Research In Field Research Articles

Digitalization for enhancing reading habits: the improved hybrid book recommendation system with genre-oriented profiles

PurposeReading habit plays a pivotal role in individuals' personal and academic growth, making it essential to encourage among campus users. University libraries serve as valuable platforms to promote reading by providing access to a diverse range of books and resources. Recommending books through personalized systems not only helps campus users discover new materials but also enhances their engagement and satisfaction with the library’s offerings, contributing to a holistic learning experience.Design/methodology/approachThis study presents a web-based solution, the Web-Based Hybrid Intelligent Book Recommender System (W_HybridBook), as a solution that addresses challenges like cold start issues and limited scalability by factoring in user preferences and item similarities in generating book recommendations. The paper improves the traditional hybrid system using Genre-Oriented Profiles (GOPs) instead of original rating profiles of users when determining similarities between individuals. Consumption-based genre profiles (W_HybridBook-CBP) are created by assessing whether an item has received any ratings in the dataset, and vote-based genre profiles (W_HybridBook-VBP) are generated by considering the genre categories based on the magnitude of the user’s rating.FindingsThe comparative results indicated that users are quite satisfied with the recommendations generated by W\\_HybridBook-VBP profiling, with an average rating of 4.0633 and a precision value of 0.7988. W\\_HybridBook-VBP is also the fastest way with respect to the algorithm and recommendation run time.Originality/valueThe proposed W\\_HybridBook has been then enhanced by adopting two user profiling strategies to boost the similarity calculation process in the recommendation generation phase. This system provides ranking-based recommendations by mainly integrating well-known collaborative and content-based filtering strategies. A dataset has been collected by considering the preferences of both users and academics at Izmir Bakircay University, which is one of the universities with the highest number of books per student. More importantly, this dataset has been released and become publicly available for future research in the recommender system field.

The sample locator: A federated search tool for biosamples and associated data in Europe using HL7 FHIR

BackgroundThis study outlines the development of a highly interoperable federated IT infrastructure for academic biobanks located at the major university hospital sites across Germany. High-quality biosamples linked to clinical data, stored in biobanks are essential for biomedical research. We aimed to facilitate the findability of these biosamples and their associated data. Networks of biobanks provide access to even larger pools of samples and data even from rare diseases and small disease subgroups. The German Biobank Alliance (GBA) established in 2017 under the umbrella of the German Biobank Node (GBN), has taken on the mission of a federated data discovery service to make biosamples and associated data available to researchers across Germany and Europe. MethodsIn this context, we identified the requirements of researchers seeking human biosamples from biobanks and the needs of biobanks for data sovereignty over their samples and data in conjunction with the sample donor's consent. Based on this, we developed a highly interoperable federated IT infrastructure using standards such as Fast Healthcare Interoperability Resources (HL7 FHIR) and Clinical Quality Language (CQL). ResultsThe infrastructure comprises two major components enabling federated real-time access to biosample metadata, allowing privacy-compliant queries and subsequent project requests. It has been in use since 2019, connecting 16 German academic biobanks, with additional European biobanks joining. In production since 2019 it has run 4941 queries over the span of one year on more than 900,000 biosamples collected from more than 170,000 donors. ConclusionThis infrastructure enhances the visibility and accessibility of biosamples for research, addressing the growing demand for human biosamples and associated data in research. It also underscores the need for improvements in processes beyond IT infrastructure, aiming to advance biomedical research and similar infrastructure development in other fields.

Greening the production of polymeric submicron particles by membrane-based manufacturing processes: A comparative analysis

The production of polymeric particles is the subject of extensive research in various fields and the interest in this area extends to the development of new sustainable production processes. The use of membrane technology has enabled the redesign of many traditional production processes with enormous impact in terms of product quality, reduction of energy consumption, high efficiency, productivity and reproducibility. In the present work, two alternative methodologies for the production of polycaprolactone (PCL) particles based on the use of membrane processes were investigated: i) membrane emulsification (ME) combined with solvent diffusion and ii) membrane nanoprecipitation (MN). ME/solvent diffusion is a widely applied technique for the production of microparticles, but its use for nanosized particles is still limited. On the other hand, MN is currently being investigated for its potentiality in the production of nanoparticles.In the present work, the performance of the two processes is compared in terms of: i) product quality (highly monodisperse particles in the nanometers range of size, ii) maximum productivity (expressed as mass of particles produced over time) under mild operating conditions (reduced mechanical stress), iii) environmental impact (assessed on the basis of the metrics established by the Green Aspiration Level (GAL)).

