Keyword Information Research Articles

On the Security of Privacy-Preserving Attribute-Based Keyword Search in Shared Multi-owner Setting

Recently in the IEEE Transactions on Dependable and Secure Computing (doi: 10.1109/TDSC.2019.28976752019), Miao et al. proposed a novel construction of Privacy-Preserving Attribute-Based Keyword Search in Shared Multi-owner Setting (ABKS-SM), which can delegate keyword search tasks to cloud server provider (CSP) without revealing any useful information. Although the authors claimed that the offline keyword guessing attacks can be resisted in ABKS-SM scheme, we show that this scheme indeed suffers from four types of offline keyword guessing attacks and hence fails to gain the claimed security property, which is an important goal to be achieved in searchable encryption schemes. Specifically, given the concrete attacks, we demonstrate that the underlying keyword information can be extracted from both encrypted keyword indexes and trapdoors by any malicious user and any adversarial CSP. We hope that the similar security vulnerabilities could be avoided in the future design of related searchable encryption schemes.

Research status and hotspots of economic evaluation in nursing by co-word clustering analysis

Abstract Objective The aim of this study is to discover research status and hotspots of economic evaluation (EE) in nursing area using co-word cluster analysis. Methods Medical Subject Heading (MeSH) term “cost–benefit analysis” was searched in PubMed and nursing journals were limited by the function of filter. The information of author, country, year, journal, and keywords of collected paper was extracted and exported to Bicomb 2.0 system, where high-frequency terms and other data could be further mined. SPSS 19.0 was used for cluster analysis to generate dendrogram. Results In all, 3,020 articles were found and 10,573 MeSH terms were detected; among them, 1,909 were MeSH major topics and generated 42 high-frequency terms. The consequence of dendrogram showed seven clusters, representing seven research hotspots: skin administration, infection prevention, education program, nurse education and management, EE research, neoplasm patient, and extension of nurse function. Conclusions Nursing EE research involved multiple aspects in nursing area, which is an important indicator for decision-making. Although the number of papers is increasing, the quality of study is not promising. Therefore, further study may be required to detect nurses’ knowledge of economic analysis method and their attitude to apply it into nursing research. More nursing economics course could carry out in nursing school or hospitals.

A Window-Based Self-Attention approach for sentence encoding

Recently, much progress has been made in the representation of sentences for the task of natural language processing (NLP). Most of existing methods utilize deep learning methods with RNN/CNN to capture contextual information. These models typically treat each word in a sentence equally, which ignores the fact that keywords always play a leading role in expressing the sentence semantic. Especially, on the tasks of sentence classification and semantic relatedness prediction, we can judge through the information of several keywords, no need for the whole sentence. To this end, we propose a window-based intra-weighing approach to weigh words in the sentence. In calculating attentive weights, we take as input multi-window n-grams and use max-pooling for feature extraction. To evaluate our model, we conduct experiments on 6 benchmark data sets. The experimental results demonstrate the superiority of our model in calculating word importance. Although our model has fewer parameters and much lower computational complexity than state-of-the-art models, it achieves comparable results with them.

Efficient Ranked Multi-Keyword Retrieval With Privacy Protection for Multiple Data Owners in Cloud Computing

With the significant rise in the demand for infinite storage resource and high-quality retrieval service, cloud computing is deemed to be a highly remarkable technology. For privacy concerns, several research works on ranked multi-keyword search over the encrypted cloud data under multiple data owner model have been developed. However, most of these schemes are vulnerable to keyword guessing attacks and equivalence test attack. Besides, they cannot accurately return the top - $k$ ranked search results from the encrypted data of different data owners to the data users. Obviously, these drawbacks may incur leakage of privacy-sensitive keyword information and the inaccuracy of returned search results. Therefore, in this article, we first propose a novel efficient ranked multi-keyword retrieval scheme with keyword privacy for multiple data owners, which empowers the cloud server to perform multi-keyword search over the cloud data and then, return the top - $k$ ranked search results to data users without leaking any keyword and trapdoor information. Additionally, we show through rigorous security analysis that our scheme is secure against the attacks launched by inside attackers and outside attackers. Finally, the performance evaluation indicates that our scheme has more satisfactory features than the existing ranked multi-keyword search schemes.

Visualization of Road Accident Data In Jabodetabek Area Year 2014-2017

Road accidents are a problem for all countries across the world because it causes material losses and life losses. The aim of this paper is to share findings in a road accident in visualization data in Jabodetabek area. Road accidents data obtained by doing text mining from social media Twitter using Tweepy API. Tweets taken is a tweet that has the word “accident” during the period from January 2014 to December 2017. Data is processed and labelled automatically by using a PHP program which has been created with an algorithm that reads a text pattern and finds the keyword. The keyword information then stored to a new column for desired information. Data that has been labelled in structured table form is processed with PowerBI tools. Labelled data will be processed using Power BI tools to provide visualization data output that provides detailed information about road accidents occurred in Jabodetabek during the year 2014-2017. Cars and trucks are the types of vehicle that most often has accidents, accidents are more common in the rainy season, and accidents prone time is T2 (04.00 a.m to 08.00 a.m).

