Search Engine Applications Research Articles

Promoting convergence and efficacy of open‐domain question answering via unsupervised clustering

AbstractOpen‐Domain Question Answering (ODQA) has attracted increasing interests due to its extensive applications in search engines and smart robots. In the experiments, it is observed that the convergence of the method has a huge effect on the generalizability performance. Motivated by this observation, an unsupervised clustering technique (namely, ClusSampling) is proposed to promote both the convergence and efficacy of existing ODQA methods via unsupervised clustering. Specifically, unsupervised clustering is first conducted and then negative samples are selected for higher similarity to the questions. In addition, the authors propose to use gap statistics to determine the optimal number of clusters. Experimental results show that the method achieves notable speedup during training and produces accuracy gains of 5.3% and 2.2 on two widely used benchmarks.

A proposed semantic keywords search engine for Indonesian Qur’an translation based on word embedding

Obtaining relevant information from the Holy Qur’an can be really challenging for people who cannot speak Arabic, such as the Indonesian people. One technology implementation which is commonly used to tackle this problem is to develop a search engine application for Al-Qur’an verses. This paper proposes a search engine based on semantic representation keywords for the Indonesian translation of the Al-Qur’an which consists of 3 phases i.e., data preparation, document representation, and search engine development. In the first stage, the Al-Qur’an dataset was built using the official translation of the Al-Qur’an from the Ministry of Religion and then enriched with the Wikipedia corpus. The second phase is document representation which produces feature vectors by utilizing the Word2Vec algorithm. Finally, the development of a search engine that can find the most relevant verses by calculating the cosine similarity between the document and the keywords. It was found that the proposed search engine succeeded in exceeding the performance of ordinary search engines by finding wider information due to the use of semantic keywords. Apart from that, the proposed search engine succeeded in maintaining the relevance of search results by achieving precision and recall levels of 98.7% and 97.3% respectively.

Evaluation of Students’ Digital Skills in Learning Creative Entrepreneurship Projects on Vocational High Schools, Province of Central Java, Indonesia

In the era of the industrial revolution 4.0, entrepreneurial activities are already digital-based. The emergence of various types of digital transaction software as a media for buying and selling online is a challenge for students. The need for digital skills for Vocational High School (SMK) students to support digital-based entrepreneurial activities. The purpose of this research is to describe the achievement of digital skills in learning entrepreneurial creative projects at Vocational High Schools in Central Java Province, Indonesia. Evaluation of digital skills based on indicators from Monggilo. To describe the research objectives, the research method used is evaluation research. The research sample is thirty vocational students who already have an independent business. The data collection technique used an online questionnaire filling survey using a Google form while the data analysis technique used was interactive analysis from Miles and Huberman. The results showed that the digital skills of SMK students in learning Creative Projects and Entrepreneurship: (1) 80.6% of students use digital mobile/smartphone devices for entrepreneurship; (2) 67.7% of students use the Google search engine application software for entrepreneurship; (3) 93.5% of students use WhatsApp social media application software for entrepreneurship; (4) 58.1% of students use the DANA digital wallet application software; and (5) 58.1% of students use the Shopee market place application software. Based on the research data, it is recommended to provide digital marketing knowledge and skills in using marketplace application software and digital payments to vocational students when learning entrepreneurial creative projects.

Preconditioned weighted full orothogonalization method for solving singular linear systems from PageRank problems

