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Academic literature on the topic 'Jaccard's similarity measure'

Author: Grafiati

Published: 3 June 2025

Last updated: 31 July 2025

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Journal articles on the topic "Jaccard's similarity measure"

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Hwang, Chao-Ming, and Miin-Shen Yang. "New Similarity Measures Between Generalized Trapezoidal Fuzzy Numbers Using the Jaccard Index." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 22, no. 06 (2014): 831–44. http://dx.doi.org/10.1142/s0218488514500445.

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Similarity measures between generalized trapezoidal fuzzy numbers (GTFNs) are employed to indicate the degrees of similarity between GTFNs. Although several similarity measures of GTFNs have been proposed in the literature, none has considered using the Jaccard index. In general, the Jaccard index is a statistic used for comparing the similarity and diversity of sample sets. This paper presents a new similarity measure between GTFNs, which involves the Jaccard index. The proposed similarity measure is found to have better properties. Several examples are employed to compare the proposed measur

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Kim, Seongho, Ikuko Kato, and Xiang Zhang. "Comparative Analysis of Binary Similarity Measures for Compound Identification in MassSpectrometry-Based Metabolomics." Metabolites 12, no. 8 (2022): 694. http://dx.doi.org/10.3390/metabo12080694.

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Compound identification is a critical step in untargeted metabolomics. Its most important procedure is to calculate the similarity between experimental mass spectra and either predicted mass spectra or mass spectra in a mass spectral library. Unlike the continuous similarity measures, there is no study to assess the performance of binary similarity measures in compound identification, even though the well-known Jaccard similarity measure has been widely used without proper evaluation. The objective of this study is thus to evaluate the performance of binary similarity measures for compound ide

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Gonzalez-Huitron, Victor Alejandro, Abraham Efraim Rodriguez-mata, Leonel Ernesto Amabilis-Sosa, Rogelio Baray-Arana, Isidro Robledo-Vega, and Guillermo Valencia-Palomo. "Jaccard distance as similarity measure for disparity map estimation." IEEE Latin America Transactions 21, no. 5 (2023): 690–98. http://dx.doi.org/10.1109/tla.2023.10130841.

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Mahmood, Tahir, Ubaid Ur Rehman, Zeeshan Ali, and Ronnason Chinram. "Jaccard and Dice Similarity Measures Based on Novel Complex Dual Hesitant Fuzzy Sets and Their Applications." Mathematical Problems in Engineering 2020 (November 11, 2020): 1–25. http://dx.doi.org/10.1155/2020/5920432.

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Complex dual hesitant fuzzy set (CDHFS) is a combination of two modifications, called complex fuzzy set (CFS) and dual hesitant fuzzy set (DHFS). CDHFS makes two degrees, called membership valued and nonmembership valued in the form of a finite subset of a unit disc in the complex plane, and is a capable method to solve uncertain and unpredictable information in real-life problems. The goal of this study is to describe the notion of CDHFS and its operational laws. The novel approach of the complex interval-valued dual hesitant fuzzy set (CIvDHFS) and its fundamental laws are also described and

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Ivanets, O. "Water fleas of Lviv region (Crustacea: Cladocera) in hydrobiological research by B. Dybovsky and M. Grohovsky (based on the materials of the round table of the ecological commission of the Shevchenko Scientific Society)." Visnyk of Lviv University. Biological series, no. 89 (October 13, 2023): 37–48. http://dx.doi.org/10.30970/vlubs.2023.89.04.

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49 taxa of Cladocera were registered in the reservoirs of Lviv region according to the materials of B. Dybovskyi and M. Grohovskyi. From the point of view of faunal diversity, the studied locations can be divided into two groups. The first group of locations (registered 10 or more taxa each): Pelchynsky pond, Yanivsky pond, Big Golosko. The second group of locations (up to 5 taxa are registered): Kilinsky Park, Sobka pond, Small Golosko, Zboishcha, Snopkiv, Horodok, Zhydachiv. The largest number of Cladocera taxa was registered in the Janivsky pond (21 taxa). The smallest number (1 taxon) was

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Rakhmawati, Nur Aini, and Miftahul Jannah. "Food Ingredients Similarity Based on Conceptual and Textual Similarity." Halal Research Journal 1, no. 2 (2021): 87–95. http://dx.doi.org/10.12962/j22759970.v1i2.107.