Assessing Assembly Errors in Immunoglobulin Loci: A Comprehensive Evaluation of Long-read Genome Assemblies Across Vertebrates.

Long-read sequencing technologies have revolutionized genome assembly producing near-complete chromosome assemblies for numerous organisms, which are invaluable to research in many fields. However, regions with complex repetitive structure continue to represent a challenge for genome assembly algorithms, particularly in areas with high heterozygosity. Robust and comprehensive solutions for the assessment of assembly accuracy and completeness in these regions do not exist. In this study we focus on the assembly of biomedically important antibody-encoding immunoglobulin (IG) loci, which are characterized by complex duplications and repeat structures. High-quality full-length assemblies for these loci are critical for resolving haplotype-level annotations of IG genes, without which, functional and evolutionary studies of antibody immunity across vertebrates are not tractable. To address these challenges, we developed a pipeline, "CloseRead", that generates multiple assembly verification metrics for analysis and visualization. These metrics expand upon those of existing quality assessment tools and specifically target complex and highly heterozygous regions. Using CloseRead, we systematically assessed the accuracy and completeness of IG loci in publicly available assemblies of 74 vertebrate species, identifying problematic regions. We also demonstrated that inspecting assembly graphs for problematic regions can both identify the root cause of assembly errors and illuminate solutions for improving erroneous assemblies. For a subset of species, we were able to correct assembly errors through targeted reassembly. Together, our analysis demonstrated the utility of assembly assessment in improving the completeness and accuracy of IG loci across species.

Quantitative Analysis of Aeolian Sand Provenance: A Comprehensive Analysis in the Otindag Dune Field, Central Inner Mongolia, China

The identification and quantification of aeolian sand contributions are essential for understanding the formation of dune fields and mechanisms of modern surface processes. In the present study, we take aeolian sand in the Otindag dune field (hereafter, often referred to as, simply, Otindag) as the research object. The dune field’s immediate source is quantitatively identified based on heavy minerals and the Conservativeness Index (CI), Consensus Ranking (CR), and the Consistent Tracer Selection (CTS) method. The primary source area of the aeolian sand was found to be from the northwestern, upwind area of the Otindag (59 ± 14%), followed by the Yinshan Mountain (17 ± 10%) and the lake basin (23 ± 12%). The proposed sediment transport model elucidates that sediments from the upwind of the Otindag are directly transported from the northwest to the Otindag, where they are deposited. Materials from the southern Yinshan Mountains are carried by rivers to the southern edge of the Otindag, where they are subsequently transported by wind and ultimately deposited. The lake deposits within the Otindag also contribute to the aeolian sand supply under the influence of wind. This study demonstrates that the fingerprinting techniques of CI, CR, and CTS serve as successful strategies for conducting quantitative provenance research in dune fields.

The link between gut microbiome and Alzheimer's disease: From the perspective of new revised criteria for diagnosis and staging of Alzheimer's disease.

Over the past decades, accumulating evidence suggests that the gut microbiome exerts a key role in Alzheimer's disease (AD). The Alzheimer's Association Workgroup is updating the diagnostic criteria for AD, which changed the profiles and categorization of biomarkers from "AT(N)" to "ATNIVS." Previously, most of studies focus on the correlation between the gut microbiome and amyloid beta deposition ("A"), the initial AD pathological feature triggering the "downstream" tauopathy and neurodegeneration. However, limited research investigated the interactions between the gut microbiome and other AD pathogenesis ("TNIVS"). In this review, we summarize current findings of the gut microbial characteristics in the whole spectrum of AD. Then, we describe the association of the gut microbiome with updated biomarker categories of AD pathogenesis. In addition, we outline the gut microbiome-related therapeutic strategies for AD. Finally, we discuss current key issues of the gut microbiome research in the AD field and future research directions. HIGHLIGHTS: The new revised criteria for Alzheimer's disease (AD) proposed by the Alzheimer's Association Workgroup have updated the profiles and categorization of biomarkers from "AT(N)" to "ATNIVS." The associations of the gut microbiome with updated biomarker categories of AD pathogenesis are described. Current findings of the gut microbial characteristics in the whole spectrum of AD are summarized. Therapeutic strategies for AD based on the gut microbiome are proposed.

