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Research on the diverse benefits of nature to people is characterised by a broad range of disciplines involved, encompassing a variety of approaches, methods and terminologies. While a diversity of approaches is valuable, it can lead to difficulties in integrating and sharing findings, and could form a barrier to effective knowledge exchange, hindering the development and applications of research outputs.As a starting point for this scoping review, we chose four broad research areas (medicine, psychology, education and environment), selected to represent disparate approaches to research on the benefits of nature to people, within and across which to explore overlap in citations and terms used to describe nature.We conducted expert consultation and a snowball‐based approach to source publications, resulting in a sample of 210 papers spanning multiple disciplines within each of our four research areas. For each paper, we recorded the discipline of the journal in which it was published (publishing discipline), the discipline of its first author (first‐author discipline), the number of times journals of each discipline were cited in their bibliographies (cited discipline) and the term(s) used in the paper's title or abstract to describe the aspect of nature being explored (nature term).The cited disciplines were significantly different between publishing and first‐author disciplines, with papers from psychology, education and public health citing distinct communities of papers. However, disciplines generally cite a wide range of other disciplines, with articles in medical journals being particularly broadly cited.Nature terms were significantly different between publishing and first‐author disciplines, with some degree of consistency within disciplines (e.g. education papers consistently used a narrow range of nature terms, such as 'outdoor learning'). However, there was a notably high range of nature terms used within psychology and public health papers, indicating that research from these disciplines may be particularly prone to being overlooked by search strings.The wide range of disciplines cited is encouraging, since this indicates that diverse research areas are generally aware of each other's work. However, to avoid unnecessary expansion of nature terms and support searchability, we propose four key terms for nature: ('outdoor learning' OR 'outdoor education'), ('nature' OR 'natural'), ('green space' OR 'greenspace') and ('biodiversity' or 'trees'), which could be used across disciplines. We particularly propose that at least one of these be included in every paper, and all four should be included in review search strings. This is likely to result in a better understanding of the valuable, disparate contributions made by different disciplines to this expanding and important topic. Read the free Plain Language Summary for this article on the Journal blog. Read the free Plain Language Summary for this article on the Journal blog. [ABSTRACT FROM AUTHOR]

The literature of neuroimaging meta‐analysis has been thriving for over a decade. A majority of them were coordinate‐based meta‐analyses, particularly the activation likelihood estimation (ALE) approach. A meta‐evaluation of these meta‐analyses was performed to qualitatively evaluate their design and reporting standards. The publications listed from the BrainMap website were screened. Six hundred and three ALE papers published during 2010–2019 were included and analysed. For reporting standards, most of the ALE papers reported their total number of Papers involved and mentioned the inclusion/exclusion criteria on Paper selection. However, most papers did not describe how data redundancy was avoided when multiple related Experiments were reported within one paper. The most prevalent repeated‐measures correction methods were voxel‐level FDR (54.4%) and cluster‐level FWE (33.8%), with the latter quickly replacing the former since 2016. For study characteristics, sample size in terms of number of Papers included per ALE paper and number of Experiments per analysis seemed to be stable over the decade. One‐fifth of the surveyed ALE papers failed to meet the recommendation of having >17 Experiments per analysis. For data sharing, most of them did not provide input and output data. In conclusion, the field has matured well in terms of rising dominance of cluster‐level FWE correction, and slightly improved reporting on elimination of data redundancy and providing input data. The provision of Data and Code availability statements and flow chart of literature screening process, as well as data submission to BrainMap, should be more encouraged. [ABSTRACT FROM AUTHOR]