AbstractThe PageRank model, which was first proposed by Google for its web search engine application, has since become a popular computational tool in a wide range of scientific fields, including chemistry, bioinformatics, neuroscience, bibliometrics, social networks, and others. PageRank calculations necessitate the use of fast computational techniques with low algorithmic and memory complexity. In recent years, much attention has been paid to Krylov subspace algorithms for solving difficult PageRank linear systems, such as those with large damping parameters close to one. In this article, we examine the full orthogonalization method (FOM). We present a convergence study of the method that extends and clarifies part of the conclusions reached in Zhang et al. (J Comput Appl Math. 2016; 296:397–409.). Furthermore, we demonstrate that FOM is breakdown free when solving singular PageRank linear systems with index one and we investigate the effect of using weighted inner‐products instead of conventional inner‐products in the orthonormalization procedure on FOM convergence. Finally, we develop a shifted polynomial preconditioner that takes advantage of the special structure of the PageRank linear system and has a good ability to cluster most of the eigenvalues, making it a good choice for an iterative method like FOM or GMRES. Numerical experiments are presented to support the theoretical findings and to evaluate the performance of the new weighted preconditioned FOM PageRank solver in comparison to other established solvers for this class of problem, including conventional stationary methods, hybrid combinations of stationary and Krylov subspace methods, and multi‐step splitting strategies.

Drug Information Resources in Iraqi Community Pharmacies (Conference Paper) #

Abstract
 Drug information resources are the information that is used in medications discovery, utilization, and management. Little information about different types of resources used by Iraqi community pharmacists is known. Therefore, the objectives were to determine drug information resources' type do the pharmacists used and the common drug information questions they faced during their work in community pharmacy. A cross-sectional descriptive study was conducted in different Iraqi provinces and online self-reported survey was introduced through Google Form Software to an appropriate sample of graduated pharmacists who were working in a private community pharmacy and having at least one year of experience between February 27 and May 15, 2021. The researchers received 201 usable surveys. British National Formulary was used by 47% of the surveyed pharmacists to find specific information, followed by "Pharmacotherapy(s) and Applied Therapeutics" (16.9% for both). On the other hand, internet was used by 93% of the surveyed pharmacists and Google search engine (65%) and Medscape application (62%) were frequently surfed to find specific drug information and 81% of pharmacists trusted in this information and passed them to consumers. Safety of drugs during pregnancy and lactation periods was the most frequently question received from the patients (60.7%). In conclusion pharmacists prefer to surf specific internet websites to collect specific information about medicines and they referred to pharmaceutical textbooks if available at their pharmacies to get such information. The pharmacist is the person who is more often accessed by patients and the patients follow pharmacist's instruction for specific drug related questions.

Recursive reordering and elimination method for efficient computation of PageRank problems

<abstract><p>The PageRank model is widely utilized for analyzing a variety of scientific issues beyond its original application in modeling web search engines. In recent years, considerable research effort has focused on developing high-performance iterative methods to solve this model, particularly when the dimension is exceedingly large. However, due to the ever-increasing extent and size of data networks in various applications, the computational requirements of the PageRank model continue to grow. This has led to the development of new techniques that aim to reduce the computational complexity required for the solution. In this paper, we present a recursive 5-type lumping algorithm combined with a two-stage elimination strategy that leverage characteristics about the nonzero structure of the underlying network and the nonzero values of the PageRank coefficient matrix. This method reduces the initial PageRank problem to the solution of a remarkably smaller and sparser linear system. As a result, it leads to significant cost reductions for computing PageRank solutions, particularly in scenarios involving large and/or multiple damping factors. Numerical experiments conducted on over 50 real-world networks demonstrate that the proposed methods can effectively exploit characteristics of PageRank problems for efficient computations.</p></abstract>

Hba1c Range Determination for Diabetes Treatment in Google Cloud Compute Engine and Serpapi

In this paper, we have taken a use case in the healthcare domain for the determination of factors for an accurate range of HbA1c in diabetics’ treatment. Google Search Engine Application Program Interface (API), SerpAPI@ is evaluated for the execution of Compute engine in Google cloud. As a service in Infrastructure as a Service (IaaS), the Compute Engine gives the accurate value in HbA1c in the work orchestration in Airflow (astronomer) of Apache and Cloud Composer. We have also developed the application layer for every work stream in python and application output is stored in Google Cloud Storage. The accuracy of diabetic range determination is calculated in python as a measure for the healthcare practitioner to provide the right line of treatment for diabetic patients. A python program is developed to connect to the Google Search with a wrapper of SerpAPI in the Google Cloud Scheduler and create the JSON file schema for parameterization of Search Engine API. The results are shared with customers in the healthcare domain. We have also addressed the challenges of diabetic treatment during long-term Covid-19.