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Open Food Facts provides a database of food products such as product names, compositions, and additives, where everyone can contribute to add the data or reuse the existing data. The open food facts data are dirty and needs to be processed before storing the data to our system. To reduce redundancy in food ingredients data, we measure the similarity of ingredient food using two similarities: the conceptual similarity and textual similarity. The conceptual similarity measures the similarity between the two datasets by its word meaning (synonym), while the textual similarity is based on fuzzy st

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Bocianowski, Jan, Janetta Niemann, Anna Jagieniak, and Justyna Szwarc. "Comparison of Six Measures of Genetic Similarity of Interspecific Brassicaceae Hybrids F2 Generation and Their Parental Forms Estimated on the Basis of ISSR Markers." Genes 15, no. 9 (2024): 1114. http://dx.doi.org/10.3390/genes15091114.

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Genetic similarity determines the extent to which two genotypes share common genetic material. It can be measured in various ways, such as by comparing DNA sequences, proteins, or other genetic markers. The significance of genetic similarity is multifaceted and encompasses various fields, including evolutionary biology, medicine, forensic science, animal and plant breeding, and anthropology. Genetic similarity is an important concept with wide application across different scientific disciplines. The research material included 21 rapeseed genotypes (ten interspecific Brassicaceae hybrids of F2

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Sakira Kamaruddin, Siti, Yuhanis Yusof, Nur Azzah Abu Bakar, Mohamed Ahmed Tayie, and Ghaith Abdulsattar A.Jabbar Alkubaisi. "Graph-based Representation for Sentence Similarity Measure : A Comparative Analysis." International Journal of Engineering & Technology 7, no. 2.14 (2018): 32. http://dx.doi.org/10.14419/ijet.v7i2.14.11149.

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Textual data are a rich source of knowledge; hence, sentence comparison has become one of the important tasks in text mining related works. Most previous work in text comparison are performed at document level, research suggest that comparing sentence level text is a non-trivial problem. One of the reason is two sentences can convey the same meaning with totally dissimilar words. This paper presents the results of a comparative analysis on three representation schemes i.e. term frequency inverse document frequency, Latent Semantic Analysis and Graph based representation using three similarity

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Li, Wen Qing, Jia Feng Sun, Wen Qin Lu, Yong Le Zhang, and Pu Zhao. "Semantic Similarity Measure Based on Concreteness Degree of a Concept." Advanced Materials Research 760-762 (September 2013): 852–56. http://dx.doi.org/10.4028/www.scientific.net/amr.760-762.852.

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Semantic similarity between concepts is widely used, but the measuring method is still a challenging task. We proposed a semantic similarity measuring method, using concreteness degree of a concept which is based on constructing process of ontology. Firstly, Concreteness degree of concept was defined for the concept by depth of the concept itself and its most specific descendant, then according to the Jaccards Coefficient the semantic similarity between concepts measured by the specified process of the two compared concepts and their co-specified process. Experiment result shows that the propo

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Qiyas, Muhammad, Muhammad Naeem, Saleem Abdullah, Neelam Khan, and Asad Ali. "Similarity Measures Based on q-Rung Linear Diophantine Fuzzy Sets and Their Application in Logistics and Supply Chain Management." Journal of Mathematics 2022 (January 20, 2022): 1–19. http://dx.doi.org/10.1155/2022/4912964.

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With the frequent occurrence of emergency events, decision-making (DM) plays an increasingly significant role in coping with them and has become an important and the challenging research focus recently. It is critical for decision makers to make accurate and reasonable emergency judgments in a short period as poor decisions can result in enormous economic losses and an unstable social order. As a consequence, this work offers a new DM approach based on novel distance and similarity measures using q-rung linear Diophantine fuzzy (q-RLDF) information to assure that DM problems may be addressed s

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Book chapters on the topic "Jaccard's similarity measure"

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Abdalla, Hassan I., Yasmeen A. Amer, Loc Nguyen, Ali A. Amer, and Basheer Mohamad Al-Maqaleh. "Numerical Similarity Measures Versus Jaccard for Collaborative Filtering." In Proceedings of the 9th International Conference on Advanced Intelligent Systems and Informatics 2023. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-43247-7_20.

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Jindal, Anisha, Naveen Sharma, and Vijay Verma. "Joyful Jaccard: An Analysis of Jaccard-Based Similarity Measures in Collaborative Recommendations." In Lecture Notes in Electrical Engineering. Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-8542-2_3.

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Burattin, Andrea, Hugo A. López, and Lasse Starklit. "Uncovering Change: A Streaming Approach for Declarative Processes." In Lecture Notes in Business Information Processing. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-27815-0_12.