Biologists increasingly rely on computer code to collect and analyze their data, reinforcing the importance of published code for transparency, reproducibility, training, and a basis for further work. Here, we conduct a literature review estimating temporal trends in code sharing in ecology and evolution publications since 2010, and test for an influence of code sharing on citation rate. We find that code is rarely published (only 6% of papers), with little improvement over time. We also found there may be incentives to publish code: Publications that share code have tended to be low‐impact initially, but accumulate citations faster, compensating for this deficit. Studies that additionally meet other Open Science criteria, open‐access publication, or data sharing, have still higher citation rates, with publications meeting all three criteria (code sharing, data sharing, and open access publication) tending to have the most citations and highest rate of citation accumulation. [ABSTRACT FROM AUTHOR]

Due to the progress of Internet technology and the increase of distributed information on networks, the present approach to knowledge management has been based more and more on the performance of various experienced users. In addition to the increase in electronic documents, the use of paper documents has not been reduced due to their convenience. This paper describes a method of tracking paper document locations and contents using radio frequency identification (RFID) technology. This research also focuses on the expression of a task process and the seamless structuring of related electronic and paper documents as a result of task knowledge formalization using information organizing. A system is proposed here that implements information organization for both Web documents and paper documents using the task model description and RFID technology. Examples of a prototype system are also presented. © 2012 Wiley Periodicals, Inc. Electron Comm Jpn, 95(8): 52-63, 2012; Published online in Wiley Online Library (). DOI 10.1002/ecj.10370 [ABSTRACT FROM AUTHOR]

In this paper, the authors apply the feature pyramid network (FPN) to the single‐stage anchor‐free object detection algorithm CenterNet, and the effectiveness of the multi‐level feature fusion of FPN for the object detection algorithm is proved by experiments. However, multi‐level feature fusion leads to an increase in computational cost. In this regard, this paper proposes an object detection algorithm, called DDE‐Net, that does not use multi‐level feature fusion and only uses single‐level feature for optimization. The key component in it: the dense dilated encoder, which encourages dense information exchange of features between different spatial scales. This paper presents extensive experiments, and DDE‐Net shows strong performance compared to that of other popular models on the PASCAL VOC and on the COCO2017 dataset. On the COCO2017 dataset, the authors' DDE‐Net achieves comparable results with its feature pyramids counterpart RetinaNet, while applying the same backbone with smaller params and GFLOPs than RetinaNet. With an image size of 512 × 512, DDE‐Net achieves 37.3 AP running at 81 fps on 2080 Ti. [ABSTRACT FROM AUTHOR]

Summary: Sometimes, unverified information is disseminated as if it is true information on social media sites. Most of the times, it goes viral and affects the belief of people and their emotions. Rumors and fake news are the most popular form of false and unconfirmed information. Such news must be identified quickly for preventing its negative impact on society. In the last decade, operational procedures for rumors and false news detection came into existence. This paper provides a holistic view of different web waves from web 1.0 to web 5.0 and their usages. Further, taxonomy describes various malicious information contents at different stages. It discusses features used for classification, publicly available datasets, the rumor detection methods proposed during web 1.0, 2.0, 3.0, 4.0, 5.0 periods, and comprehensive analysis related to various methods and techniques. Numerous research gaps and future directions are illustrated to make online information more trustworthy for knowledge sharing and decision‐making purposes. [ABSTRACT FROM AUTHOR]

Cetaceans are considered ecosystem engineers and useful bioindicators of the health of marine environments. The Eastern North Atlantic is an area of great geographical and oceanographic complexity that favours ecosystem richness and, consequently, cetacean occurrence. Although this occurrence has led to relevant scientific research on this taxon, information on the composition of this research has not been assessed.We aimed to describe and quantify the evolution of research on cetaceans in the Eastern North Atlantic, highlighting the main focal areas and trends.We considered 380 peer‐reviewed publications between 1900 and 2018. For each paper, we collected publication year, research topics and regions, and species studied. We assessed differences among regions with distinct socio‐economic landscapes, and between coastal and oceanic habitats. To evaluate the changes in scientific production over time, we fitted a General Additive Model to the time series of numbers of papers.Although research in this region has been increasing, the results show relatively little research output in North African and coastal regions within the study area. Moreover, except for four studies, research was restricted to a few miles around the coast of the main islands, leaving offshore regions less well surveyed. There was little research on genetics, acoustics, and behaviour. Most papers were focused on the Azores and Canary Islands, and mostly involved Tursiops truncatus, Delphinus delphis, and Physeter macrocephalus. Species considered Endangered or Near Threatened were the subjects of only 10% of the studies.We suggest a greater research focus on beaked whales (Ziphiidae) in Macaronesia, as well as collaborative efforts between research teams in the region, by sharing data sets, and aiming to produce long‐term research. Moreover, a Delphi method approach, based on questionnaires answered by experts, could be attempted to identify priority research for cetaceans in these areas. [ABSTRACT FROM AUTHOR]

