Library Retrieval Research Articles

HOW TO IMPACT WITH LIBRARY AND LIBRARIANSHIP INFORMATION RETRIEVAL & KNOWLEDGE

The impact of information retrieval and knowledge management in library and librarianship has evolved significantly with the advent of digital technologies and modern information systems. This study investigates the key role that libraries and librarians play in enhancing information retrieval processes and knowledge dissemination in academic, research, and public settings. It highlights the transformation of libraries from traditional repositories of books to dynamic centers for knowledge access and creation. The paper explores how advancements in digital libraries, metadata management, and search algorithms have enabled more efficient retrieval of information, thus empowering researchers, students, and the public. Furthermore, the research examines the skills and evolving role of librarians as key facilitators of knowledge management, curating and guiding users through vast resources. Challenges such as the digital divide, limited resources, and the need for ongoing professional development are also considered. The study concludes with recommendations for the future of librarianship, emphasizing the importance of adopting emerging technologies and continuing to support open access initiatives for better knowledge sharing.

Diagnostic Potential of Complementation of MRI to Prenatal Ultrasound for Detecting Orofacial Clefts in High-Risk Fetuses: A Network Meta-Analysis.

To compare the complementation of magnetic resonance imaging (MRI) to prenatal ultrasound (US) with prenatal US alone in detecting orofacial clefts in high-risk fetuses. A network meta-analysis. Literature retrieval in PubMed, EMBASE, and Cochrane library, and meta-analysis based on STATA 14.0. Fetuses were at high-risk for orofacial clefts. Prenatal US and the complementation of MRI to prenatal US. The pooled sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), diagnostic odds ratio (DOR), and area under the curve (AUC). Thirteen studies involving 776 patients were included. Direct meta-analysis showed that the complementation of MRI to prenatal US did not differ from prenatal US in detecting orofacial clefts if the type of orofacial clefts was not distinguished. Subgroup analysis showed that the specificity of prenatal US for the detection of isolated cleft palate (CP) was lower than that of the complementation of MRI to prenatal US. Furthermore, network meta-analysis consistently suggested a comparable diagnostic value between prenatal US and the complementation of MRI to prenatal US. Moreover, subgroup analysis showed that the specificity of prenatal US was significantly lower than that of complementation of MRI to prenatal US for the detection of isolated CP. MRI is more accurate than ultrasound in detecting cleft palate. Therefore, MRI should be offered if there is a fetus with a possible or ultrasound diagnosis of cleft palate, especially if the evaluation of cleft palate is deemed unsatisfactory after careful evaluation of the images.

Analysis of Floral Fragrance Components in Different Parts of Iris typhifolia

Floral fragrance, as one of the evaluation indicators for ornamental plants, influences people’s perception of these plants. To explore the volatile compounds and their application value in different parts of Iris typhifolia and to investigate the contributions of each part to the floral aroma, an AIRSENSE electronic nose, principal component analysis (PCA), linear discriminant analysis (LDA), and loading analysis (Loading) are employed to study the differences in floral components among the various parts. Samples from the stamen, pistil, flag petal, and pendant petal are qualitatively and quantitatively analyzed using solid-phase microextraction (SPME) and gas chromatography–mass spectrometry (GC-MS) techniques, combined with spectral library retrieval, cluster analysis, and Odor Activity Value (OAV) calculation. The results show that the electronic nose significantly distinguished the aromas from different parts, and there are significant differences in aroma composition. Through cluster analysis and OAV calculation, it is found that the pistil makes the primary contribution to the floral profile of Iris typhifolia, due to the presence of caproaldehyde, 2-methoxy-3-sec-butylpyrazine, and abundant terpenes. This research provides a valuable reference for reconstructing the floral aroma profile, extracting bioactive substances, and exploring aromatherapy with Iris typhifolia.

IMDLIB: An open-source library for retrieval, processing and spatiotemporal exploratory assessments of gridded meteorological observation datasets over India

Addressing a pressing need for streamlined access to observed meteorological data in India, we present IMDLIB, an open-source Python library that operates on gridded datasets from the India Meteorological Department (IMD). IMDLIB simplifies the retrieval, management, and processing of IMD's rainfall, maximum and minimum temperature data at varying scales (point, regional, catchment, and country scales). IMDLIB stands out by directly interfacing with IMD's database through robust APIs, streamlining data acquisition. It offers transformation of IMD's binary data into common formats (e.g., NetCDF/GeoTIFF/CSV) and advanced analytics, including trend analysis, spatiotemporal data interpolation, calculation of meteorological indices and extreme characteristics, showcasing superior capabilities compared to traditional meteorological data processing tool available for the region. To underline its robustness, IMDLIB's application was illustrated in two distinct regions: Rajasthan State and the Godavari River Basin. Through IMDLIB, we envision enhanced data accessibility, leading to more insightful hydro-climatic research and analysis.