IMPLEMENTATION OF E-GOVERNMENT IN PROCUREMENT OF GOODS AND SERVICES

This study aims to find out how the process of implementing E-Government in the Procurement of Goods and Services at the Medan City LPSE Office and to find out the obstacles faced by the Medan City Electronic Procurement Service (LPSE) in carrying out their authority and the settlement pattern applied. The research method used in this study is to use a systematic review to examine issues related to travel risk and gender, while Pickering discusses the benefits of systematic reviews in research, especially for those who are completing a doctoral program. The research begins by setting search keywords, then searching data through a predetermined search engine application. The results of this study conclude that the implementation of e-government in the city of Medan can create a synergy between the community and the government, where the community can participate in building the city, while the government can channel their ideas

Evidence-Based Cognitive Endoscopy Simulators: Do They Exist? A Systematic Search and Evaluation of Existing Platforms.

BackgroundThe development of guidelines by gastroenterology societies increasingly stresses evidence-based endoscopic practice.AimsWe performed a systematic assessment to determine whether endoscopic video teaching platforms incorporate evidence-based educational strategies and methods in order to disseminate guideline-based endoscopic management strategies.MethodsPlatforms with a video component were systematically identified using the Google search engine, Apple and Android application stores, and searching four major gastroenterology society websites and three known platforms, to identify all relevant platforms. Two video samples from each teaching platform were reviewed independently by two authors and assessed for use of a priori defined principles of evidence-based medicine, as determined by consensus agreement and for the use of simulation.ResultsFourteen platforms were included in the final analysis, and two videos from each were analyzed. One of the 14 platforms used simulation and incorporated evidence-based medicine principles consistently. Nine of the 14 platforms were not transparent in regard to citation. None of the platforms consistently cited the certainty of evidence or explained how evidence was selected.ConclusionsEducation of guideline-based endoscopic management strategies using principles of evidence-based medicine is under-utilized in endoscopic videos. In addition, the use of cognitive simulation is absent in this arena. There is a paucity of evidence-based cognitive endoscopy simulators designed for fellows that incorporate systematic evaluation, and efforts should be made to create this platform.Supplementary InformationThe online version contains supplementary material available at 10.1007/s10620-022-07558-w.

Semiotics of Advertising Communication in WEB 2.0 Network Social Services

The article is devoted to the study of semiotics in the advertising communication of web 2.0 network social services. The purpose of the article is to analyze the publications of various brands on social Internet services focused on communication with the consumer and the subsequent study of the features of the use of semiotics tools. The relevance of the article is due to the fact that the modern information society has increased interest in semiotic systems, including in the field of Internet communication. The modern vision of semiotics has gone beyond the traditional framework and defined it as part of global and local communication in web 2.0 social network services, not only between Internet users, but also in the areas of B2B and B2C. The study of the possibilities of semiotics in advertising communication on web 2.0 social platforms, using the example of search engine applications, the social network Instagram, and company sites, in this article is based on the works of R. Barthes, J. Baudrillard, Y. Lotman, and U. Eco. This material confirms our hypothesis that today, especially since the beginning of the pandemic, communication on web 2.0 services is not limited only to text with a picture/photos or videos, more and more often there are visualized scenes created with the help of graphic design with the use of symbols and iconic signs that are familiar to the consumer, which he easily decodes, since they are inscribed in his socio-cultural coordinate system. The innovation of the research is based on the fixation of modern criteria of advertising Internet communication: polycode, intertextuality and multimedia, used as a way of working with target audiences. The novelty of the material consists of the understanding that semiotics today is a new look not only at the branch of scientific knowledge, but also at the practical possibilities of sign systems in the digital age, when the sign becomes a part of the socio-cultural space, a trend of the global world, a tool for transmitting information, knowledge, positioning, a tool for manipulation, influence, and attracting attention. Thus, brands working with the audience in todays realities should take into account not only the product preferences of consumers, but also broadcast their social / civic activity.