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AbstractProcess discovery is a family of techniques that helps to comprehend processes from their data footprints. Yet, as processes change over time so should their corresponding models, and failure to do so will lead to models that under- or over-approximate behaviour. We present a discovery algorithm that extracts declarative processes as Dynamic Condition Response (DCR) graphs from event streams. Streams are monitored to generate temporal representations of the process, later processed to create declarative models. We validated the technique by identifying drifts in a publicly available da

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Mohana, H., and M. Suriakala. "An Enhanced Prospective Jaccard Similarity Measure (PJSM) to Calculate the User Similarity Score Set for E-Commerce Recommender System." In Advances in Intelligent Systems and Computing. Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-5400-1_14.

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"Cosine-Based Distances, Correlations, and Angles for Face Recognition." In Similarity Measures for Face Recognition, edited by Enrico Vezzetti and Federica Marcolin. BENTHAM SCIENCE PUBLISHERS, 2015. http://dx.doi.org/10.2174/9781681080444115010007.

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The cosine distance compares the feature vectors of two images by returning the cosine of the angle between two vectors. Other cosine- and angle-based measures are here presented, including Tanimoto dissimilarity and Jaccard index, together with other correlations; they have been employed in algorithms relying on PCA, ICA, NN, and Gabor wavelets, especially on bi-dimensional facial data. Only correlation coefficients have been applied on three-dimensional point clouds.

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Bahr Nathan J., Nelson Scott D., Winnenburg Rainer, and Bodenreider Olivier. "Eliciting the Intension of Drug Value Sets – Principles and Quality Assurance Applications." In Studies in Health Technology and Informatics. IOS Press, 2017. https://doi.org/10.3233/978-1-61499-830-3-843.

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Value sets (VSs) used in electronic clinical quality measures are lists of codes from standard terminologies (&ldquo;extensional&rdquo; VSs), whose purpose (&ldquo;intension&rdquo;) is not always explicitly stated. We elicited the intension for the 09/01/2014 release of extensional medication value sets by comparison to drug classes from the October 2014 release of RxClass. Value sets matched drug classes if they shared common ingredients, as evidenced by Jaccard similarity score. We elicited the intension of 80 extensional value sets. The average Jaccard similarity was 0.65 fo

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Borg Anton, Lavesson Niklas, and Boeva Veselka. "Comparison of Clustering Approaches for Gene Expression Data." In Frontiers in Artificial Intelligence and Applications. IOS Press, 2013. https://doi.org/10.3233/978-1-61499-330-8-55.

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Clustering algorithms have been used to divide genes into groups according to the degree of their expression similarity. Such a grouping may suggest that the respective genes are correlated and/or co-regulated, and subsequently indicates that the genes could possibly share a common biological role. In this paper, four clustering algorithms are investigated: k-means, cut-clustering, spectral and expectation-maximization. The algorithms are benchmarked against each other. The performance of the four clustering algorithms is studied on time series expression data using Dynamic TimeWarping distanc

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Kastrin Andrej, Rindflesch Thomas C., and Hristovski Dimitar. "Link Prediction in a MeSH Co-occurrence Network: Preliminary Results." In Studies in Health Technology and Informatics. IOS Press, 2014. https://doi.org/10.3233/978-1-61499-432-9-579.

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Literature-based discovery (LBD) refers to automatic discovery of implicit relations from the scientific literature. Co-occurrence associations between biomedical concepts are commonly used in LBD. These co-occurrences can be represented as a network that consists of a set of nodes representing concepts and a set of edges representing their relationships (or links). In this paper we propose and evaluate a methodology for link prediction of implicit connections in a network of co-occurring Medical Subject Headings (MeSH&reg;). The proposed approach is complementary to, and may augment, exis

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Sun, Yingcheng, Jiaqi Tang, Alex Butler, Cong Liu, Yilu Fang, and Chunhua Weng. "Interactive Similarity-Based Search of Clinical Trials." In MEDINFO 2021: One World, One Health – Global Partnership for Digital Innovation. IOS Press, 2022. http://dx.doi.org/10.3233/shti220085.

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The rapid growth of clinical trials launched in recent years poses significant challenges for accurate and efficient trial search. Keyword-based clinical trial search engines require users to construct effective queries, which can be a difficult task given complex information needs. In this study, we present an interactive clinical trial search interface that retrieves trials similar to a target clinical trial. It enables user configuration of 13 clinical trial features and 4 metrics (Jaccard similarity, semantic-based similarity, temporal overlap and geographical distance) to measure pairwise

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Dua Prerna, Bais Sonali, and Lukiw Walter J. "Analysis of Network Based Co-Expression Modules for Alzheimer's Disease." In Studies in Health Technology and Informatics. IOS Press, 2013. https://doi.org/10.3233/978-1-61499-289-9-1227.