Network meta-analysis of comparative efficacy and safety of intubation devices in children

To evaluate the comparative efficacy and safety of different intubation devices on intubation outcomes in pediatric intubation. We identified relevant studies from previous meta-analyses and literature retrieval in PubMed, EMBASE, and Cochrane Library. The primary outcome was the first-pass success (FPS), and the secondary outcome included the time to intubation (TTI) and the risk of local complications (LC). Network meta-analysis was performed using STATA 14.0. Twenty-three randomized comparative trials (RCTs) including 12 devices were included. Compared with Macintosh, Airtraq (odds ratio [OR] = 13.05, 95% confidence interval [CI] = 4.68 to 36.38), Miller (OR = 4.77, 95%CI = 1.32 to 17.22), Glidescope (OR = 2.76, 95%CrI = 1.60 to 4.75) and McGrath (OR = 4.61, 95%CI = 1.18 to 17.99) obtained higher PFS. Meanwhile, Airtraq was superior to Glidescope (OR = 0.21, 95%CI = 0.07 to 0.65) for PFS. For TTI, Canada was superior to other intubation devices, as well as CMAC was superior to TruViewEVO2, Glidescope, and StorzDCI. Airtraq lowered the risk of LC compared with Macintosh and Pentax but there was no statistical difference between Airtraq and KingVision. Airtraq may be the optimal option for FPS, Canada for TTI, and KingVision for LC in pediatric intubation.

Fuzzy retrieval algorithm for film and television animation resource database based on deep neural network

The large amount of data in the film and television animation resource library leads to the increase of retrieval difficulty and the decrease of retrieval accuracy. Therefore, a fuzzy retrieval algorithm for film and television animation resource database based on deep neural network is designed. According to the structure of the film and television animation resource base and the static and dynamic characteristics of the color, texture and shape of the film and television animation, the deep neural network is used to supervise and learn the multi-layer neural network of the film and television animation and extract the characteristics of the film and television animation. The improved fuzzy C-means is used for feature clustering analysis. According to the results of feature clustering analysis, the fast sorting algorithm and Top-k sorting algorithm are used to obtain the retrieval results of the film and television animation resource library, and improve the retrieval accuracy of the film and television animation resource library. The experiment shows that using the 7th layer features of deep neural networks for animation resource retri of 90.15%. Therefore, this algorithm eval has the highest recall rate of 98% and the highest average precision rate meets the retrieval requirements of film and television animation resource libraries and can significantly improve the comprehensive performance of film and television animation resource library retrieval.

Characterization and identification of chemical components in traditional Chinese medicine Psoraleae Fructus based on UHPLC-Q-TOF-MS

This study was designed to comprehensively characterize and identify the chemical components in traditional Chinese medicine Psoraleae Fructus by establishing an ultra-high performance liquid chromatography/quadrupole time-of-flight mass spectrometry(UHPLC-Q-TOF-MS) method in combination with in-house library. The chromatographic separation conditions(stationary phase, column temperature, mobile phase, and elution gradient) and key MS monitoring parameters(capillary voltage, nozzle voltage, and fragmentor) were sequentially optimized via single-factor experiments. A BEH C_(18) column(2.1 mm×100 mm, 1.7 μm) was finally adopted, with the mobile phase consisting of 0.1% formic acid in water(A) and acetonitrile(B) at the flow rate of 0.4 mL·min~(-1) and column temperature of 30 ℃. Auto MS/MS was utilized for data acquisition in both positive and negative ion modes. By comparison with reference compounds, analysis of the MS~2 fragments, in-house library retrieval and literature research, 83 compounds were identified or tentatively characterized from Psoraleae Fructus, including 58 flavonoids, 11 coumarins, 4 terpenoid phenols, and 10 others. Sixteen of them were identified by comparison with reference compounds, and ten compounds may have not been reported from Psoraleae Fructus. This study achieved a rapid qualitative analysis on the chemical components in Psoraleae Fructus, which provided useful reference for elucidating its material basis and promoting the quality control.