This paper shows that the optimal policy to deal with unemployment features important roles for monitoring of search and job search assistance, with the optimal combined policy also incorporating more generous unemployment insurance (UI). These results are significantly different from the previous literature, which has overwhelmingly focused on UI on its own. I incorporate two empirically relevant phenomena that have often been ignored: private consumption smoothing and fiscal externalities from income taxes. I estimate a job search model using indirect inference on data from the March Current Population Survey, and simulate the model to evaluate a variety of policy reforms. [ABSTRACT FROM AUTHOR]

The concept and influence of untraded inter‐dependencies are under‐explored in the industrial cluster and informal economy literature. In this paper, we attempt to bridge this gap by extending the conventional Cobb‐Douglas production function to operationalising and testing the moderating effects of two forms of untraded inter‐dependencies in informal production. Based on the diffusion theory, we argue that knowledge‐sharing would favour informal production, as opposed to tool‐sharing. Using quantitative methods, 334 informal artisans were randomly sampled from three clusters in the Kumasi Metropolis of Ghana and analysed data obtained with moderating models and simple slopes plots. The tested models and fuzzy set configurations confirmed that knowledge‐sharing, but not tool‐sharing, has significant interaction effects on informal production. The optimal model derived would be one in which capital interacts with incremental knowledge‐sharing at the existing level of tool‐sharing among the artisans. This paper serves as an extension of new economic geography with an additional factor of untraded inter‐dependencies. As part of post‐COVID restoration and enhancement of informal production processes, we recommend city officials to deliberately plan and space clustered enterprises that enable the observed rates of interactions between production factors and untraded inter‐dependencies. [ABSTRACT FROM AUTHOR]

Summary: Internet of Things (IoT) connects different objects in the physical world to the Internet, and various Internet protocols are used to provide communication services to a large number of these embedded devices termed as smart devices. But, these devices are resource‐constrained, low configured, and have very low power storage capacity, which depends on the services offered by the protocols. For the exchange of information to the end‐users, smart devices communicate through an open channel, such as the Internet, which is not secure enough. Moreover, efficient delivery ratio, secure data forwarding are not achieved because of the enormous amount of data produced by these smart devices and the possibility of security threats. So there is a need to devise a secure and reliable data dissemination scheme for the IoT environment. Motivated from the these facts, this paper presents a systematic review and propose a solution taxonomy for secure data dissemination techniques for various smart IoT‐based applications. This paper also includes a comparison of the state‐of‐the‐art data dissemination techniques used for the Internet of Vehicles (IoVs), Internet of Drones (IoDs), and Internet of Battlefield Things (IoBTs) applications along with their merits and demerits. Finally, the research challenges and possible countermeasures are also discussed in detail, which gives insights to the beginners who want to start work in this emerging area. [ABSTRACT FROM AUTHOR]