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There has been an intensive research going on for Alzheimer's disease (AD) to understand its cause and progression through the past decade. However, the pathogenic factors that are responsible for these processes are still unclear. In this research we utilize the hippocampal gene expression data of 22 AD patients and present a framework for a comparative study to evaluate the two similarity measures, Mutual Information and Pearson Correlation Coefficient in developing gene coexpression networks. We hypothesize that Mutual Information based co-expression networks can capture more biologically s

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Conference papers on the topic "Jaccard's similarity measure"

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Batyrshin, Ildar, and Imre Rudas. "New Similarity Correlation Functions for Sets and Binary Data Based on Jaccard Similarity Measure." In 2024 IEEE 18th International Symposium on Applied Computational Intelligence and Informatics (SACI). IEEE, 2024. http://dx.doi.org/10.1109/saci60582.2024.10619901.

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Sulaiman, N. H., and D. Mohamad. "A Jaccard-based similarity measure for soft sets." In 2012 IEEE Symposium on Humanities, Science and Engineering Research (SHUSER). IEEE, 2012. http://dx.doi.org/10.1109/shuser.2012.6268901.

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Ayub, Mubbashir, Mustansar Ali Ghazanfar, Muazzam Maqsood, and Asjad Saleem. "A Jaccard base similarity measure to improve performance of CF based recommender systems." In 2018 International Conference on Information Networking (ICOIN). IEEE, 2018. http://dx.doi.org/10.1109/icoin.2018.8343073.

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Fernando, Basura, and Samitha Herath. "Anticipating human actions by correlating past with the future with Jaccard similarity measures." In 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, 2021. http://dx.doi.org/10.1109/cvpr46437.2021.01302.

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Alobed, Mohammad, Abdallah M. M. Altrad, and Zainab Binti Abu Bakar. "A Comparative Analysis of Euclidean, Jaccard and Cosine Similarity Measure and Arabic Wordnet for Automated Arabic Essay Scoring." In 2021 Fifth International Conference on Information Retrieval and Knowledge Management (CAMP). IEEE, 2021. http://dx.doi.org/10.1109/camp51653.2021.9498119.

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Saravanan, S., Aravind Britto, and S. M. Prabin. "A Novel K Means Biclustering Fusion Based Collaborative Recommender System." In International Research Conference on IOT, Cloud and Data Science. Trans Tech Publications Ltd, 2023. http://dx.doi.org/10.4028/p-510vfd.

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Collaborative Filtering (CF) examines a consumer's interests and delivers automatic and personalized suggestions for purchasing a variety of products. Sparsity, on the other hand, is one of the approach's primary flaws. This difficulty is inherent in the system due to an ever-increasing quantity of people and things. To address the problem of sparsity, many existing techniques have been given. The user-item rating matrix can only provide minimal information to estimate unknown evaluations in both user-based and item-based instances. In scarce data contexts, they are ineffective. In sparse data

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Zhang, Xian, Jiahui Li, and Shuying Li. "A Comparative Study on Text Multi-Features Mining for Patent Text Clustering: The Case of Graphene Sensing Technology." In 20th International Conference on Scientometrics & Informetrics. Institute for Informatics and Automation Problems of NAS RA, 2025. https://doi.org/10.51408/issi2025_041.

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The development of text feature extraction and measurement methods has given rise to a diversification of perspectives on text mining. However, few studies have explored the similarity, complementarity, and effectiveness of different text features. The selection of different feature combinations lacks a supporting basis. This study selected four types of text feature words from patent texts, namely, text domain feature keywords by Comprehensively Measure Feature Selection algorithm (CMFS), technical interdisciplinary keywords by the term Interdisciplinary index (TI), technical breakthrough key

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XU, YANG, YI LI, YUNFEI FAN, XIAODONG ZHENG, and YUEQUAN BAO. "TASK-SIGNIFICANCE-AWARE META LEARNING FOR FEW-IMAGE-BASED STRUCTURAL DAMAGE RECOGNITION." In Structural Health Monitoring 2023. Destech Publications, Inc., 2023. http://dx.doi.org/10.12783/shm2023/36869.

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Recently, structural damage recognition has gained significant progress using deep learning and computer vision techniques. However, massive training images, the interclass balance and completeness of damage categories are essential to ensure recognition accuracy. In addition, the generalization ability for new damage categories and robustness under real-world scenarios are limited. This study proposes a task-aware meta-learning paradigm using limited images for universal structural damage segmentation. First, a novel task generation strategy instead of random sampling is designed based on fea

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