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Relevant bibliographies by topics / Aggregate entity

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Journal articles

Academic literature on the topic 'Aggregate entity'

Author: Grafiati

Published: 13 April 2024

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Journal articles on the topic "Aggregate entity"

1

Hirose, Shoichi, and Junji Shikata. "Aggregate Entity Authentication Identifying Invalid Entities with Group Testing." Electronics 12, no. 11 (2023): 2479. http://dx.doi.org/10.3390/electronics12112479.

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It is common to implement challenge-response entity authentication with a MAC function. In such an entity authentication scheme, aggregate MAC is effective when a server needs to authenticate many entities. Aggregate MAC aggregates multiple tags (responses to a challenge) generated by entities into one short aggregate tag so that the entities can be authenticated simultaneously regarding only the aggregate tag. Then, all associated entities are valid if the pair of a challenge and the aggregate tag is valid. However, a drawback of this approach is that invalid entities cannot be identified whe

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Guangyu, Lei, and Han Jichang. "Based on the CT Image Rebuilding the Micromechanics Hierarchical Model of Concrete." Advances in Civil Engineering 2022 (October 12, 2022): 1–12. http://dx.doi.org/10.1155/2022/2445901.

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Establishing a mesoscopic numerical model to investigate the mechanical properties of concrete has very important significance. This paper considers the random distribution of aggregate in concrete. The aggregate is assumed to be spherical, respectively, to simulate the interface layer as the entity unit or the contact elements. The random aggregate model and the interface model of random aggregate were established. Based on the CT image and the application of MATLAB and MIMICS software, the different characteristics of the concrete model for 3D reconstruction were set up. Through comparative

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3

Korkontzelos, Ioannis, Dimitrios Piliouras, Andrew W. Dowsey, and Sophia Ananiadou. "Boosting drug named entity recognition using an aggregate classifier." Artificial Intelligence in Medicine 65, no. 2 (2015): 145–53. http://dx.doi.org/10.1016/j.artmed.2015.05.007.

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Cui, Xiaohui, Xiaolong Qu, Dongmei Li, Yu Yang, Yuxun Li, and Xiaoping Zhang. "MKGCN: Multi-Modal Knowledge Graph Convolutional Network for Music Recommender Systems." Electronics 12, no. 12 (2023): 2688. http://dx.doi.org/10.3390/electronics12122688.

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With the emergence of online music platforms, music recommender systems are becoming increasingly crucial in music information retrieval. Knowledge graphs (KGs) are a rich source of semantic information for entities and relations, allowing for improved modeling and analysis of entity relations to enhance recommendations. Existing research has primarily focused on the modeling and analysis of structural triples, while largely ignoring the representation and information processing capabilities of multi-modal data such as music videos and lyrics, which has hindered the improvement and user experi

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Aberbach, Adin, Mayank Kejriwal, and Ke Shen. "Multipartite Entity Resolution: Motivating a K-Tuple Perspective (Student Abstract)." Proceedings of the AAAI Conference on Artificial Intelligence 38, no. 21 (2024): 23434–35. http://dx.doi.org/10.1609/aaai.v38i21.30417.

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Entity Resolution (ER) is the problem of algorithmically matching records, mentions, or entries that refer to the same underlying real-world entity. Traditionally, the problem assumes (at most) two datasets, between which records need to be matched. There is considerably less research in ER when k > 2 datasets are involved. The evaluation of such multipartite ER (M-ER) is especially complex, since the usual ER metrics assume (whether implicitly or explicitly) k < 3. This paper takes the first step towards motivating a k-tuple approach for evaluating M-ER. Using standard algorithms and k-

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6

Tsukui, Kazuo, and Kenji Tadokoro. "Affinity Association between Polynucleotide, Glycoprotein, or Sulfated Polysaccharides and Disease-Associated Prion Protein." Microbiology Insights 2 (January 2009): MBI.S3103. http://dx.doi.org/10.4137/mbi.s3103.

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Proteinase-K resistant prion protein (PrPres) has the property to aggregate in TSE-injured animal tissues. We have developed a test method to discriminate scrapie-infected and mock-infected hamsters by detecting the PrPres in plasma. It seemed that aggregation of the PrPres with some heterogeneous molecule(s) enabled successful detection by this method. In order to investigate which molecule became the partner in the PrPres aggregates; we examined some molecules that could presumably have this ability. As a result, we found synthetic Poly-A RNA, especially in its denatured form, to be the most

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7

SEID, DAWIT, and SHARAD MEHROTRA. "AGGREGATE QUERY PROCESSING FOR SEMANTIC WEB DATABASES: AN ALGEBRAIC APPROACH." International Journal of Semantic Computing 01, no. 04 (2007): 479–95. http://dx.doi.org/10.1142/s1793351x07000226.

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As a growing number of applications represent data as semantic graphs like RDF (Resource Description Format) and the many entity-attribute-value formats, query languages for such data are being required to support operations beyond graph pattern matching and inference queries. Specifically the ability to express aggregate queries is an important feature which is either lacking or is implemented with little attention to the peculiarities of the data model. In this paper, we study the meaning and implementation of grouping and aggregate queries over RDF graphs. We first define grouping and aggre

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8

Yi, Liu, Diao Xing-chun, Cao Jian-jun, Zhou Xing, and Shang Yu-ling. "A Method for Entity Resolution in High Dimensional Data Using Ensemble Classifiers." Mathematical Problems in Engineering 2017 (2017): 1–11. http://dx.doi.org/10.1155/2017/4953280.

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In order to improve utilization rate of high dimensional data features, an ensemble learning method based on feature selection for entity resolution is developed. Entity resolution is regarded as a binary classification problem, an optimization model is designed to maximize each classifier’s classification accuracy and dissimilarity between classifiers and minimize cardinality of features. A modified multiobjective ant colony optimization algorithm is employed to solve the model for each base classifier, two pheromone matrices are set up, weighted product method is applied to aggregate values

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9

Yuan, Xu, Qihang Lei, Shuo Yu, Chengchuan Xu, and Zhikui Chen. "Fine-grained relational learning for few-shot knowledge graph completion." ACM SIGAPP Applied Computing Review 22, no. 3 (2022): 25–38. http://dx.doi.org/10.1145/3570733.3570735.

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Few-shot knowledge graph completion (FKGC) task aims to infer missing entities or relations by using few-shot support instances in the knowledge graph. Existing FKGC methods focus on the learning of few-shot relation representations, which are obtained by aggregating the neighbor information of each entity. However, most of these models take the entity's neighbor relations and entities as the same hierarchy and do not make fine-grained distinctions, resulting in entity embeddings with low expressiveness, which may further decrease the quality of learned few-shot relation embeddings. Moreover,

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10

Hager, Liesl. "The Insolvency Act’s deviation from the common law: Juristic ghost or aggregate approach?" South African Law Journal 138, no. 1 (2021): 152–70. http://dx.doi.org/10.47348/salj/v138/i1a7.

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In this article I engage with the provisions of the Insolvency Act 24 of 1936 regulating the dissolution of the universal partnership upon insolvency. Our common law prefers an aggregate approach to partnerships, meaning that a partnership enjoys no separate legal personality distinct from its composing partners. The lack of separate legal personality of a partnership is described by some academics as a ‘remarkable defect’. The Insolvency Act however creates an exception to this general rule by deeming a partnership to be a separate legal entity. The Insolvency Act’s deviation from the common-

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