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Deciphering cluster representations

Yasemin Kural, Steve Robertson, Susan Jones
2001 Information Processing & Management  
There are several recent studies that propose search output clustering as an alternative representation method to ranked output.  ...  Users are provided with cluster representations instead of lists of titles and invited to make decisions on groups of documents.  ...  be indicated in the cluster representations.  ... 
doi:10.1016/s0306-4573(00)00037-6 fatcat:mxn7v3oh3jgppefqbubgopgwsa

Duplicate detection for symbolically compressed documents

Dar-Shyang Lee, J.J. Hull
1999 Proceedings of the Fifth International Conference on Document Analysis and Recognition. ICDAR '99 (Cat. No.PR00318)  
It recognizes the text in an image by deciphering the sequence of occurrence of blobs in the compressed representation.  ...  They cluster individual blobs in a document and store the sequence of occurrence of blobs and representative blob templates, hence the name symbolic compression.  ...  The HMM deciphering algorithm proposed here solves the problem of there being more than one cluster for a given character identity in a typical document image.  ... 
doi:10.1109/icdar.1999.791785 dblp:conf/icdar/LeeH99 fatcat:adij7apekrhttg7zwyiqsv6mzm

Detecting duplicates among symbolically compressed images in a large document database

Dar-Shyang Lee, Jonathan J. Hull
2001 Pattern Recognition Letters  
This paper describes a hidden Markov model (HMM) method that recognizes the text in an image by deciphering data from the compressed representation.  ...  We apply a deciphering algorithm to the sequence of cluster identi®ers. It computes a pairwise correspondence between cluster identi®ers and letters.  ...  This sequence encodes a representation for the text in the original document.  ... 
doi:10.1016/s0167-8655(00)00115-x fatcat:zpitjv3j2nb4npgg4kn3g63riu

A Reply to a Comment on "Dark matter: A phenomenological existence proof" [article]

D. V. Ahluwalia-Khalilova
2006 arXiv   pre-print
from the studies on globular clusters.  ...  Furthermore, the phenomenologically motivated existence proof refrained from invoking the data on galactic rotational curves and gravitational lensing, but used as input the age of the universe as deciphered  ...  [2] regarding the age of the universe and the age of the globular clusters. We did not use the age of the globular clusters but the age of the universe as deciphered from that age.  ... 
arXiv:astro-ph/0603256v1 fatcat:awwsuvekdnb2hke7ujbe4ljeq4

Deciphering a multi-event in a non-complex set of detrital zircon U–Pb ages from Carboniferous graywackes of SW Iberia

A. Ferreira, C. Lopes, M. Chichorro, M.F. Pereira, A.R. Solá
2014 Chemical Geology  
First, cluster analysis is carried out, aimed at grouping zircon ages into a set of consistent clusters.  ...  Thus, can a multi-event in a non-complex set of detrital zircon U-Pb ages be deciphered and characterized?  ...  analysis based on cluster analysis; 2) the construction of several Chemical Geology 378-379 (2014) 62-74 Abbreviations: n, number of zircon age spots in a dataset; m, number of clusters of zircon age  ... 
doi:10.1016/j.chemgeo.2014.04.011 fatcat:ruwjk23pmnhmrep2yxvwp5qjhu

Substitution deciphering based on HMMs with applications to compressed document processing

Dar-Shyang Lee
2002 IEEE Transactions on Pattern Analysis and Machine Intelligence  
Although a significant amount of noise is present in the cluster sequence, enough information can be recovered with a robust deciphering algorithm to accomplish certain document analysis tasks.  ...  In this paper, we propose a new solution to substitution deciphering based on hidden Markov models.  ...  The deciphering rate and the average number of clusters generated in the compressed images are shown in Table 2 .  ... 
doi:10.1109/tpami.2002.1114860 fatcat:dwb36tm5wvamdblxeczwoam7cq

Phenotype-genotype comorbidity analysis of patients with rare disorders provides insight into their pathological and molecular bases

Elena Díaz-Santiago, Fernando M. Jabato, Elena Rojano, Pedro Seoane, Florencio Pazos, James R. Perkins, Juan A. G. Ranea, Ron Do
2020 PLoS Genetics  
We applied the approach to the DECIPHER database, containing phenotypic and genomic information for thousands of patients with heterogeneous rare disorders and copy number variants.  ...  These phenotypes are clustered using network analysis to obtain functionally coherent phenotype clusters.  ...  Acknowledgments This study makes use of data generated by the DECIPHER community.  ... 
doi:10.1371/journal.pgen.1009054 pmid:33001999 fatcat:bgjta3rvkjc4boz4fcln7v7weu

sj-pdf-1-jla-10.1177_24726303211019394 – Supplemental material for Quantitative Confocal Microscopy for Grouping of Dose–Response Data: Deciphering Calcium Sequestration and Subsequent Cell Death in the Presence of Excess Norepinephrine

Kuruba Manohar, Suman Gare, Soumita Chel, Vaibhav Dhyani, Lopamudra Giri
2021 Figshare  
Supplemental material, sj-pdf-1-jla-10.1177_24726303211019394 for Quantitative Confocal Microscopy for Grouping of Dose–Response Data: Deciphering Calcium Sequestration and Subsequent Cell Death in the  ...  (B) Cluster map (hierarchical clustering) representation of time-series Fluo-4 intensity distribution across clusters in the dose-response experiments.  ...  (a) Similarity analysis Box plot representation of correlation coefficients between two cells present within the same cluster. Ci represents i th cluster.  ... 
doi:10.25384/sage.15148211.v1 fatcat:yzusstf3xnbcfdnzl64nn2fpxq

