and semantic connections. From our previous work, ObjectRank extends to ValueRank that also takes into account the value of tuples in authority transfer flows. In a maked difference from ObjectRank, which only considers authority flows through relationships, it is only valid in the bibliographic databases e.g. DBLP dataset, ValueRank facilitates the estimation of importance for any databases, e.g. trading databases, etc. A relational keyword search paradigm Object Summary (denote as OS) is proposed recently, given a set of keywords, a group of Object Summaries as its query result. An OS is a multilevel-tree data structure, in which node (namely the tuple with keywords) is OS's root node, and the surrounding nodes are the summary of all data on the graph. But, some of these trees have a very large in total number of tuples, size-l OSs are the OS snippets, have also been investigated using ValueRank.We evaluated the real bibliographical dataset and Microsoft business databases to verify of our proposed approach.

• International Journal of Computer Science & Network Security
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• v.22 no.12
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• pp.107-115
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• 2022

Recently, big data applications need another database different from the Relation database. NoSQL databases are used to save and handle massive amounts of data. NoSQL databases have many advantages over traditional databases like flexibility, efficiently processing data, scalability, and dynamic schemas. Most of the current applications are based on the web, and the size of data is in increasing. NoSQL databases are expected to be used on a more and large scale in the future. However, NoSQL suffers from many security issues, and one of them is access control. Many recent applications need Fine-Grained Access control (FGAC). The integration of the NoSQL databases with FGAC will increase their usability in various fields. It will offer customized data protection levels and enhance security in NoSQL databases. There are different NoSQL database models, and a document-based database is one type of them. In this research, we choose the CouchDB NoSQL document database and develop an access control mechanism that works at a fain-grained level. The proposed mechanism uses role-based access control of CouchDB and restricts read access to work at the document level. The experiment shows that our mechanism effectively works at the document level in CouchDB with good execution time.

• Journal of Agricultural Extension & Community Development
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• v.3 no.2
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• pp.177-195
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• 1996

This study examines the demand for agricultural information at farm level, using Probit and Logit models. 646 farmers are surveyed with a questionnaire to attain the data and 441 of them have responded. The demand functions for computers, agricultural softwares, and agricultural databases at from level have been derived and used to project the demand for agricultural information in year $2001{\sim}2004$. Results find that only 5.89% of farmers have PCs at farm and rarely use the agricultural databases and softwares in 1994. The low demand figures are mostly due to the difficulty of using the PCs, databases, and softwares. The demand figures will increase in early 2000`s with 15.46% of farmers having PCs. User Friendly developed softwares and databases, and education for using agricultural information are necessary to increase the demand figures.

• Journal of Information Processing Systems
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• v.14 no.3
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• pp.709-726
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• 2018

Database classification is an important preprocessing step for the multi-database mining (MDM). In fact, when a multi-branch company needs to explore its distributed data for decision making, it is imperative to classify these multiple databases into similar clusters before analyzing the data. To search for the best classification of a set of n databases, existing algorithms generate from 1 to ($n^2-n$)/2 candidate classifications. Although each candidate classification is included in the next one (i.e., clusters in the current classification are subsets of clusters in the next classification), existing algorithms generate each classification independently, that is, without taking into account the use of clusters from the previous classification. Consequently, existing algorithms are time consuming, especially when the number of candidate classifications increases. To overcome the latter problem, we propose in this paper an efficient approach that represents the problem of classifying the multiple databases as a problem of identifying the connected components of an undirected weighted graph. Theoretical analysis and experiments on public databases confirm the efficiency of our algorithm against existing works and that it overcomes the problem of increase in the execution time.

• Journal of Computing Science and Engineering
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• v.1 no.1
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• pp.1-30
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• 2007

In this paper we have provided an extensive survey of the databases and other resources related to the current research in bioinformatics and the issues that confront the database researcher in helping the biologists. Initially we give an overview of the concepts and principles that are fundamental in understanding the basis of the data that has been captured in these databases. We briefly trace the evolution of biological advances and point out the importance of capturing data about genes, the fundamental building blocks that encode the characteristics of life and proteins that are the essential ingredients for sustaining life. The study of genes and proteins is becoming extremely important and is being known as genomics and proteomics, respectively. Whereas there are numerous databases related to various subfields of biology, we have maintained a focus on genomic and proteomic databases which are the crucial stepping stones for other fields and are expected to play an important role in the future applications of biology and medicine. A detailed listing of these databases with information about their sizes, formats and current status is presented. Related databases like molecular pathways and interconnection network databases are mentioned, but their full coverage would be beyond the scope of a single paper. We comment on the peculiar nature of the data in biology that presents special problems in organizing and accessing these databases. We also discuss the capabilities needed for database development and information management in the bioinformatics arena with particular attention to ontology development. Two research case studies based on our own research are summarized dealing with the development of a new genome database called Mitomap and the creation of a framework for discovery of relationships among genes from the biomedical literature. The paper concludes with an overview of the applications that will be driven from these databases in medicine and healthcare. A glossary of important terms is provided at the end of the paper.