Exploring applications of electron ionization mass spectrometry in dense embedding space

In this study, we investigate the conversion of electron ionization mass spectrometry (EI-MS) data into dense embedding space for various mass spectrometry tasks. We employ the Spec2Vec algorithm to transform the original mass spectral space into a low-dimensional dense embedding space to overcome the challenge of processing sparse mass spectra. To validate the effectiveness of the Spec2Vec space, we extend the focus of mass spectrometry studies beyond library retrieval by exploring two downstream tasks: molecular fingerprint prediction and cooperation with Neural Electron–Ionization Mass Spectrometry (NEIMS). Compared to the sparse mass spectral space, the Spec2Vec space can significantly improve identification performance, reduce time cost, and save computational resources. This study may inspire more research tasks in the embedding space for mass spectrometry.

Deep learning under mass-to-charge ratio pre-retrieval to realize electron ionization mass spectrometry library retrieval.

Gas chromatography-mass spectrometry (GC-MS) is an analytical technique widely used in materials science, biomedicine, and other fields. The target compound in the experiment is identified by searching for its mass spectrum in a large mass spectrum database using some algorithms. This work introduces the use of deep learning ranking for the identification of small molecules using low-resolution electron ionization MS. Because different spectra are often very similar, the algorithm produces wrong search results, and the search accuracy needs improvement. Due to the library's large amount of data, the algorithm sometimes requires a large amount of calculation and is very time consuming. Given these two problems, this work aims to develop a model for ranking based on mass-to-charge ratio (m/z) pre-retrieval method combined with deep learning to improve search accuracy and reduce the algorithm's computational time. The master spectral library maintained by the National Institute of Standards and Technology is used as the reference library for all the experiments, and the replicate library is used as the query library to evaluate the method's performance. Compared with non-machine learning algorithms, the combination of m/z matching pre-retrieval and deep learning significantly improves library retrieval accuracy by about 4%. Moreover, compared with the deep learning sorting algorithm that does not use the pre-retrieval process, it improves the accuracy of spectral library retrieval by about 0.1% and reduces the computational time of the algorithm by more than 2h. This method identifies compounds more efficiently and accurately than non-machine learning and deep learning algorithms without a pre-retrieval process.

Re_Trans: Combined Retrieval and Transformer Model for Source Code Summarization

Source code summarization (SCS) is a natural language description of source code functionality. It can help developers understand programs and maintain software efficiently. Retrieval-based methods generate SCS by reorganizing terms selected from source code or use SCS of similar code snippets. Generative methods generate SCS via attentional encoder–decoder architecture. However, a generative method can generate SCS for any code, but sometimes the accuracy is still far from expectation (due to the lack of numerous high-quality training sets). A retrieval-based method is considered to have a higher accurac, but usually fails to generate SCS for a source code in the absence of a similar candidate in the database. In order to effectively combine the advantages of retrieval-based methods and generative methods, we propose a new method: Re_Trans. For a given code, we first utilize the retrieval-based method to obtain its most similar code with regard to sematic and corresponding SCS (S_RM). Then, we input the given code and similar code into the trained discriminator. If the discriminator outputs onr, we take S_RM as the result; otherwise, we utilize the generate model, transformer, to generate the given code’ SCS. Particularly, we use AST-augmented (Syntax Tree) and code sequence-augmented information to make the source code semantic extraction more complete. Furthermore, we build a new SCS retrieval library through the public dataset. We evaluate our method on a dataset of 2.1 million Java code-comment pairs, and experimental results show improvement over the state-of-the-art (SOTA) benchmarks, which demonstrates the effectiveness and efficiency of our method.

Indigenous Cultural-Heritage Resource Management System: Designing an Open-Source Based Technical Framework

This paper reports the development of a digital indigenous or aboriginal cultural heritage archive prototype to understand more specifically how to manage cultural heritage resources for local needs, for traditional and indigenous communities, and in libraries, archives, and museums as they seek to manage, preserve, strengthen, develop, and reuse these resources. The tribes who are the earliest inhabitants of India are economically and socially the least advanced, as they live in isolated and self-contained groups, and are distinct culturally and ethnically from mainstream societies. Historically, colonization, ignorance of mainstream societies, etc., have dominated thousands of indigenous cultures that have ceased to exist or have been marginalized to the brink of extinction. This exploratory study is an attempt to find the tools and techniques that can assist in building an information system for indigenous culture. It considers the need for integration of such a system with a library retrieval system, and the prototype includes the indigenous cultural resources of the Rabha tribe of North-East India to illustrate the idea and suggest a prototype based on open source software and open standards.