Decipherment of Historical Manuscript Images [article]

Xusen Yin and Nada Aldarrab and Beáta Megyesi and Kevin Knight
2019 arXiv   pre-print
We develop unsupervised models for character segmentation, character-image clustering, and decipherment of cluster sequences.  ...  Convert each character image into a low-dimensional feature-vector representation. 3. Cluster feature vectors into similar groups. 4. Output a sequence of cluster IDs.  ...  We feed cipher character images into the SNN to extract feature representations. The SNN architecture (Koch et al., 2015) is shown in Figure 6 .  ... 
arXiv:1810.04297v3 fatcat:vmgeare43zfpzcsshrtrobvarm

Convolution Index based Unsupervised Label Procedure for Efficient Medical Image Exploration

2019 VOLUME-8 ISSUE-10, AUGUST 2019, REGULAR ISSUE  
We characterize AI as matrix convex optimization with cluster-based matrix representation which can be utilized to improve the productivity in picture recovery framework.  ...  We characterize AI as matrix convex optimization with cluster based matrix representation which can be utilized to improve the productivity in picture recovery framework.  ...  We characterize AI as matrix convex optimization with cluster-based matrix representation which can be utilized to improve the productivity in picture recovery framework. keywords: Content based image  ... 
doi:10.35940/ijitee.l3707.1081219 fatcat:2r7ujz3u4fbepodzchedoiqbyu

Jointly learning T-cell receptor and transcriptomic information to decipher the immune response [article]

Yang An, Felix Drost, Fabian Theis, Benjamin Schubert, Mohammad Lotfollahi
2021 bioRxiv   pre-print
We evaluated mvTCR on two datasets showing a clear separation of the cell state and their functionality, thus, providing a more biologically informative representation than models using each modality individually  ...  representation when studying human T cell repertoires.  ...  ASW measures intra-cluster cohesion compared to inter-cluster separation, where higher values indicate clearer clustering.  ... 
doi:10.1101/2021.06.24.449733 fatcat:vrkeem6w2fd4zibnjly6bcwnwu

Generative pretraining from large-scale transcriptomes: Implications for single-cell deciphering and clinical translation [article]

Hongru Shen, Xilin Shen, Jiani Hu, Jilei Liu, Chao Zhang, Dan Wu, Mengyao Feng, Meng Yang, Yang Li, Yichen Yang, Wei Wang, Qiang Zhang (+3 others)
2022 bioRxiv   pre-print
The single-cell clusters and cell lineage trajectories derived from tGPT are highly aligned with known cell labels and states.  ...  tissues learned by tGPT are associated with a wide range of genomic alteration events, prognosis and treatment outcome of immunotherapy. tGPT represents a new analytical paradigm for integrating and deciphering  ...  The high clustering performance in single-cell cluster delineation is probably attributable to better feature representation learned by tGPT.  ... 
doi:10.1101/2022.01.31.478596 fatcat:ehqfmpbm2rbxpf2cgptahjiwqe

Evaluating, Filtering and Clustering Genetic Disease Cohorts Based on Human Phenotype Ontology Data with Cohort Analyzer

Elena Rojano, José Córdoba-Caballero, Fernando M. Jabato, Diana Gallego, Mercedes Serrano, Belén Pérez, Álvaro Parés-Aguilar, James R. Perkins, Juan A. G. Ranea, Pedro Seoane-Zonjic
2021 Journal of Personalized Medicine  
In addition, it performs clustering analysis to find subgroups of patients that share similar phenotypic profiles.  ...  found that cohorts with the most specific and complete phenotypic characterization give more potential insights into the disease than those that were less deeply characterised by forming more informative clusters  ...  In the case of the ID/MCA cohort, clusters include lower number of phenotypes in comparison to the DECIPHER dataset and all members in each cluster have identical phenotypes, except for clusters 6, 17,  ... 
doi:10.3390/jpm11080730 pmid:34442375 pmcid:PMC8398478 fatcat:a4psvjd3d5dvnaoaegpycinuoe

Inferring Intra-Community Microbial Interaction Patterns from Metagenomic Datasets Using Associative Rule Mining Techniques

Disha Tandon, Mohammed Monzoorul Haque, Sharmila S. Mande, Niyaz Ahmed
2016 PLoS ONE  
Deciphering these interaction patterns is crucial for understanding the mode/mechanism(s) through which an individual microbial community transitions from one state to another (e.g. from a healthy to a  ...  Using real-world microbiome data, the efficiency/utility of this rule mining approach in deciphering multiple (biologically meaningful) association patterns between 'subsets/subgroups' of microbes (constituting  ...  The distance values are then hierarchically clustered (and progressively merged) until 2 clusters remain.  ... 
doi:10.1371/journal.pone.0154493 pmid:27124399 pmcid:PMC4849775 fatcat:aqpvgk2afnds3bdgs4ujviuqpe

Analysis of COVID-19 in different countries using Wigner energy distribution and clustering

Ranjani Murali
2020 2020 19th IEEE International Conference on Machine Learning and Applications (ICMLA)  
The fundamental similarity in the pandemic's progress in countries can be deciphered using clustering and this similarity can be used to model the future dynamics of countries from those clustered together  ...  The modified EM algorithm with two layer latent representations effectively captures the similarity in the temporal dynamics of different countries.  ...  The fundamental similarity in the pandemic's progress in countries can be deciphered using clustering and this similarity can be used to model the future dynamics of countries from the same clusters.  ... 
doi:10.1109/icmla51294.2020.00099 fatcat:bayslgvubrbx7cp36yed676sme
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