Výsledky vyhľadávania - "algorithms for data and knowledge management"

SpatialSSJP: QoS-Aware Adaptive Approximate Stream-Static Spatial Join Processor

Autori: Jawarneh, Isam Mashhour Al Bellavista, Paolo Corradi, Antonio a ďalší

Zdroj: IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS

Predmety: Algorithms for data and knowledge management, Data Architecture, Spatial databases and GIS, QoS Data Management, Spatial Join, Spatial Indexes, Geospatial Analysis, Apache Spark, Query Processing, Big Data Applications

Popis súboru: application/pdf

Prístupová URL adresa: https://hdl.handle.net/11585/962266
https://doi.org/10.1109/tpds.2023.3330669
https://ieeexplore.ieee.org/document/10309986

Biasing second-order random walk sampling for heterogeneous graph embedding

Autori: Soto-Gomez, Mauricio Cano, Carlos Reese, Justin a ďalší

Prispievatelia: Soto-Gomez, Mauricio Cano, Carlos Reese, Justin a ďalší

Predmety: machine learning, graphs and network, algorithms for data and knowledge management, Settore INFO-01/A - Informatica

Relation: info:eu-repo/semantics/altIdentifier/isbn/979-8-3315-1043-5; ispartofbook:2025 International Joint Conference on Neural Networks (IJCNN); International Joint Conference on Neural Networks; firstpage:1; lastpage:8; numberofpages:8; serie:PROCEEDINGS OF . INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS; https://hdl.handle.net/2434/1197455

Dostupnosť: https://hdl.handle.net/2434/1197455
https://doi.org/10.1109/ijcnn64981.2025.11228884

Unsupervised feature construction for improving data representation and semantics

Autori: Rizoiu, Marian-Andrei Velcin, Julien Lallich, Stéphane a ďalší

Prispievatelia: Rizoiu, Marian-Andrei Velcin, Julien Lallich, Stéphane a ďalší

Zdroj: Journal of Intelligent Information Systems. 40:501-527

Predmety: [INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI], FOS: Computer and information sciences, Computer Science - Machine Learning, Nonparametric statistics, Computer Science - Artificial Intelligence, [INFO.INFO-LG] Computer Science [cs]/Machine Learning [cs.LG], 02 engineering and technology, Feature evaluation, 7. Clean energy, 01 natural sciences, Clustering, [STAT.ML] Statistics [stat]/Machine Learning [stat.ML], Machine Learning (cs.LG), Representations, Pattern analysis, Artificial Intelligence (cs.AI), 13. Climate action, Unsupervised feature construction, 0202 electrical engineering, electronic engineering, information engineering, Heuristic methods, 0101 mathematics, Algorithms for data and knowledge management, Data mining

Popis súboru: application/pdf

Prístupová URL adresa: http://arxiv.org/pdf/1512.05467
http://arxiv.org/abs/1512.05467
http://ui.adsabs.harvard.edu/abs/2015arXiv151205467R/abstract
http://export.arxiv.org/pdf/1512.05467
https://arxiv.org/pdf/1512.05467.pdf
https://arxiv.org/abs/1512.05467
https://link.springer.com/article/10.1007/s10844-013-0235-x
https://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.398.8389&rep=rep1&type=pdf
https://doi.org/10.1007/s10844-013-0235-x
http://users.cecs.anu.edu.au/~u5673898/documents/research/papers/RIZOIU_JIIS-2013-preprint.pdf
https://dblp.uni-trier.de/db/journals/corr/corr1512.html#RizoiuVL15a
https://link.springer.com/article/10.1007/s10844-013-0235-x/fulltext.html
https://hal.science/hal-00866982v1/document
https://doi.org/10.1007/s10844-013-0235-x
https://hal.science/hal-00866982v1