Mechanism underlying the effect of Liujunzi decoction on advanced-stage non-small cell lung cancer in patients after first-line chemotherapy.

To further clarify the anticancer mechanisms of Liujunzi decoction and provide possible targets for the treatment of advanced-stage nonsmall cell lung cancer (NSCLC) by re-analyzing differential gene expression profile of peripheral blood mononuclear cells (PBMCs) from Liujunzi decoctiontreated NSCLC patients receiving first-line chemotherapy. The PBMC gene expression microarray data set GSE61926 was retrieved from a high throughput gene expression database. Differentially expressed genes (DEGs) were screened by paired sample t-test and the multiple ratio method. Gene ontology and Kyoto encyclopedia of genes and genomes (KEGG) pathway analyses were performed using the DAVID database. The protein-protein interaction (PPI) network was constructed using interaction gene library retrieval tools and Cytoscape software. A total of 162 DEGs were identified, with 67 upregulated genes and 95 downregulated genes. The functional distribution of Gene Oncology (GO) genes showed that DEGs were mostly concentrated in extracellular regions, calcium ion binding, and transcriptase activity. KEGG pathway analysis showed that cytokine-cytokine receptor interactions were significantly enriched. PPI network analysis screened out the top 10 central protein-coding genes with the highest nodal degree: IL2, PIWIL4, DICER1, PIWIL2, SAA1, XCL1, IL22RA1, ARHGAP11A, DCP1A, and GDNF. Among them, the central protein-coding gene with the highest node degree was IL2. In addition, the central protein-coding genes with high node degrees and high molecular complex detection (MCODE) scores were PIWIL4, DICER1, PIWIL2, and DCP1A, all of which are related to tumor development. One signaling pathway and 10 central protein-coding genes related to anticancer mechanisms were screened by re-analysis of GSE61926 data. IL2, PIWIL4, DICER1, PIWIL2, and DCP1A may have important roles in the mechanism of Liujunzi decoction treatment against NSCLC. Our results suggest that the anticancer mechanism of Liujunzi decoction may be related to gene silencing by RNA and the biological processes of piwi-interacting RNA and other small RNAs.

Rapid screening and identification of 62 kinds of illegally added traditional Chinese medicine in food by high performance liquid chromatography coupled with quadrupole-time of flight mass spectrometry

建立了高效液相色谱-四极杆-飞行时间质谱快速筛查鉴别食品中非法添加的62种中药材的方法。依据卫生部关于进一步规范保健食品原料管理的通知(卫法监发[2002]51号)中可用于保健食品的物品名单,确定食品中可能非法添加的62种中药材原料清单,再从62种中药材中筛选其特征组分,获得不同中药材对应的特征组分清单。62种对照药材经甲醇超声提取后,于Thermo Accucore aQ色谱柱(150 mm×2.1 mm, 2.6 μm)上分离,在电喷雾正负离子扫描模式下,分别以0.1%(v/v)甲酸水溶液-乙腈和水-乙腈为流动相梯度洗脱,进行一级质谱和二级质谱全扫描检测,采用Library View软件建立不同中药材对应的特征组分的一级精确质量数据库和二级碎片质谱库。样品同法处理后上样分析,采用Peak View软件将样品高分辨数据与自建数据库中的质谱图、精确分子离子质量数、碎片离子质量数、保留时间等相关参数进行快速筛查鉴别分析。该工作通过建立“中药材-特征组分”对应清单,构建了食品中易非法添加的62种中药材中共388种特征组分的高分辨质谱库,每种中药材包括5~10种特征组分,通过对实际食品样品配制酒、代用茶及饮料进行筛查分析,1批次配制酒样品与淫羊藿中药材的7种特征组分匹配一致,推断该配制酒样品中加入了淫羊藿中药材。该法可实现无标准品情况下中药材的定性筛查,具有高通量、准确、简便、快捷的特点,解决了食品中非法添加中药材难以识别和确证的难题,可以实现食品中非法添加中药材的快速筛查鉴别分析。

Fault Detection of Permanent Magnet Synchronous Motor Based on Image Content Retrieval

The motor fault detection based on data-driven approach has achieved some results. However, there are still some problems, such as complex signal processing, long training time and poor adaptability to different working conditions. A new fault detection method for permanent magnet synchronous motor based on image content retrieval is proposed in this paper, which does not require complex signal processing and model training, and has strong adaptability to conditions. First, the fault signals are converted into images by the symmetrized dot pattern method. Second, an image coding technology based on KAZE feature and bag of features is proposed to reduce the computational cost. Then, to improve adaptability of conditions, a cyclic update algorithm of image retrieval library based on image fusion is proposed. Finally, fault detection is realized through image retrieval of feature code matching. Extensive experiments demonstrate the superiority and effectiveness of the proposed method.