Design of Reporting, Evaluation, and Monitoring Application for Student Organization in University

In few decades, the development of information system has been increased rapidly. It is because most organization in various sector of industries, commerce, government, or even education become highly dependent on the use of information system. The purpose of this study is to design the application that will facilitate the reporting, evaluation, and monitoring activities of student organization based on what user needs. The object of this study is student affair department in one of faculty in one of universities in Indonesia. The method employed in this study to design the system is waterfall. The system designed in this study is focus on the activities related to student organization activities. The result of this study found that there are eight dimensions of web quality that has to be fulfilled by the system according to the result of focus group discussion and Delphi method. The system designed in this study was adjusted to the needs that have been defined previously.
 
 Keywords—Information system design, student organization, waterfall method

Obtaining the Factors Affecting Bioeconomy

Abstract At the scientific level it is being increasingly recognised that the concept of bioeconomy has transdisciplinary nature, but there is still no consensus on key factors that would accelerate the development of sustainable bioeconomy. Therefore, within the framework of this study, certain factors, their interactions and link strength with bioeconomy from a scientific perspective are identified. A bibliometric analysis method is used to achieve this aim in such a way that the keyword information on the published scientific literature in relation to the bioeconomy is translated into quantifiable data. This way the relevance of the bioeconomy factors and the strength of their direct and mutual interaction with the bioeconomy will be determined. From this study it can be concluded that the strongest links with bioeconomy are for biomass, bioenergy, biotechnology and innovations. No significant link was found for such factors as: behaviour, production, pollution and infrastructure. It becomes clear that, in the view of scientists, the decisive role in the development of the bioeconomy resulting from the use of bio resources in the higher value-added production is for technologies. These results are used to build a framework for a system dynamics model that can be used for modelling bioeconomy development scenarios in the future.

A tripartite-graph based recommendation framework for price-comparison services

The recommender systems help users who are going through numerous items (e.g., movies or music) presented in online shops by capturing each user?s preferences on items and suggesting a set of personalized items that s/he is likely to prefer [8]. They have been extensively studied in the academic society and widely utilized in many online shops [33]. However, to the best of our knowledge, recommending items to users in price-comparison services has not been studied extensively yet, which could attract a great deal of attention from shoppers these days due to its capability to save users? time who want to purchase items with the lowest price [31]. In this paper, we examine why existing recommendation methods cannot be directly applied to price-comparison services, and propose three recommendation strategies that are tailored to price-comparison services: (1) using click-log data to identify users? preferences, (2) grouping similar items together as a user?s area of interest, and (3) exploiting the category hierarchy and keyword information of items. We implement these strategies into a unified recommendation framework based on a tripartite graph. Through our extensive experiments using real-world data obtained from Naver shopping, one of the largest price-comparison services in Korea, the proposed framework improved recommendation accuracy up to 87% in terms of precision and 129% in terms of recall, compared to the most competitive baseline.

A Keyword-Searchable ABE Scheme From Lattice in Cloud Storage Environment

Currently, the security situation of data security and user privacy protection is increasingly serious in cloud environment. Ciphertext data storage can prevent the risk of user's privacy disclosure. But how to search keyword on ciphertext data without revealing keyword information becomes a new challenge. Searchable encryption (SE) is put forward for this reason, which can be used to realize ciphertext-search directly. In terms of multi-user data sharing, public-key encryption with keywords search (PEKS) is more widely used than symmetric searchable encryption. PEKS has been widely studied and developed by researchers in recent years. However, the existing PEKS scheme often lacks flexible access policy. Therefore, combining the advantage of policy control on attribute-based encryption (ABE), and as that the bilinear pairing related assumption is fragile in post-quantum era, lattice-based cryptography is considered as one of secure encryption technology against quantum attack. With this background, in this paper, we give a keyword-searchable ABE scheme based on the hardness of lattice problems, our scheme supports flexible attribute control policy by integrating ABE and PEKS, and the security of new scheme is proved under the learning with errors (LWE) assumption. As lattice-based cryptographic technology is currently thought to be resistant to quantum attacks, so the new scheme has stronger security in a quantum era.

ЩОДО СТВОРЕННЯ ДЕРЖАВНОГО БАНКУ ДАНИХ ГЕОЛОГО-ГЕОФІЗИЧНОЇ ІНФОРМАЦІЇ

The article suggests creation of state database of geological and geophysical information. It deals with the main problem that must be solved during creation and implementation this database. It also defined the main information resources and possible hierarchical structure of state database of geological and geophysical information Key words: Databases, state bank of geological and geophysical data, exploration, processing, interpretation

How Does Asymmetric Information Create Market Incompleteness?