ADMiRe: an algebraic data mining approach to system performance analysis

Autori: Kien A. Hua Abhijit Sawant R. Villafane a ďalší

Zdroj: IEEE Transactions on Knowledge and Data Engineering. 17:888-901

Predmety: Systems, data mining, 02 engineering and technology, Engineering, Artificial Intelligence, performance of systems, Information, algorithms for data and knowledge, Computer Science, 0202 electrical engineering, electronic engineering, information engineering, Electrical & Electronic, KNOWLEDGE, Algorithms for data and knowledge management, Data mining, management, Performance of systems

Conversemos: Un sistema conversacional inteligente para el bienestar emocional ; Let's Talk: An Intelligent Conversational System for Emotional Well-being

Autori: Anaya Ramirez, Paula Andrea Cardenas Cortes, Luis Esteban Sanchez Malagon, Cristian David a ďalší

Prispievatelia: Anaya Ramirez, Paula Andrea Cardenas Cortes, Luis Esteban Sanchez Malagon, Cristian David a ďalší

Predmety: Inteligencia Artificial, Algoritmos para la gestión de datos y conocimiento, Medicina y ciencia, Psicología, Diagnósticos, Educación, 621.3, Artificial Intelligence, Algorithms for data and knowledge management, Medicine and science, Psychology, Diagnostics, Education

Popis súboru: application/pdf

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Delgado Roman, "CLINIC DETEC: Agente inteligente para detectar la depresión en jóvenes universitarios," Ciencia Latina, vol. 6, no. 3, pp. 3090-3109, Jun. 2022.; [15] J. Leon Martinez, "Identificación de depresión mediante el análisis de sentimientos," Escuela Politécnica de México. Bachelor's thesis, 2019.; [16] L. A. Herrera Maldonado, "Detección de depresión con técnicas de inteligencia artificial," Bachelor’s thesis, Benemérita Universidad Autónoma de Puebla, 2022.; [17] F. A. Incio Flores, D. L. Capuñay Sanchez, R. O. Estela Urbina, M. Angel Valles Coral, S. E. Vergara Medrano, y D. G. Elera Gonzalez, "Inteligencia artificial en educación: una revisión de la literatura en revistas científicas internacionales," Apunt. univ., vol. 12, no. 1, pp. 353–372, Dic. 2021.; [18] J. J. Palacios Rozo, H. E. Palacio Velasquez, y R. Gonzalez Silva, "Educación versus tecnología y su convergencia hacia la IA," Rev. Vínculos, vol. 15, no. 2, pp. 186–194, Nov. 2018.; [19] B. Bonami, L. 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Weisz, "Psychotherapy for depression across different age groups: A systematic review and meta-analysis," JAMA Psychiatry, 77, 2020, pp. 694–702.; [28] G. B. L. L. R. M. Fulmer R, Joerin A, "Using psychological artificial intelligence (TESS) to relieve symptoms of depression and anxiety: Randomized controlled trial," JMIR Mental Health, 6, 2018.; [29] K. E. G. M. Babu, Nirmal Varghese, "Sentiment analysis in social media data for depression detection using artificial intelligence: A review," SN Comput. Sci., 3, 2019.; [30] J. N. C. C. B. E. Dosovitsky G, Pineda BS, "Artificial intelligence chatbot for depression: Descriptive study of usage," JMIR Form Res, 4, 2020.; [31] S. T. T. S. A. G. Lija Joy, Nissy Alex, "Artificial intelligence-based depression recognition system," Int. Res. J. Eng. Technol., 7, 2020.; [32] B. F. J. R. L. D. S. K. 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Cormack F, McCue M, "Wearable technology for high-frequency cognitive and mood assessment in major depressive disorder: Longitudinal observational study," JMIR Mental Health, 6, 2019.; [37] L. Tarver, P. Barreira, "Evaluating a Mobile App for Students Seeking Care for Depression and Anxiety at Harvard University Health Services," Harvard Medical School, https://clinicaltrials.gov/study/NCT03552900, abril 2018.; [38] T. V. Little, S. Caplan, A. S. Lovera, P. Reyna, P. Chau, A. Aguilera, J. A. Sánchez Castillo y E. R. Shapiro, "Mobile App to Prevent Depression in the Dominican Republic: Sociocultural Adaptations," presentado en Sigma Theta Tau International, Dublin, Ireland, 30 de julio de 2017.; [39] A. Drigas, D. E. Dede y S. Dedes, "Mobile and other applications for mental imagery to improve learning disabilities and mental health," International Journal of Computer Science Issues (IJCSI), vol. 17, no. 4, pp. 18-23, 2020.; [40] S. Graham, C. Depp, E. E. Lee, C. Nebeker, X. Tu, H. C. 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Sammut, "The prevalence and correlates of depression, anxiety, and stress in a sample of college students," Journal of Affective Disorders, vol. 173, pp. 90-96, 2015. doi:10.1016/j.jad.2014.10.054.; [44] N. Suarez Monzon, R. Requeiro Almeida, S. A. Heredia Gálvez y D. G. Lara Paredes, "Salud mental y usos de la tecnología en el contexto universitario. Una revisión de la literatura," PUBLICACIONES, vol. 52, no. 3, pp. 191-228, 2022. doi:10.30827/publicaciones.v52i3.22272.; [45] E. K. Jenkins, V. Bungay, A. Patterson, E. M. Saewyc y J. L. Johnson, "Assessing the impacts and outcomes of youth-driven mental health promotion: A mixed-methods assessment of the Social Networking Action for Resilience study," Journal of Adolescence, vol. 67, pp. 1-11, 2018. doi:10.1016/j.adolescence.2018.05.009.; [46] A. Va¨an¨ anen, K. Haataja, K. Vehviläinen-Julkunen y P. Toivanen, "AI in healthcare: A narrative review," F1000Research, vol. 10, p. 6, 2021. doi:10.12688/f1000research.26997.2.; [47] F. 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Dostupnosť: https://hdl.handle.net/20.500.12495/12297