Serendipity in Library Retrieval: Reinforcing Discovery through Visualization of Bibliographic Relationships

This work starts with a background study of serendipity, its meaning in the context of information discovery, its interrelation with bibliographic relationships, and the technical possibilities for practical implementation of a relationships based visual navigation in a library discovery interface to achieve serendipitous resource discovery. The methodology for developing the prototype consists of two components – theoretical base and practical steps. The theoretical framework includes an indepth study of the concept of bibliographic relationships as proposed by experts, as reflected in bibliographic data models and as included in bibliographic formats and metadata schemas. The practical sides deal with the application of the theoretical framework in designing a prototype that, in addition to other typical retrieval features, supports visual navigational facility driven by bibliographic relationships. The components, tools and standards of the entire software architecture are all open source and open standards.

Identification of New Psychoactive Tryptamines 4-OH-MET and 4-AcO-DMT Using High Resolution Mass Spectrometry and Nuclear Magnetic Resonance Spectroscopy

Objective To detect the uncontrolled new psychoactive tryptamines involved in drug-related cases with high resolution mass spectrometry and nuclear magnetic resonance spectroscopy. Methods White and brown powder obtained in actual cases were extracted and analyzed by gas chromatography-quadrupole time-of-flight mass spectrometry （GC-QTOF-MS）, ultra-high performance liquid chromatography-linear ion trap quadrupole-orbitrap mass spectrometry （UPLC-LTQ-Orbitrap MS） and 1H-nuclear magnetic resonance spectroscopy （1H-NMR）. Results After detection by GC-QTOF-MS, the components of white powder showed main characteristic fragment ion peaks at m/z 218.141 0 （molecular ion peak）, 72.080 6 （base peak）, etc. After detection by UPLC-LTQ-Orbitrap MS, its protonated molecular ion was m/z 219.149 4. The main ions in the secondary mass spectrum under the collision-induced dissociation （CID） mode were m/z 160.076 3 and 72.080 8. After detection by GC-QTOF-MS, the components of brown powder showed main characteristic fragment ion peaks at m/z 246.135 7 （molecular ion peak）, 58.065 1 （base peak）, etc. After detection by UPLC-LTQ-Orbitrap MS, its protonated molecular ion was m/z 247.145 0. The main ions in the secondary mass spectrum under CID mode were m/z 202.087 1, 160.076 3 and 134.060 5. NIST 17 library retrieval and 1H-NMR confirmed that the white powder and brown powder contained new psychoactive tryptamines 4-OH-MET and 4-AcO-DMT, respectively. Conclusion GC-QTOF-MS, UPLC-LTQ-Orbitrap MS and 1H-NMR can be used together to identify unknown new psychoactive substances.

Efektivitas Sistem Temu Kembali Informasi Perpustakaan Digital Institut Seni Indonesia (ISI) Yogyakarta dalam Tinjauan Recall dan Precision

Today's digital library is a necessity. A system that provides all-digital information and services requires that all aspects of it should be accessed effectively. In the context of information retrieval in digital libraries, the information retrieval systems are important instruments. The system becomes a link between relevant information and its users. Evaluation of the information retrieval system to determine its effectiveness is important to ensure that users receive good retrieval services. Recall and precision are approaches to measure the effectiveness of information retrieval systems that are widely used. This study aims to determine the effectiveness of the ISI Yogyakarta digital library retrieval system based on recall and precision approaches. This study will provide benefits for librarians in knowing the effectiveness of the information retrieval system and the extent of their accuracy in indexing. This research uses an experimental method with a quantitative approach. The researcher chose a sample of the searching keywords purposively and then tested them by searching on the portal http://digilib.isi.ac.id/. The data obtained were analyzed using the formula recall and precision. In this study the subjects tested were interior design subjects. The precision measurement of 10 keywords on the subject of interior design gets 92.37% results while the recall measurement gets 80.79% results. The result stated that precision is higher than recall, it showed that the information retrieval system of ISI Yogyakarta’s digital library is quite effective.