Business process modeling and implementation has taken researchers' attention for almost 30 years, since Hammer and Champy published in 1992 their book on business process reengineering. Process management proponents mostly focused on the system approach and workflow modeling. In this paper, we would like to emphasize the issues of business process paradigm development. This paper's aim is to confront workflow modeling with case management. These two approaches have different purposes, although, through their application, the process paradigm change is presented. This study methodology covers the literature survey (LS) and case study. The LS on the application of Case Management Model Notation (CMMN) is included to answer the question for what purposes CMMN is applied. The empirical part covers a case study on remote audit (e‐audit) process modeling. Further, a discussion on the strengths and weaknesses of e‐audit process is included. Final conclusions concern the transformability of process modeling methodologies. This paper contributes to process management theory with explanations of how and why specific e‐audit processes are developed and how they expand process managers' practices. The e‐audit activities are included in step‐by‐step processes as well as in the case management model to improve knowledge sharing and practice improvement. [ABSTRACT FROM AUTHOR]

This paper explores co‐production of knowledge for impact with young people through the process of creating digital story maps, drawing on co‐produced research from two projects: with homeless youth in African cities; and with youth refugees in Uganda and Jordan. It examines the process of creating three story maps with the intention of enabling young people to co‐produce knowledge exchange and research impact. Participants were able to engage in the latter stages of research as part of research analysis, outcomes and outputs beyond the temporal and spatial confines of data collection. The story maps were therefore used not only to 'bring life' to reports produced for stakeholders and funders, but also to take young people's research stories beyond locally bound contexts to reach a variety of global audiences. The reflections in this paper also highlight that while the approach adopted was not without challenges, in all three story maps a knowledge exchange process was fostered that resulted in young people feeling they had been listened to; were able to contribute to debates that affect their own lives and to instil a desire to create change, influence policy and inform publics about their lives. The paper concludes that story mapping is a useful creative process for extending young people's input into knowledge exchange and longer‐term research impacts. [ABSTRACT FROM AUTHOR]

Crisis management is a challenging and interdisciplinary task in which various information must be acquired and fused. In Germany, Civil Crisis Management is usually organized into two parts: the organizational‐administrative division and the operative‐tactical division, which are subordinate to the authorities (political) leadership. To organize an efficient and interdisciplinary response, crisis staffs can be called up. In these administrative crisis staffs, information sources are bundled, responsible experts collaborate and exchange information. To achieve a common understanding of the crisis, situational displays are created. Situational displays present the extend of the crisis and offer high‐level information required by the staff members. They can show the extent of the crisis area on maps or integrate other, for example numeric, information. This paper presents both state of the art in situational display creation and the most recent requirements in administrative crisis management. Data were collected through structured questionnaires and workshops regarding the tools for the creation of situational displays. For both data gathering methods, we were able to acquire active crisis management experts as participants. To determine the state of the art for situational displays for administrative crisis management staff we utilized structured questionnaires, which were answered by 14 crisis management authorities. Through two expert workshops with each nine participants, the requirements for situational display were collected. This paper compares the two datasets to evaluate the recent state of situational displays for administrative crisis staff in practice. The article summarizes usage of situational displays by practitioners and compiles lessons from the field. [ABSTRACT FROM AUTHOR]

To address the IoT security problem, in this paper we propose and evaluate the DDoS attack mitigation method based on blockchain, and construct a DDoS abnormal information detection and sharing model. The obtained experimental results show that when the number of decision trees increases, the training time of the DDoS attack detection model based on the RF model grows with a minimum trend of 14 s. The testing time is finally maintained at 1 s, and the recognition accuracy of DDoS attacks keeps improving, ultimately reaching over 99.8%. If the amount of DDoS abnormal traffic information exceeds 100 pieces and 2000 pieces, it only takes 0.1 and 5 s to sign the DDoS abnormal traffic information using ECDSA algorithm digitally. The signature verification only takes 0.1 and 9 s, respectively. And compared to conventional network physical system IoT security architecture, a network physical system IoT security architecture that integrates AI empowerment, blockchain, and SDN integration has a higher joint defense success rate. It can be explained that this scheme will be conducive to promoting joint defense against DDoS attacks and ensuring the security of the Internet of Things. [ABSTRACT FROM AUTHOR]

