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A semantic annotation framework for retrieving and analyzing observational datasets

Shawn Bowers, Huiping Cao, Mark Schildhauer, Matt Jones, Ben Leinfelder, Margaret O'Brien
2010 Proceedings of the third workshop on Exploiting semantic annotations in information retrieval - ESAIR '10  
This framework combines a core observational model, domain-specific ontologies compatible with the core model, and a semantic annotation language.  ...  To address this issue, we describe a framework for accessing observational data.  ...  Our approach leverages a core observational ontology and a declarative annotation syntax. Our annotation framework has been implemented within a common set of ecological data management tools.  ... 
doi:10.1145/1871962.1871982 dblp:conf/cikm/BowersCSJLO10 fatcat:6e5nzij77fblrc2y4iyndfdd7a

Ad hoc retrieval via entity linking and semantic similarity

Faezeh Ensan, Weichang Du
2018 Knowledge and Information Systems  
In this paper, we propose a novel semantic retrieval framework that uses semantic entity linking systems for forming a graph representation of documents and queries, where nodes represent concepts extracted  ...  The semantic retrieval framework also provides basis for interpolating keyword-based retrieval systems with the semantic-enabled language model.  ...  Experiments In this section, we describe experiments for analyzing the performance of the proposed semantic retrieval framework.  ... 
doi:10.1007/s10115-018-1190-1 fatcat:i54ocl6etngkpkcx62mhxilfxe

On Analyzing Annotation Consistency in Online Abusive Behavior Datasets [article]

Md Rabiul Awal, Rui Cao, Roy Ka-Wei Lee, Sandra Mitrović
2020 arXiv   pre-print
In this study, we proposed an analytical framework to study the annotation consistency in online hate and abusive content datasets.  ...  We found that there is still a substantial amount of annotation inconsistency in the existing datasets, particularly when the labels are semantically similar.  ...  We applied our proposed framework to analyze three popular online misbehavior datasets.  ... 
arXiv:2006.13507v1 fatcat:6vqfrdhfsvc35mhdbx7z2o6k4y

Semantic-based Approach for Solving the Heterogeneity of Clinical Data

Basma Elsharkawy, Hatem Ahmed, Rashed Salem
2016 IJCI. International Journal of Computers and Information  
Secondly, it achieves a semantic-based medical retrieval approach with enhanced precision.  ...  Our experimental study on medical datasets demonstrates the significant accuracy and speedup of the proposed framework over existing approaches.  ...  Furthermore, this paper proposes a semantic-based framework for medical data retrieval.  ... 
doi:10.21608/ijci.2016.33955 fatcat:zl7knrxnpnhndhkwtunt4dxo4q

Semantic Concept Co-Occurrence Patterns for Image Annotation and Retrieval

Linan Feng, Bir Bhanu
2016 IEEE Transactions on Pattern Analysis and Machine Intelligence  
ACKNOWLEDGMENTS This material is based upon work supported by the National Science Foundation under Grant No. 0905671 and 1552454.  ...  Hierarchical semantic indexing (HSI): The retrieval framework proposed in [38] uses the information Fig. 6 . The annotations for the test images from the three datasets by our approach.  ...  The framework is evaluated for automated image annotation and concept-based image retrieval tasks using the new concept signature representation.  ... 
doi:10.1109/tpami.2015.2469281 pmid:26959678 fatcat:enu2lsrmzfgsfp4vvf5hj3d27y

Semi-automatic audio semantic concept discovery for multimedia retrieval

Yipei Wang, Shourabh Rawat, Florian Metze
2014 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)  
Previous work explored semantic concepts for content analysis to assist retrieval.  ...  Also, building a corpus is expensive and time-consuming. To address these issues, we propose a semi-automatic framework to discover the semantic concepts. We limit ourselves in audio modality here.  ...  Given a query, search engine retrieve relevant videos by analyzing their captions or textual descriptions. This initial method faces big problem.  ... 
doi:10.1109/icassp.2014.6853822 dblp:conf/icassp/WangRM14a fatcat:h5od6ae3njadbbut3czjlavwgi

iASiS Open Data Graph: Automated Semantic Integration of Disease-Specific Knowledge [article]

Anastasios Nentidis, Konstantinos Bougiatiotis, Anastasia Krithara, Georgios Paliouras
2020 arXiv   pre-print
In this study, we propose a framework to automatically retrieve and integrate disease-specific knowledge into an up-to-date semantic graph, the iASiS Open Data Graph.  ...  Exemplary queries are presented, investigating the potential of this automatically generated semantic graph as a basis for retrieval and analysis of disease-specific knowledge.  ...  Dataset creation The framework was employed once for each disease, configured with the appropriate semantic topic 12 to retrieve and analyse all available relevant literature in PubMed and create the corresponding  ... 
arXiv:1912.08633v2 fatcat:djs6dt5lubctbfgc7uurqvt66e

On combining image-based and ontological semantic dissimilarities for medical image retrieval applications

Camille Kurtz, Adrien Depeursinge, Sandy Napel, Christopher F. Beaulieu, Daniel L. Rubin
2014 Medical Image Analysis  
The relevance of the retrieval results was assessed using two protocols: evaluation relative to a dissimilarity reference standard defined for pairs of images on a 25-images dataset, and evaluation relative  ...  to the diagnoses of the retrieved images on a 72-images dataset.  ...  This project was funded in part by a Grant from National Cancer Institute, National Institutes of Health (# U01CA142555-01, # R01 CA160251), the Swiss National Science Foundation (# PBGEP2_142283), and  ... 
doi:10.1016/ pmid:25036769 pmcid:PMC4173098 fatcat:jxg3gipstndjzabu3rpfl5vweu