• International Journal of Knowledge Content Development & Technology
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• v.10 no.3
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• pp.21-31
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• 2020

The study examined information retrieval tools as predictors for information resources utilization, four research questions, and four hypotheses were made to guide the study. A descriptive survey was adopted for the study. Random sampling technique was used to select sample of 393 from a population of 557 academic staff registered in the University of Port Harcourt library. The questionnaire was adopted as a data collection instrument titled Information retrieval as predictors for information resources utilization (IRPIRUQ). Data were analyzed using both simple and multiple regression while analysis of variance (ANOVA) associate with regression was used for testing the hypotheses at 0.05 alpha level. The study revealed that information resources are under utilized as the OPAC and Online Databases are not easily accessed. Further findings showed that the academic staff made use of internet search engines more often than the OPAC and online databases. It was recommended among others that a new library software be installed in place of KOHA for wider connectivity and adequate distribution of software that will aid usage of the online databases and OPAC.

• Journal of the Korean Society for Library and Information Science
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• v.17
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• pp.49-83
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• 1989

A Full text retrieval system is a natural language document retrieval system in which the full text of all documents in a collection is stored on a computer so that every word in every sentence of every document can be located by the machine. This kind of IR System is recently becoming rapidly available online in the field of legal, newspaper, journal and reference book indexing. Increased research interest has been in this field. In this paper, research on full text databases and retrieval systems are reviewed, directions for research in this field are speculated, questions in the field that need answering are considered, and variables affecting online full text retrieval and various role that variables play in a research study are described. Two obvious research questions in full text retrieval have been how full text retrieval performs and how to improve the retrieval performance of full text databases. Research to improve the retrieval performance has been incorporated with ranking or weighting algorithms based on word occurrences, combined menu-driven and query-driven systems, and improvement of computer architectures and record structure for databases. Recent increase in the number of full text databases with various sizes, forms and subject matters, and recent development in computer architecture artificial intelligence, and videodisc technology promise new direction of its research and scholarly growth. Studies on the interrelationship between every elements of the full text retrieval situation and the relationship between each elements and retrieval performance may give a professional view in theory and practice of full text retrieval.

• Journal of KIISE:Databases
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• v.28 no.3
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• pp.406-417
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• 2001

With the advances in multimedia databases on the World Wide Web, it becomes more important to provide users with the search capability of distributed multimedia data. While there have been many studies about the database selection and the collection fusion for text databases. The multimedia databases on the Web have autonomous and heterogeneous properties and they use mainly the content based retrieval. The collection fusion problem of multimedia databases is concerned with the merging of results retrieved by content based retrieval from heterogeneous multimedia databases on the Web. This problem is crucial for the search in distributed multimedia databases, however, it has not been studied yet. This paper provides novel algorithms for processing the collection fusion of heterogeneous multimedia databases on the Web. We propose two heuristic algorithms for estimating the number of objects to be retrieved from local databases and an algorithm using the linear regression. Extensive experiments show the effectiveness and efficiency of these algorithms. These algorithms can provide the basis for the distributed content based retrieval algorithms for multimedia databases on the Web.

• Journal of the Korean Society for information Management
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• v.16 no.1
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• pp.157-174
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• 1999

This investigation used meta-analysis to examine the quality of data of domestic ST(Science & Technical) databases. Analyses measured the quality of data itself, determined whether these databases have any critical errors in terms of accuracy, completeness, and consistency by conducting the data retrieval experiments. The purpose of this study was to diagnose the science & technical databases and to find out the problems of them and also to provide possible suggestions for their improvements. The researcher concluded the results by mentioning the three research questions.

• Journal of the Korean Society for Library and Information Science
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• v.32 no.3
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• pp.281-296
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• 1998

This study indicates that it is necessary to have characteristic information the information experts recognize-that is to say, experimental and inherent knowledge only human being can have built-in into the system rather than to approach the information system by the linguistic, statistic or structuralistic way, and it can be more essential and intelligent information system. As this study proves that the cited primary legal information within the secondary legal information functions as the index which represents the contents of the text because of the characteristics of legal information, the automatic indexing in the secondary legal full-text databases can be possible without the assitance of the experts. In case of the establishment, amendment or repealing of law, change of index terms can be possible through revising the legal text cited in the secondary legal information full-text databases. Even when we don't input the full-text about retrospective documents, automatic indexing is also possible, and the establishment and the practice of expert knowledge and integrated databases are possible in case of the retrospective documents.