The paper by M. Finkelstein and J.H. Cha (named hereafter the FC paper) is entitled I Virtual age, is it real? As explained in Reference 6, other models that can be considered as virtual age models, such as the Geometric Process7 or Quasi-Renewal model,8 overcome this difficulty. Therefore, the age correspondence model seems to be closer to an Accelerated failure Time model (AFT) than to a virtual age model. 13 Brenière L, Doyen L, Bérenguer C. Virtual age models with time-dependent covariates: a framework for simulation, parametric inference and quality of estimation. [Extracted from the article]

The European Bioeconomy Strategy aims to facilitate the transition from a take--make--dispose fossil economy into one fostering circular bio-based value chains linking sustainable land use with cutting- edge products. Optimized designs, implementation and monitoring rely on continuous interactions between policymakers and modellers who run multiple scenarios for environmentally, economically and socially desirable futures. This paper leverages a multi-layered framework that cross-references 39 policies and 32 models to assess how they address the five principle objectives of the Bioeconomy Strategy in terms of accompanying sectors, value chains and multi-dimensional indicators. The framework identifies gaps in bioeconomy knowledge both in policy and modelling. Overall, the analysis found little mention of the wide range of bio-based products, technologies and processes, bio-refineries, waste and land conservation. Bio-based product policies can be simulated only in a limited number of models, compared, for example, to the wide range of modelling capacities that can model bioenergy. Additionally, in both policy and modelling realms, integration of market and biophysical drivers within the full scope of the value chain is scarce. Multidisciplinary studies combining multiple models perform best in this respect by integrating a more comprehensive range of relevant policies, bioeconomy drivers and indicators. Findings point to a more significant issue in policy-modelling information exchange, and this paper discusses the challenges and opportunities for future improvements in this collaboration. [ABSTRACT FROM AUTHOR]

Exome sequencing (ES) enhanced the diagnostic yield of genetic testing, but has also increased the possibility of uncertain findings. Prenatal ES is increasingly being offered after a fetal abnormality is detected through ultrasound. It is important to know how to handle uncertainty in this particularly stressful period. This systematic review aimed to provide a comprehensive overview of guidelines available for addressing uncertainty related to prenatal chromosomal microarray (CMA) and ES. Ten uncertainty types associated with prenatal ES and CMA were identified and defined by an international multidisciplinary team. Medline (all) and Embase were systematically searched. Laboratory scientists, clinical geneticists, psychologists, and a fetal medicine specialist screened the papers and performed the data extraction. Nineteen papers were included. Recommendations generally emphasized the importance of trio analysis, clinical information, data sharing, validation and re‐analysis, protocols, multidisciplinary teams, genetic counselling, whether to limit the possible scope of results, and when to report particular findings. This systematic review helps provide a vocabulary for uncertainties, and a compass to navigate uncertainties. Prenatal CMA and ES guidelines provide a strong starting point for determining how to handle uncertainty. Gaps in guidelines and recommendations were identified and discussed to provide direction for future research and policy making. [ABSTRACT FROM AUTHOR]

It is challenging for a single development subject to complete complex scientific research tasks due to the peculiarities of saline–alkali land. Collaborative innovation and cooperation can help break through the common critical technology R&D problems in the development process by sharing information, technology, knowledge, and resources. However, the process of saline–alkali land development in China is slow and the transformation rate of research results is low. Few articles analyze the current situation and driving mechanism of the collaborative innovation network for saline–alkali land development from the perspective of the innovation chain. This paper first constructs an undirected weighted collaborative innovation network from the upstream, midstream, and downstream levels of technological innovation for saline–alkali land development, analyzing the network's structural characteristics and spatial distribution features. Then uses ERGM to explore the internal and external driving mechanism for network formation from network self‐organization, subject characteristics, and exogenous environmental factors. The results demonstrate that the distribution of the collaborative innovation network is relatively uniform. However, there are also clusters, and the clusters are mostly centered on universities and scientific research institutions. Both the development subjects and clusters present regional features. Centrality and transitivity are crucial to the internal driving mechanism. In the external driving mechanism, the Matthew effect is modest, and the homogeneity effect is considerable; Organizational and technical proximity play a positive role; Geographical and institutional proximity play a blocking role. This study also provides practical enlightenment for encouraging horizontal and vertical collaborative innovation of sustainable development of saline–alkali land. [ABSTRACT FROM AUTHOR]