Preface

It is a pleasure to welcome you to the 2024 International Symposium on New Energy Technologies and Power Systems (NETPS 2024). At this dynamic and innovative time, we were honored to have invite academic elites from all over the world to discuss the latest advances and cutting-edge research in new energy technologies and power systems. NETPS 2024 was held in Nanjing, China from March 22nd to 24th 2024 (virtual event). It focused on cutting-edge issues in new energy technologies and power systems, and provided a platform for academics to share knowledge, exchange views and promote collaboration. To make the program more informative and colorful, the Conference invited renowned scholars and experts from around the world, who brought us a series of fascinating thematic presentations. These reports covered multiple aspects of new energy technologies and power systems, including but not limited to hot topics such as New Energy Power Generation, Power System Communication and Control, Intelligent Energy Information Support Technology, Computational Intelligence in Electrical Engineering, Smart Grid, Big Data in Power Systems, etc. Experts and scholars including Prof. Ting Yang (Tianjin University, China), Prof. Pierluigi Siano (University of Salerno, Italy), Prof. Mohan Lal Kolhe, University of Agder (Norway), Norway, etc. performed dramatic presentations on their own researches. We believe that these reports have provided participants with both insight and inspiration, and promoted research and development in related fields. In addition, it featured oral presentations and poster presentations, providing an opportunity for graduate students and young researchers to present their research findings. It was an important platform for participants to exchange and interact with each other, helping to share experiences, promote cooperation and build new partnerships. We believe that through the interaction and cooperation in this Conference, we have deepened our understanding of relevant fields, promoted interdisciplinary integration, and provided new solutions to the complex problems facing the world today. Finally, we believe that the Proceedings of this Conference will be of great significance to the academic community. This Proceedings features outstanding papers from NETPS 2024, which represents the latest research results and innovative ideas in the fields. By publishing and sharing these papers, we are able to further expand the impact of our research, promote communication and collaboration among the academic community, and provide valuable references for future research. We would like to acknowledge all those who supported and participated in NETPS 2024. We look forward to have your active participation in the future series conference of NETPS! The Committee of NETPS 2024 List of Committee Member is available in this Pdf.

A Visual Analytics Conceptual Framework for Explorable and Steerable Partial Dependence Analysis.

Machine learning techniques are a driving force for research in various fields, from credit card fraud detection to stock analysis. Recently, a growing interest in increasing human involvement has emerged, with the primary goal of improving the interpretability of machine learning models. Among different techniques, Partial Dependence Plots (PDP) represent one of the main model-agnostic approaches for interpreting how the features influence the prediction of a machine learning model. However, its limitations (i.e., visual interpretation, aggregation of heterogeneous effects, inaccuracy, and computability) could complicate or misdirect the analysis. Moreover, the resulting combinatorial space can be challenging to explore both computationally and cognitively when analyzing the effects of more features at the same time. This article proposes a conceptual framework that enables effective analysis workflows, mitigating state-of-the-art limitations. The proposed framework allows for exploring and refining computed partial dependences, observing incrementally accurate results, and steering the computation of new partial dependences on user-selected subspaces of the combinatorial and intractable space. With this approach, the user can save both computational and cognitive costs, in contrast with the standard monolithic approach that computes all the possible combinations of features on all their domains in batch. The framework is the result of a careful design process involving experts' knowledge during its validation and informed the development of a prototype, W4SP1, that demonstrates its applicability traversing its different paths. A case study shows the advantages of the proposed approach.

Preface

The 2024 4th International Conference on Advanced Materials and Mechatronics (ICAMM 2024) was held via virtual form in Xi’an, China from May 10th to 12th, 2024. Previous conferences in the past three years of this series have been successfully held and it was agreed to hold the conference once a year, with the aim to establish and develop a constant international collaboration. In recent years, interest in advanced materials and mechatronics has been flourishing all over the globe due to both theoretical and practical requirements. Considering the trend, the fourth conference of ICAMM series was organized in order to provide an international academic forum for developing research cooperation and to promote research and other academic activities in related fields. We entertained about 80 participants at ICAMM 2024 and arranged various speeches and presentations which cover a wide range of topics related to the Conference theme. Many scholars and researchers all over the world have contributed to the emerging technology and application of advanced materials and mechatronics. The wonderful keynote speeches included Semiconductor Lighting and Display: Design and Manufacturing Technology for High Efficiency GaN-based LED Chips (by Prof. Shengjun Zhou, Wuhan University, China), Materials, Processing and Reliability of Low Temperature Bonding in 3D Chip Stacking (by Prof. Liang Zhang, Xiamen University of Technology, China), Monitoring Applications of Electronic Devices in the Shipbuilding Industry (by Assoc. Prof. Fengming Du, Dalian Maritime University, China), and Addictive Manufacturing and Intelligent Processing Control of Advanced Metal Materials (by Prof. Kun Li, Chongqing University, China). ICAMM 2024 has been endorsed and supported by many national and international engineering-related universities and organizations and was a complete success. The topics of papers collected and undergone rigorous peer review in the Proceedings of ICAMM 2024 can be classified as follows: Semiconductor Materials, Mechanics of Materials, Material Forming Process and Equipment, Advanced Electromagnetism, Laser Physics and Technology, Irradiation electronics, etc. Last but not the least is our gratitude. We would like to express our sincere thanks to all the keynote speakers, authors, committee members for the success of the Conference, which has given rise to this present volume of selected papers. We would also like to acknowledge the staff of Journal of Physics: Conference Series for their effective work to make this Proceedings published. The Committee of ICAMM 2024 List of Committee Member is available in this Pdf.