Analysis of the Volatile Components in Flowers of <i>Paeonia lactiflora</i> Pall. and <i>Paeonia lactiflora</i> Pall. var. <i>Trichocarpa</i>

Paeonia lactiflora Pall. var. trichocarpa is a variety of Paeonia lactiflora Pall., and is currently the peony herb’s principal cultivar group. Here, we study the differences in aromatic components and flowers of different varieties between two groups of cultivars, providing a reference for applying natural fragrance substances of peonies, breeding fragrant flower types, and developing and using improved varieties. Headspace solid-phase microextraction (HS-SPME), gas chromatography-mass spectrometry (GC-MS), peak area normalization for each component relative to content, component library (NIST14/NIST14S) retrieval, and a literature review were used to analyze the volatile compounds in flowers of eight peony varieties, such as “Gaoganhong”, and ten comospore peony varieties, such as “Jinshanhong”. Results showed that the main volatile compound constituents in flowers of the two groups were terpenes and alcohols. Additionally, the content of eucalyptol, caryophyllene, α-Pinene, citronellol, and 3-Hexen-1-ol, acetate, (Z) was high. Peony cultivars contained linalool, (1R)-2,6,6-trimethylbicyclo[3.1.1]hept-2-ene, and 1,4-dimethoxybenzene, while comospore peony varieties contained 1,3,6-octatriene, 3,7-dimethyl-, (Z)-, phenylethyl alcohol, and geraniol. In this study, the differences between the volatile components of flowers of different peony varieties were clarified, laying a foundation for further molecular biology research into the floral fragrance of peonies and the cultivation of new varieties of aromatic peonies. At the same time, it also provides a theoretical basis for the development and application of peony flower by-products.

A survey of Intel SGX and its applications

This paper presents a comprehensive survey on the development of Intel SGX (software guard extensions) processors and its applications. With the advent of SGX in 2013 and its subsequent development, the corresponding research works are also increasing rapidly. In order to get a more comprehensive literature review related to SGX, we have made a systematic analysis of the related papers in this area. We first search through five large-scale paper retrieval libraries by keywords (i.e., ACM Digital Library, IEEE/IET Electronic Library, SpringerLink, Web of Science, and Elsevier Science Direct). We read and analyze a total of 128 SGX-related papers. The first round of extensive study is conducted to classify them. The second round of intensive study is carried out to complete a comprehensive analysis of the paper from various aspects. We start with the working environment of SGX and make a conclusive summary of trusted execution environment (TEE). We then focus on the applications of SGX. We also review and study multifarious attack methods to SGX framework and some recent security improvements made on SGX. Finally, we summarize the advantages and disadvantages of SGX with some future research opportunities. We hope this review could help the existing and future research works on SGX and its application for both developers and users.

Comprehensive Analysis of Volatile Compounds in Mouthpiece Cigarette Adhesive by Coupling Headspace with Gas Chromatography-Mass Spectrometry.

Some volatile compounds in mouthpiece cigarette adhesive emit irritating odors and affect the taste of smoking cigarettes. Therefore, it is necessary to monitor the volatile compounds in mouthpiece cigarette adhesive. A rapid and simple analytical method of volatile compounds in mouthpiece cigarette adhesive was established. In this study, headspace (HS) injection coupled with GC-MS was utilized for qualitative and quantitative analysis. Initially, the volatile compounds in mouthpiece cigarette adhesives were detected by HS-GC-MS, followed by spectrum library retrieval. The detected compounds with the similarity to a spectrum library of more than 85% were further identified by comparing the retention time and mass spectra of the detected volatile compounds and those of the corresponding standard samples. The quantitative analysis of nine identified volatile compounds was performed. Eleven volatile compounds in the mouthpiece cigarette adhesive were accurately identified. The quantitative analytical method of nine volatile compounds in mouthpiece cigarette adhesive was validated to have good linearities (R2 > 0.9932) within the range of 20-5000 ng/g. The detection limits of 9 compounds were within the range of 3.1-147.7 ng/g. The intra- and inter-day relative standard deviations were less than 19.8%. The recoveries of these 9 compounds spiked into mouthpiece cigarette adhesive were 68.1-108.3%. The proposed method is rapid, simple, and accurate for qualitative and quantitative analysis of volatile compounds in the mouthpiece cigarette adhesive. The developed analytical method is expected to be used to monitor volatile compounds in various adhesives.