Interpretation of Structural Preservation in Low-Dimensional Embeddings.

Autori: Ghosh, Aindrila Nashaat, Mona Miller, James a ďalší

Zdroj: IEEE Transactions on Knowledge & Data Engineering. May2022, Vol. 34 Issue 5, p2227-2240. 14p.

Predmety: *DIMENSIONAL reduction algorithms, *DIMENSION reduction (Statistics), *GEOGRAPHICAL discoveries

VA-Store: A Virtual Approximate Store Approach to Supporting Repetitive Big Data in Genome Sequence Analyses.

Autori: Liu, Xianying Zhu, Qiang Pramanik, Sakti a ďalší

Zdroj: IEEE Transactions on Knowledge & Data Engineering. Mar2020, Vol. 32 Issue 3, p602-616. 15p.

Predmety: *BIG data, *SEQUENCE analysis, *NUCLEOTIDE sequencing, *TASK analysis, *ELECTRONIC data processing, *GENETIC techniques, *NONRELATIONAL databases

Bayesian Nonparametric Models for Multiway Data Analysis.

Autori: Xu, Zenglin Yan, Feng Qi, Yuan

Zdroj: IEEE Transactions on Pattern Analysis & Machine Intelligence. Feb2015, Vol. 37 Issue 2, p475-487. 13p.

Predmety: *BAYESIAN analysis, *DATA analysis, *MATHEMATICAL decomposition, *FACTORIZATION, *COMPUTATIONAL complexity

Efficient Duplication Free and Minimal Keyword Search in Graphs.

Autori: Kargar, Mehdi An, Aijun Yu, Xiaohui

Zdroj: IEEE Transactions on Knowledge & Data Engineering. Jul2014, Vol. 26 Issue 7, p1657-1669. 13p.

Predmety: *KEYWORD searching, *DATABASE management, *INFORMATION technology, *SUBGRAPHS, *POLYNOMIAL time algorithms, *APPROXIMATION algorithms

Determining $(k)$-Most Demanding Products with Maximum Expected Number of Total Customers.

Autori: Lin, Chen-Yi Koh, Jia-Ling Chen, Arbee L.P.

Zdroj: IEEE Transactions on Knowledge & Data Engineering. Aug2013, Vol. 25 Issue 8, p1732-1747. 16p.