This paper collects 103 sample firms' 2015 to 2019 data through data envelopment analysis to measure their technical innovation performance and social network analysis to build joint‐patent networks and explore knowledge‐creating alliance relationships. The article highlights how tacit knowledge recombination works as a mechanism of boundary spanning. It emphasizes the significance of strategic balancing networks' position to improve technical innovation performance and competitiveness of patent‐intensive (PI) firms. This research contributes to shedding additional light on the nature of the boundary‐spanning mechanism and PI firms' knowledge exchanges. Specifically, it examines how balancing boundaries spanning through joint‐patent networks can influence the processes of tacit knowledge transmission and recombination between knowledge‐based actors. [ABSTRACT FROM AUTHOR]

Knowledge and experience are gained during the execution of every project. This knowledge remains in the heads of the engineers, but often is not distributed more widely. In Model‐Based Systems Engineering (MBSE) projects, this knowledge can include problem solving techniques, algorithms, libraries of types, patterns, interfaces, components, etc. One of the ways to preserve this knowledge is by creating libraries of these reusable assets. For example, the newest version of Unified Architecture Framework (UAF) included a library developed by Mitre of 1200 different security controls defined in National Institute of Standards and Technology (NIST) standard 800‐53r5. These controls can be referenced on projects to mitigate many common security risks. Each defined control can be integrated with the corresponding risks, security metrics, mitigating elements, solutions, and so forth. All these elements could then be used to construct Security Patterns showing risks that the security controls can mitigate as well as abstract solutions that can satisfy these controls. Patterns publicly provided as a curated, searchable, solution set library could be leveraged by projects and augmented over time, preserving their Intellectual Property (IP) and knowledge assets. This paper discusses these concepts and methods and demonstrates how they can be applied to improve system security. [ABSTRACT FROM AUTHOR]

Open data sharing democratizes science by making data more equitably available throughout the world. Furthermore, open data sharing improves the reproducibility and quality of research and enables new collaborations powered by the freely available data. Open data are defined as data that can be freely used, reused, and redistributed by anyone. For an interdisciplinary field like biological anthropology, data sharing is critical since one person cannot easily collect data across the domains relevant to our field. The goal of this paper is to encourage broader data sharing in our discipline by exploring the state of data sharing in the field of biological anthropology. Our paper is divided into four parts: the first section describes the benefits, challenges, and emerging solutions to open data sharing; the second section presents the results of our data archiving and sharing survey that was completed by over 700 researchers; the third section presents personal experiences of data sharing by the authors; and the fourth section discusses the strengths of different types of data repositories and provides a list of recommended data repositories. [ABSTRACT FROM AUTHOR]

Summary: The Internet of Things (IoT) has a significant impact on our daily lives as applications, services, devices, and industries become more intelligent. Artificial intelligence (AI) is expected to significantly influence machine learning training on IoT devices without data sharing. Federated learning (FL) is a distributed machine learning method used in many IoT smart devices; however, FL ensures IoT security and privacy. The systematic literature review (SLR) method is used in this paper to review recently published articles in the FL‐based IoT domain. We analyzed 39 papers that were published between 2018 and March 2022. According to the evaluation factors, the accuracy factor has a high percentage in the FL‐based IoT domain by 29%, and the epoch has 23%, the time has 18%, the energy consumption has 9%, the delay has 9%, the communication overhead has 6%, and the privacy has 6%. Finally, we discuss future research challenges and open issues in the context of FL‐based IoT. [ABSTRACT FROM AUTHOR]