A Deep Learning Framework for Semi-Supervised Cross-Modal Retrieval with Label Prediction [article]

Devraj Mandal, Pramod Rao, Soma Biswas
2018 arXiv   pre-print
Extensive experiments on three standard benchmark datasets, Wiki, Pascal VOC and NUS-WIDE demonstrate that the proposed framework outperforms the state-of-the-art for both supervised and semi-supervised  ...  for cross-modal retrieval.  ...  For the M-L datasets, we analyzed the following loss functions (a) L1 loss (b) BCE and (d) WBCE.  ... 
arXiv:1812.01391v1 fatcat:xpbpeepiyzcxtbofeiwbr63ps4

Semantic indexing and computational aesthetics

Miriam Redi
2013 Proceedings of the 3rd ACM conference on International conference on multimedia retrieval - ICMR '13  
We investigate the role of Semantic Indexing techniques for Computational Aesthetics Frameworks, and, vice versa, the importance of Aesthetic features for Semantic Indexing prediction.  ...  Semantic Indexing and Computational Aesthetics are two closely related fields. For some aspects they are similar, complementary for others, and sometimes completely disjoint.  ...  We re-use our graded relevance learning framework for video retrieval [10] , namely a semantic indexing system that can deal with multiple degrees of annotations.  ... 
doi:10.1145/2461466.2461532 dblp:conf/mir/Redi13 fatcat:5tu5dqztkjcrrfgseyxcba63ve

Using manual and automated annotations to search images by semantic similarity

João Magalhães, Stefan Rüger
2010 Multimedia tools and applications  
However, for full rank measures (MAP) in the real datasets (Flickr) retrieval by semantic similarity with automatic annotations is similar or better than amateur-level manual annotations.  ...  To assess these aspects we conducted experiments on a professional image dataset (Corel) and two amateur image datasets (one with 25,000 Flickr images and a second with 269,648 Flickr images) with a large  ...  Rasiwasia et al. proposed a framework to compute semantic similarity to rank images according to the submitted query example [24, 26] and show that the semantic space offers a better retrieval precision  ... 
doi:10.1007/s11042-010-0558-3 fatcat:aark2ay6p5clrfjetsjbtbvwzu

A novel framework for assessing the criticality of retrieved information

Ashwani Varshney, Yatin Kapoor, Vaishali Chawla, Vibha Gaur
2022 International Journal of Computing and Digital Systems  
Taking advantage of Deep Learning (DL) and Natural Language Processing (NLP) techniques, this paper proposes a novel framework for retrieving critical information from Twitter to manage emergencies effectively  ...  The proposed work was tested on a real-world dataset of Uttarakhand Floods that occurred in February 2021.  ...  Acknowledgment We thank the anonymous annotators for annotating the dataset utilized in the study. Moreover, we thank the anonymous reviewers for their valuable suggestions.  ... 
doi:10.12785/ijcds/1101100 fatcat:wz4uc236vret3c5i7otmmmmtcu

Bridging the Semantic Gap Between Image Contents and Tags

Hao Ma, Jianke Zhu, Michael Rung-Tsong Lyu, Irwin King
2010 IEEE transactions on multimedia  
Experimental analysis on a large Flickr dataset shows the effectiveness and efficiency of our proposed framework.  ...  text-based image retrieval, and image annotation.  ...  ACKNOWLEDGMENT The authors also would like to thank the reviewers and associate editor for their helpful comments.  ... 
doi:10.1109/tmm.2010.2051360 fatcat:zipoonbsibbd7pcmd7pvbz3mze

A hierarchical knowledge-based approach for retrieving similar medical images described with semantic annotations

Camille Kurtz, Christopher F. Beaulieu, Sandy Napel, Daniel L. Rubin
2014 Journal of Biomedical Informatics  
We propose a new framework that includes semantic features in images and that enables retrieval of similar images in large databases based on their semantic relations.  ...  Under this framework, retrieval accuracy of more than 0.96 was obtained on a 30-images dataset using the Normalized Discounted Cumulative Gain (NDCG) index that is a standard technique used to measure  ...  This project was funded in part by a grant from National Cancer Institute, National Institutes of Health, U01CA142555-01, R01-CA160251 and by a grant from GE Medical Systems.  ... 
doi:10.1016/j.jbi.2014.02.018 pmid:24632078 pmcid:PMC4058405 fatcat:movcgiinojdkpoiwemrx4oopai

Self-supervised learning of visual features through embedding images into text topic spaces [article]

Lluis Gomez, Yash Patel, Marçal Rusiñol, Dimosthenis Karatzas, C.V. Jawahar
2017 arXiv   pre-print
End-to-end training from scratch of current deep architectures for new computer vision problems would require Imagenet-scale datasets, and this is not always possible.  ...  For this we leverage the hidden semantic structures discovered in the text corpus with a well-known topic modeling technique.  ...  This work has been partially supported by the Spanish research project TIN2014-52072-P and the CERCA Programme/Generalitat de Catalunya.  ... 
arXiv:1705.08631v1 fatcat:c7pu7heiobcexhftqemuuye6pi
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