Predmety: *NUMBER theory, *PRODUCTION planning, *CONSUMERS, *GREEDY algorithms, *SCHOOLS, *DECISION support systems, *SEARCH algorithms

Robust Module-Based Data Management.

Autori: Goasdoué, François Rousset, Marie-Christine

Zdroj: IEEE Transactions on Knowledge & Data Engineering. Mar2013, Vol. 25 Issue 3, p648-661. 14p.

Predmety: *DATABASE management, *ONTOLOGY, *DATA extraction, *SEMANTIC Web, *ARTIFICIAL intelligence, *KNOWLEDGE management

有效率找出k個滿足最多客戶需求/喜愛產品之演算法

Autori: 林真伊 Lin, Chen-Yi 陳良弼 a ďalší

Prispievatelia: 林真伊 Lin, Chen-Yi 陳良弼 a ďalší

Predmety: 資料與知識管理演算法, 決策支援, 演算法及系統效能評估, 查詢處理, algorithms for data and knowledge management, decision support, performance evaluation of algorithm and systems, query processing

Time: 2

Relation: http://nthur.lib.nthu.edu.tw/dspace/handle/987654321/76402

Dostupnosť: http://nthur.lib.nthu.edu.tw/dspace/handle/987654321/76402

FLOTT—A Fast, Low Memory T-TransformAlgorithm for Measuring String Complexity.

Autori: Rebenich, Niko Speidel, Ulrich Neville, Stephen W. a ďalší

Zdroj: IEEE Transactions on Computers. Apr2014, Vol. 63 Issue 4, p917-926. 10p.

Predmety: *COMPUTER storage devices, *COMPUTATIONAL complexity, *ALGORITHMS, *TREE graphs, *LEMPEL-Ziv algorithm, *OPEN source software

Appendix A.

Autori: Kantardzic, Mehmed

Zdroj: Data Mining: Concepts, Models, Methods & Algorithms; 2011, p470-495, 26p

KungFQ: A Simple and Powerful Approach to Compress fastq Files.

Autori: Grassi, Elena Gregorio, Federico Di Molineris, Ivan

Zdroj: IEEE/ACM Transactions on Computational Biology & Bioinformatics; Nov2012, Vol. 9 Issue 6, p1837-1842, 6p

ADMiRe: An Algebraic Data Mining Approach to System Performance Analysis.

Autori: Jiang, Ning Villafane, Roy Hua, Kien A. a ďalší

Zdroj: IEEE Transactions on Knowledge & Data Engineering; Jul2005, Vol. 17 Issue 7, p888-901, 14p

Predmety: DATA mining, DATABASE searching, DECISION support systems, INFORMATION resources management, ONLINE data processing, ALGEBRA

IEEE GUIDE FOR AUTHORS.

Zdroj: IEEE Spectrum; 1996, Vol. 33 Issue 1, p107-107, 1p

使用混合特徵選取於蛋白質結晶預測 ; Hybrid feature selection in protein crystallization prediction

Autori: 葉致遠 Yeh, Jr-yuan 淡江大學資訊工程學系碩士班 a ďalší

Prispievatelia: 葉致遠 Yeh, Jr-yuan 淡江大學資訊工程學系碩士班 a ďalší

Predmety: 支持向量機, 適應推進演算法, 特徵選取, 機器學習, 不平衡資料集, 蛋白質結晶, Support Vector Machine, Adaboost, Feature Selection, Machine learning, Imbalance data, Protein Crystallization

Popis súboru: 143 bytes; application/octet-stream

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Dostupnosť: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/35205
https://tkuir.lib.tku.edu.tw/dspace/bitstream/987654321/35205/1/

Data Mining : Concepts, Models, Methods, and Algorithms

Autori: Mehmed Kantardzic

Typ zdroja: eBook.

Predmet: Data mining

Kategórie: COMPUTERS / Data Science / Data Analytics

Data Mining : Concepts, Models, Methods, and Algorithms

Autori: Mehmed Kantardzic

Typ zdroja: eBook.

Predmet: Data mining

Kategórie: COMPUTERS / Data Science / Data Analytics