The impact of accounting conservatism on enterprise innovation investment

This study investigates the influence of accounting conservatism on corporate innovation investment through the lens of information asymmetry theory. While existing literature acknowledges the importance of accounting conservatism in corporate decision-making, there remains a gap in understanding how it specifically affects innovation investment, particularly in varied market environments and regulatory contexts. Specifically, current research often overlooks the heterogeneity of the impact of accounting conservatism on innovation investment under different market environments and regulatory frameworks. Additionally, there is a lack of specialized studies on the unique group of Chinese listed companies. This study fills this gap by empirically analyzing data from Chinese A-share listed companies, revealing a negative correlation between accounting conservatism and corporate innovation investment. Through empirical analysis of the financial reports and research and development (R&D) investment data of Chinese A-share listed companies from 2015 to 2022, this study finds a significant negative correlation between accounting conservatism and corporate innovation investment. Specifically, as accounting conservatism increases, corporate investment in R&D shows a decreasing trend, with a correlation coefficient of −0.364. This result is further validated by hierarchical regression analysis, where the regression coefficient is −0.465, indicating that accounting conservatism has a significant inhibitory effect on corporate innovation investment. This study is pioneering in its examination of the relationship between accounting conservatism and corporate innovation investment within the unique market environment of China, taking into account its distinctive characteristics and rapidly evolving technological industry background. To quantify accounting conservatism, the research employs the C-Score and G-Score models, while employing a range of indicators to measure corporate innovation investment, including proportions of R&D expenditure, number of new products or services, patent applications, total R&D personnel, capital investments, and progress in innovation projects. This comprehensive evaluation method enhances the accuracy and reliability of the study. The contribution of this study is significant as it offers a fresh perspective on how accounting conservatism influences corporate innovation investment. By providing empirical data support, it assists investors and corporate managers in making informed financial decisions and shaping innovation strategies. Through hierarchical regression analysis, the study substantiates the detrimental impact of accounting conservatism on corporate innovation investment, thereby establishing new theoretical and practical foundations for further research and application in related fields.

What's the Situation With Intelligent Mesh Generation: A Survey and Perspectives.

Intelligent Mesh Generation (IMG) represents a novel and promising field of research, utilizing machine learning techniques to generate meshes. Despite its relative infancy, IMG has significantly broadened the adaptability and practicality of mesh generation techniques, delivering numerous breakthroughs and unveiling potential future pathways. However, a noticeable void exists in the contemporary literature concerning comprehensive surveys of IMG methods. This paper endeavors to fill this gap by providing a systematic and thorough survey of the current IMG landscape. With a focus on 113 preliminary IMG methods, we undertake a meticulous analysis from various angles, encompassing core algorithm techniques and their application scope, agent learning objectives, data types, targeted challenges, as well as advantages and limitations. We have curated and categorized the literature, proposing three unique taxonomies based on key techniques, output mesh unit elements, and relevant input data types. This paper also underscores several promising future research directions and challenges in IMG.

Enhancing the Meaning of Psychological Research Through Trend Research and Research Registries

The relentless development of research in various fields of science, including psychology, has the potential to cause redundancy and reduce relevance. To overcome this, the discourse and efforts of Trend Research and Research Registries were developed. The integration of Trend Research and Research Registry is expected to be implemented and utilized by researchers in the field of science, to not only maintain the quality of research conducted, but to further improve the quality so that it can be more meaningful.