Design of Digital Library Data Search Engine Based on Cloud Computing in Big Data Era

In the big data environment, people’s acquisition of knowledge is no longer limited to the contents of books, but more data information from the Internet. Intelligent search engine implements information retrieval based on knowledge level, with strong natural language understanding and knowledge processing ability, showing good personalized information service characteristics. he theory of information ecology uses the theory, viewpoint and method of ecology to study the constituent factors of information ecosystem. Excess information and meeting the needs of readers have become the main contradictions in library services. As an architecture model suitable for library application, cloud computing can integrate scattered internet information data, realize the intensification of digital libraries, and provide a new solution for building and sharing digital resources and intelligent search engines. This paper discusses the construction mode of digital library service platform based on cloud computing technology, and analyzes the application and design method of intelligent search engine of cloud service digital library under the background of big data.

Comparative Analysis of Brute Force and Boyer Moore Algorithms in Word Suggestion Search

The development of information that continues to develop causes an explosion of information which certainly has a very complex impact on information storage management. This also impacts on companies that have several data that continues to grow every day. Therefore, there is a needs to have a search engine algorithm that can do a search system quickly with the development of information that continues to increase every day. Search engine applications or search engines in a computer system make it easy for users to find a variety of information. To facilitate its use, search engines add search features or better known as word suggestion, which in designing this application requires string matching algorithms that can be used to solve these problems. Many strings matching algorithms are available and therefore, the need for an analysis of the search algorithm to be able to help determine which search system is appropriate for use in word suggestion search. The result comparing brute force and boyer moore algorithm, it was found that as much as 79.05% showed that the Boyer Moore algorithm has a better time efficiency compared to the Brute Force.

Massively parallel algorithms for personalized pagerank

Personalized PageRank (PPR) has wide applications in search engines, social recommendations, community detection, and so on. Nowadays, graphs are becoming massive and many IT companies need to deal with large graphs that cannot be fitted into the memory of most commodity servers. However, most existing state-of-the-art solutions for PPR computation only work for single-machines and are inefficient for the distributed framework since such solutions either (i) result in an excessively large number of communication rounds, or (ii) incur high communication costs in each round. Motivated by this, we present Delta-Push , an efficient framework for single-source and top- k PPR queries in distributed settings. Our goal is to reduce the number of rounds while guaranteeing that the load, i.e., the maximum number of messages an executor sends or receives in a round, can be bounded by the capacity of each executor. We first present a non-trivial combination of a redesigned parallel push algorithm and the Monte-Carlo method to answer single-source PPR queries. The solution uses pre-sampled random walks to reduce the number of rounds for the push al6gorithm. Theoretical analysis under the Massively Parallel Computing (MPC) model shows that our proposed solution bounds the communication rounds to [EQUATION] under a load of O ( m/p ), where m is the number of edges of the input graph, p is the number of executors, and ϵ is a user-defined error parameter. In the meantime, as the number of executors increases to p' = γ · p , the load constraint can be relaxed since each executor can hold O (γ · m/p' ) messages with invariant local memory. In such scenarios, multiple queries can be processed in batches simultaneously. We show that with a load of O (γ · m/p' ), our Delta-Push can process γ queries in a batch with [EQUATION] rounds, while other baseline solutions still keep the same round cost for each batch. We further present a new top- k algorithm that is friendly to the distributed framework and reduces the number of rounds required in practice. Extensive experiments show that our proposed solution is more efficient than alternatives.

The making of Android-based search engine applications with Elastic-search algorithm to improve programming competence

This research aims to create an Android-based search engine application using the Elastic-search algorithm which can later be used for students learning object-oriented programming. This media contains a search for material that makes it easy to learn and do assignments. The method used in developing this application is 4D from Thiagarajan and using Java language programming. The results of this study indicate that this application is valid for use in terms of Quality of visual and auditory perception, Ease of interaction and collaboration, Ease of learning to operate, Ease of use. It can be concluded that the Search engine application with Elastic Search algorithm is declared valid to be used as learning for students who want to learn about programming.