The aim of this work is to show that incompleteness is due in general not only to a lack of assets, but also to a lack of information. In this paper we present a simple inuence model where the inuencial agent has access to additional information. This leads to the construction of two models, a complete model and an incomplete model where the only dierence is a dierence of information. This leads to a simple model of incomplete market where the number of assets is not the cause of incompleteness: incomplete information is the explanation. Keywords Information · asymmetric information · option pricing · martin-gales · insider trading · complete market · incomplete market AMS Classication (2000): 60H10, 60G44, 60H07, 60J75, 91G20, 91B70, 93E11. JEL Classication: C60,G11,G14.

Document- and Keyword-based Author Co-citation Analysis

AbstractIn the field of scientometrics, the principal purpose for author co-citation analysis (ACA) is to map knowledge domains by quantifying the relationship between co-cited author pairs. However, traditional ACA has been criticized since its input is insufficiently informative by simply counting authors’ co-citation frequencies. To address this issue, this paper introduces a new method that reconstructs the raw co-citation matrices by regarding document unit counts and keywords of references, named as Document- and Keyword-Based Author Co-Citation Analysis (DKACA). Based on the traditional ACA, DKACA counted co-citation pairs by document units instead of authors from the global network perspective. Moreover, by incorporating the information of keywords from cited papers, DKACA captured their semantic similarity between co-cited papers. In the method validation part, we implemented network visualization and MDS measurement to evaluate the effectiveness of DKACA. Results suggest that the proposed DKACA method not only reveals more insights that are previously unknown but also improves the performance and accuracy of knowledge domain mapping, representing a new basis for further studies.

Design of Web-Based Material Management Information System in Financial Module (Case Study PT INTI)

PT INTI engaged in telecommunication, has long become a supplier of network construction with a large scale that is national. Therefore, PT INTI has a lot of material and spread all over the city in Indonesia. Previously, PT Inti still uses semi-manual way to do their material recording. The material recording is done by using Microsoft Excel which will be sent by electronic mail (email) if needed. But it is vulnerable to errors because the data contained in is not integrated. To overcome this, PT INTI wants to have a web based application called INTI Maintenance to manage financial materials such as material input, material search, material removal, material search, material data printing, to finance such as request addition, change of request status, delivery, and residual balances of each city. INTI Maintenance web-based information system financial module is built with open source software that uses PHP as the programming language, MySQL as the database, and Windows as server computer. The final results achieved in the material management information system in this module have advantages in assisting PT INTI employees in managing financial data and validation for material delivery using receipt of delivery material.
 
 Keywords—information system, management, material, finance.

Research on Pattern Representation Based on Keyword and Word Embedding in Chinese Entity Relation Extraction

With the rapid development of the Internet, it is becoming more and more important to extract the relationship between the entity from the massive network text and then to build the knowledge graph or the knowledge base. In this paper, we focus on the research of the pattern representation in relation extraction, and extract the high accuracy Chinese entity pairs from large scale web texts. Past relation patterns only consider shallow lexical and syntax, not accurately and deeply express pattern context information, and do not consider keywords information. According to the new entity relation extraction technology and the characteristics of Chinese corpora, we define pattern representation based on keywords and word embedding information, extract deep semantic feature of context information, and strengthen keywords information effect for relation extraction. In addition, we propose a method for obtaining sentence keyword based on word embedding. In the experiment, we use ChineseHudongEncyclopedia corpus to implement the character relation extraction system, and test the character relation extraction effect. The experimental results show that this method effectively improves the quality of the pattern, and obtains a favorable relation extraction performance.

LEGAL ASPECT OF CONSULTATION WITH DOCTOR VIA ONLINE SYSTEM IN INDONESIA

Development of technology, communications and the internet make people life easier and faster. Online systems provide changes to buy foods & goods, reserve online transportation even to get consultation with doctor. This research aims to examine the legal aspects of online consultation between doctor and patient or users, about the limitations that can be given in the consultation. The method used is the normative juridical method, using secondary data in the form of books, journals, articles and related regulations and data analysis techniques used are qualitative descriptive. The results of the study: (1). People can consult & communicate with doctors through the online medium by providing true information about their disease history, use of certain drugs and doctors would give the opinions according to the patient's information and the code of ethics; (2). The consultation of doctors through online media obeyed to the Law on Technology & Information, the Health Act, the Medical Practice Act, Consumer Protection Act.Key words: doctor, online consultation, patient, law on techology and informationKey words: doctor, online consultation, patient, law on techology and information