Overview on Application of Operation Research in Various fields

Abstract: In any area of human endeavour, whether it is a production system, business system or service system where an objective is to be optimized. Operation research as coined by Europeans or operations Research by Americans is relatively a new discipline that deals with the application of analytical methods to gain a better decision. Operation research finds a solution to a problem is by breaking down the problem into basic components and then solving it in defined steps by mathematical analysis.

A Neurophysical Hypothesis on the Role of the Intensity of the Electromagnetic Field Generated by the Cerebral Hemispheres in the Determination of Laterality, in Line with Einstein's Unified Field Theory

Abstract Objective: Traditional models of cerebral laterality, focusing primarily on anatomical and functional asymmetries, fall short of explaining the underlying physical dynamics. This study pioneers a novel perspective by hypothesizing that the intensity of the electromagnetic field generated by the cerebral hemispheres plays a crucial role in determining laterality. Inspired by Einstein's unified field theory, we explore this hypothesis through an interdisciplinary approach that merges principles of physics with neurophysiology. Material and Methods: Our research employed an innovative experimental design involving three groups of male Wistar albino rats categorized based on handedness: right-handed, left-handed, and ambidextrous. We utilized electroencephalography (EEG) to measure the electromagnetic field intensity of the cerebral hemispheres, analyzing the data through a lens that combines traditional neuroscientific methods with concepts adapted from field theory. Results: The findings reveal a significant correlation between the intensity of the electromagnetic field in the dominant hemisphere and handedness, with dominant hemispheres displaying higher field intensities. Notably, ambidextrous rats exhibited no significant difference in field intensity between hemispheres, underscoring the potential influence of electromagnetic fields on hemispheric dominance. Conclusion: This study's implications suggest a radical rethinking of how cerebral functions might be influenced by electromagnetic phenomena. The integration of Einstein's unified field theory into the study of cerebral laterality opens new pathways for research. Our findings advocate for a broader, more integrated understanding of brain functionality, highlighting the need for further interdisciplinary research in this nascent field.

ADVANCEMENTS IN DEFLUORIDATION TECHNOLOGIES FOR SAFE DRINKING WATER: A COMPREHENSIVE REVIEW

Higher fluoride concentrations in groundwater have been reported in more than 20 developed and developing countries.In the quest for ensuring safe drinking water, the removal of fluoride has emerged as a critical concern globally. This comprehensive review paper delves into the realm of defluoridation technologies, exploring a myriad of methods employed to mitigate excess fluoride levels in water sources. By meticulously examining traditional techniques alongside cutting-edge advancements, this paper provides a detailed analysis of the evolution of defluoridation technologies. From adsorption processes to membrane technologies and electrocoagulation methods, diverse array of approaches are scrutinized for their efficacy in addressing the pressing issue of fluorosis. Through a systematic evaluation of the strengths and limitations of each technology, this review aims to offer valuable insights into the current landscape of defluoridation methodologies. By synthesizing existing knowledge with recent innovations, this paper highlights the progress made in combating fluoride contamination and also underscores the ongoing need for continuous research and development in this crucial field. It has been concluded that the selection of treatment process should be site-specific as per local needs and prevailing conditions as each technology has some limitations and no one process can serve the purpose in diverse conditions.

Research on Visual Design of Smart Phone APP Interface Based on Human-Computer Interaction Behavior

This paper explores the application and influence of human-computer interaction behaviours in the visual design of smartphone APP interfaces. This paper firstly analyses the user's behavioural characteristics, interaction mode and optimization of the interaction process, and points out that the interface design should be closely integrated with the user's needs. Then the article puts forward the principles of smartphone app interface visual design, which provides a guiding framework for designers. In elaborating the design elements, the importance of colour, icon and text in interface design is emphasized, and the corresponding design principles and methods are proposed. The article concludes with a summary of the research results pointing out the problems and shortcomings, and looking forward to the future development trends and directions. This article aims to improve the user experience rate and interaction efficiency of smartphone APP interface design, and provide useful references for research and practice in related fields.