In the era of 5G, billions of terminal devices achieve global interconnection and intercommunication, which leads to the generation of massive data. However, the existing cloud‐based data‐sharing mechanism faces challenges such as sensitive information leakage and data islands, which makes it difficult to achieve secure sharing across domains. In this paper, the authors propose a fine‐grained data‐sharing scheme based on blockchain and ciphertext policy attribute‐based encryption, and design a verifiable outsourced computation method to reduce the computational pressure of end users. Second, the authors comprehensively consider the user's identity privacy and transaction privacy, and propose a multi‐level privacy protection method based on ring signature and garbled bloom filter, which enhance the user's data privacy and availability, and prevent the traceability of requests. Finally, the authors design a set of interconnected smart contracts, and verify that their scheme can achieve secure and efficient data sharing through security analysis and performance testing. [ABSTRACT FROM AUTHOR]

Cable trees are primarily employed in industrial products to facilitate energy transfer and information exchange among various components. When utilizing machines for assembly, it is essential to convert the wiring plan into a sequence of cable insertion operations executed by the machine under various constraints. This poses a combinatorial optimization problem. In this domain, constraint programming (CP) solvers often exhibit outstanding performance by leveraging their robust problem‐modelling capabilities, excellent scalability, and precise solving capabilities. However, CP solvers may achieve various performances for different problem instances. Selecting the most suitable CP solver for each problem instance is crucial. This paper introduces an automatic selection algorithm for CP solvers to solve the cable tree wiring problem (CTW). Firstly, a scoring system is used to conduct an in‐depth analysis and compare four well‐known CP solvers: CPLEX, Chuffed, OR‐Tools, and Gurobi. The results indicate that OR‐Tools and CPLEX outperform other solvers in performance. Moreover, these two solvers exhibit complementary advantages in quickly finding optimal and feasible solutions within specified time limits. Therefore, CP and machine learning are ingeniously integrated, harnessing their complementary advantages. 4240 instances covering various scenarios are randomly generated to form the problem space. This method incorporates decision trees, random forests, K‐nearest neighbours, and naive Bayes, utilizing these four machine learning techniques. The proposed method can achieve better results than traditional single CP solvers. Among all the evaluated machining learning techniques, the automatic solver selection methods based on decision trees and random forests can achieve accuracy rates of 91.29% and 84.15%, respectively. [ABSTRACT FROM AUTHOR]

Summary: Recommender systems are important applications in big data analytics because accurate recommendation items or high‐valued suggestions can bring high profit to both commercial companies and customers. To make precise recommendations, a recommender system often needs large and fine‐grained data for training. In the current big data era, data often exists in the form of isolated islands, and it is difficult to integrate the data scattered due to privacy security concerns. Moreover, privacy laws and regulations make it harder to share data. Therefore, designing a privacy‐preserving recommender system is of paramount importance. Existing privacy‐preserving recommender system models mainly adapt cryptography approaches to achieve privacy preservation. However, cryptography approaches have heavy overhead when performing encryption and decryption operations and they lack a good level of flexibility. In this paper, we conduct privacy analysis on the existing locality sensitive hashing (LSH) approach based privacy‐preserving recommender system and show how an attacker can retrieve user's information under such a recommender system. Given such privacy risks, we propose differentially private LSH approach to build recommender system that can offer differential privacy guarantees for users. Our proposed efficient and scalable federated recommender system can make full use of multiple source data from different data owners while guaranteeing privacy preservation of users' data in contributing parties. Extensive experiments on real‐world benchmark datasets show that our approach can achieve both high time efficiency and accuracy under small privacy budgets. [ABSTRACT FROM AUTHOR]