SKQAI: A novel air index for spatial keyword query processing in road networks

Spatial keyword query (SKQ) processing is gaining great interest with the proliferation of location-based devices and services. However, most of the existing SKQ processing methods are either focused on Euclidean space or suffer from poor scalability. This paper addresses the problem of SKQ processing in road networks under wireless broadcast environments, and devises a novel air index called SKQAI, which combines a road network weighted quad-tree, several keyword quad-trees and a distance bound array, to facilitate SKQ processing in road networks. Based on SKQAI, efficient algorithms for processing Boolean Range, Top-k and Ranked SKQs are proposed. The proposed methods can efficiently prune irrelevant regions of the road network based on both road network distance and keyword information, and thus improve query processing efficiency significantly. Finally, simulation studies on two real road networks and two geo-textual datasets are conducted to demonstrate the effectiveness and efficiency of the proposed algorithms.

Personal learning environments: A systematic literature review based on study keywords using thematic analysis

Throughout the last decade, there has been an important increase in the number of the Personal Learning Environment (PLE) research. However, there is a lack of recent systematic reviews covering the large amount of PLE studies. In this study, aforementioned gap is addressed using a hybrid method. This hybrid method is composed of Systematic Literature Review and Thematic Analysis Approach which are based on the keyword information of published PLE studies. As a result of our search query, we have reached 506 studies. Keywords of selected studies are recorded along with year of publication, study type and country of authors. We present the frequency distribution of all keyword themes (codes) and define the most frequent codes. We also share some trend graphics regarding the other study attributes (year of publication, study type and country of authors).      Keywords: Personal learning environment, PLE, personal learning, literature review, self-regulated learning.  &nbsp

Efficient Clue-Based Route Search on Road Networks

With the advances in geo-positioning technologies and location-based services, it is nowadays quite common for road networks to have textual contents on the vertices. Previous work on identifying an optimal route that covers a sequence of query keywords has been studied in recent years. However, in many practical scenarios, an optimal route might not always be desirable. For example, a personalized route query is issued by providing some clues that describe the spatial context between PoIs along the route, where the result can be far from the optimal one. Therefore, in this paper, we investigate the problem of clue-based route search ( ${\sf {CRS}}$ ), which allows a user to provide clues on keywords and spatial relationships. First, we propose a greedy algorithm and a dynamic programming algorithm as baselines. To improve efficiency, we develop a branch-and-bound algorithm that prunes unnecessary vertices in query processing. In order to quickly locate candidate, we propose an AB-tree that stores both the distance and keyword information in tree structure. To further reduce the index size, we construct a PB-tree by utilizing the virtue of 2-hop label index to pinpoint the candidate. Extensive experiments are conducted and verify the superiority of our algorithms and index structures.

AN EMPIRICAL INVESTIGATION OF INFORMATION TECHNOLOGY INVESTMENT AND BUSINESS PERFORMANCE AT FIRM LEVEL AND INDUSTRY LEVEL

ABSTRACT Since the popular of the term IT in the mid-1980s, the literature has attempted to investigate the benefits of IT investment, due to the enormous potential of IT investment to achieve competitive advantage and better firm performance. It can be indicated from previous literatures that national economic growth and firm performance are influenced by IT investment. However, limited number of studies are performed at industry level. This section shows significant line of thought to investigate the impact of IT investment on economic growth and industry performance. The main contribution of this study is to add the relationship between IT investment and business performance at industry level. The results indicated that the total amount of IT investment had significant positive association with business performance at both economic and industry levels for almost all the industries covered in the study. Keywords Information Technology (IT), Investment, business performance, economic growth, labor productivity

COST-BENEFIT ANALYSIS OF INFORMATION SYSTEMS SECURITY

ABSTRACT Economic aspects of information systems (IS) security are growing concern to small organizations in recent years due to security breaches. A recent study sponsored by IBM corporation’s security division states that on average, the cost of a security failure has increased to $4 million per incident-up 29% since 2013. The cost of a breached system varies widely by type of industry, according to findings of this study. Healthcare, a highly-regulated industry that deals with the most intimate personal information-which can include patient names, medical histories, credit card data, and Social Security numbers-has the highest cost per stolen record at $355 (Hackett, 2016). From a business standpoint cost-benefit-justifications for information systems security are in the focus. Today, the question is not whether more security is needed but how much to spend for added security. And yet investing in Information Systems Security has always been hard-sell for IS managers. There are a wide range of new security technologies to select from and yet if anything is certain is that none of them can provide full security. Each choice involves risk. Security managers need a structured cost-benefit methodology to examine and compare IS security solutions in relation to prevailing security risks. While most of the published research has applied economics models for security investments, this paper proposes using cost-benefit analysis for IS security enhancement projects. Keywords Information Systems Security, Cost-benefit analysis, IS Security Investment