Consideration of natural scientific background in Russia’s climate policy

Aim. Based on normative acts to reveal the key importance of the domestic scientific background in the implementation of climate policy.Objectives. To characterize the historical experience of using scientific-balance calculations in the implementation of strategic planning, applied today in the process of climate policy implementation in the national economy; to consider the current trends in strategic management of climate policy, description of the system of key cross-sectoral documents of strategic planning, reflection of accounting for the implementation of the major innovative project of state importance (MIP SI) and federal scientific and technical program (FSTP) in the system of climate policy in Russia.Methods. The author used general scientific methods of theoretical research, including analysis, synthesis, deduction, induction, and presented a system of intersectoral documents of climate policy in the context of the need to ensure anti-sanctions resistance. The results of the implementation of MIP SI and FSTP in the system of documents of inter-sectoral strategic planning of climate policy in the Russian economy are investigated.Results. The article analyzes the system of key intersectoral strategic planning documents developed and approved for the implementation of climate policy. According to the approved acts, in the Russian economy are realized MIP SI and FSTP, which contribute to the aggregation and implementation of scientific developments necessary in the implementation of climate policy of the Russian Federation (RF). In addition, the connection of the relevant documents with the documents of intersectoral (including technological) nature, which take into account not only the implementation of climate policy, but also the need to form technological sovereignty in connection with the sanctions restrictions imposed on the Russian economy. It is shown that state-level projects implemented in connection with the climate agenda can form a domestic foundation that will provide a promising scientific calculations and developments aimed at the realization of low-carbon development of the domestic economy.Conclusions. The low-carbon economic development strategy developed on the basis of the input-output methodology (inter-sectoral balance), the approved state program to reduce the carbon intensity of the Russian economy, as well as the updated Climate Doctrine are the key intersectoral documents of climate policy, which take into account relevant scientific research, including in the natural-science plane. Aggregation of the results of the implementation of the MIP SI and FSTP will allow taking into account the advanced achievements of domestic research in the climate field, which will further ensure a more balanced implementation of the state climate policy in the long term, including in the context of the need to form and ensure technological sovereignty. This in the long term can positively affect the sustainable improvement of welfare in the country.

How Do Combustions Actuate High-Speed Soft Robots?

The combustion actuation method opens a unique pathway for high-performance soft robots, allowing for high accelerations in multifunctional applications. Along with multifunctionality come great challenges in effective robot structure design, accurate control and prediction of combustion-actuated motions, and practical implementation of various applications. However, research in this nascent field remains fragmented, lacking central guiding principles. To systematize these works, this review article summarizes state-of-the-art technologies in combustion-actuated soft robots, addressing three key questions: How to design a combustion-enabled soft robot? How to predict its movements and control it? and How to practically apply it.

Comparative Analysis and Regeneration Strategies for Three Types of Cartilage.

Cartilage tissue, encompassing hyaline cartilage, fibrocartilage, and elastic cartilage, plays a pivotal role in the human body because of its unique composition, structure, and biomechanical properties. However, the inherent avascularity and limited regenerative capacity of cartilage present significant challenges to its healing following injury. This review provides a comprehensive analysis of the current state of cartilage tissue engineering, focusing on the critical components of cell sources, scaffolds, and growth factors tailored to the regeneration of each cartilage type. We explore the similarities and differences in the composition, structure, and biomechanical properties of the three cartilage types and their implications for tissue engineering. A significant emphasis is placed on innovative strategies for cartilage regeneration, including the potential for in situ transformation of cartilage types through microenvironmental manipulation, which may offer novel avenues for repair and rehabilitation. The review underscores the necessity of a nuanced approach to cartilage tissue engineering, recognizing the distinct requirements of each cartilage type while exploring the potential of transforming one cartilage type into another as a flexible and adaptive repair strategy. Through this detailed examination, we aim to broaden the understanding of cartilage tissue engineering and inspire further research and development in this promising field.

Semantic mapping techniques for indoor mobile robots: Review and prospect

With the continuous development of robotics and computer vision technology, mobile robots have been widely applied in various fields. In this process, semantic maps for robots have attracted considerable attention because they provide a comprehensive and anthropomorphic representation of the environment. On the one hand, semantic maps are a tool for robots to depict the environment, which can enhance the robot’s cognitive expression of space and build the communication bond between robots and humans. On the other hand, semantic maps contain spatial location and semantic properties of entities, which helps robots realize intelligent decision-making in human-centered indoor environments. In this paper, we review the primary approaches of semantic mapping proposed over the last few decades, and group them according to the type of information used to extract semantics. First, we give a formal definition of semantic map and describe the techniques of semantic extraction. Then, the characteristics of different solutions are comprehensively analyzed from different perspectives. Finally, the open issues and future trends regarding semantic maps are discussed in detail. We wish this review provides a comprehensive reference for researchers to drive future research in related field.