Semantic voice search in IETP: filling the gap for maintenance 4.0

PurposeA framework is being developed to help Integrated Electronic Technical Publications (IETP) consultation inside and outside the aviation maintenance hangar. The expected results are the reduction in time to access the desired IETP and to assist mechanics while performing maintenance tasks using voice recognition.Design/methodology/approachThe work is being conducted based on literature review and consultation with mechanics from the aviation industry, through questionnaires. The development will be made through study cases by building a core search engine and mobile applications to support the mechanics during the maintenance activities.FindingsThe identified problem in small maintenance shops and defence organizations suggests that IETP are not entirely accessible before and during the maintenance activity. Such organizations suffer from information and communications technology (ICT) low infrastructure capability and demand access to multiple IETP databases as they usually support different aircraft. To have access to the IETP through voice assistant application will help mechanics to access the IETP, including when they would be with dirty hands and having difficulty in using mobile devices with touch displays.Originality/valueThe framework being developed will give mechanics the ability to quickly find any existing IETP to support its maintenance task at any time and in any place with low demanding for ICT infrastructure. The architecture will support different applications, and the identified priority is for IETP viewers to the most demanding functionality of specification ASD S1000D. This approach could also help in troubleshooting activities since COVID-19 brought new demands for the social distancing for mechanics.

Research on Data Management of Marine Disaster Mitigation Based on Big Data

With the explosive growth of ocean data, ocean big data has received more and more attention. It mainly analyzes and summarizes the current research status and key technologies of ocean big data, and focuses on the examples of machine learning model prediction research in ocean big data. With the advancement of 3S technology, China’s marine monitoring network has achieved all-round development, including air, ground, and sea monitoring platforms, which has promoted the rapid growth of marine big data from the original GB and TB levels to PB levels. Taking the typhoon disaster search and situation display implementation as an example, the thesis has preliminarily completed the realization and application of the intelligent ocean search engine. Combined with the design of typhoon disaster search and the overall structure and function design of the situation display, module development was carried out, and the development was initially completed to realize the business data management of marine typhoon disaster mitigation based on big data.

Application of full-text search engine in coal mine operation and maintenance system

Application of full-text search engine in coal mine operation and maintenance system

图片搜索引擎在舆情导控中运用的实验研究

图片搜索引擎在舆情导控中运用的实验研究

Application of a Web Search Engine in Translating Business Terms in English-Chinese Dictionaries

Application of a Web Search Engine in Translating Business Terms in English-Chinese Dictionaries

IMPLEMENTASI ALGORITMA DIJKSTRA PADA APLIKASI WISATA KUNINGAN BERBASIS ANDROID

Kuningan Regency is one of the tourist destinations that is quite popular among tourists. Kuningan has many potential tourism object whether it is natural tourism, history, jiarah, and artificial. To find tourism destinations, tourists are usually looking at search engine applications or tourist maps so it takes a long time. To facilitate tourists in finding tourist destinations, it needs an application. The application that will be developed based on preliminary research held at Dinas Pemuda Olahraga dan Pariwisata Kabupaten Kuningan. Mobile-based application is needed in finding the location of tourissm objects and it provides descriptions of attractions, and facilities that exist in the tourism object. It is created only to show the location of existing tourism object in Kuningan Regency. In finding the closest route, it will be displayed in the form of maps. Tourists can choose the location of tourist attractions and initial location of tourists, then the system will display the results of the existing route on the maps. And in this application is also available services to find the location of tourists using GPS technology. And the author uses Dijkstra algorithm to determine the shortest route in finding the route from the initial location to the desired location of the object of tourism. And in the data storage in this application, the author uses MySQL or Apache as a web server in storing data objects and data node,, destination and route concerned with searching the location of the tourist attraction. And on the development of this application he uses client server. Keywords: Dijkstra Algorithma, Nearest Order, Mobile-based Application, Kuningan District, Tourism Object.