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Cross-media Scientific Research Achievements Query based on Ranking Learning
[article]
2022
arXiv
pre-print
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In view of the above background, this paper expounds on the research status from four aspects: characteristic learning of scientific research results, cross-media research results query, ranking learning ...
of scientific research results, and cross-media scientific research achievement query system. ...
At present, the research on data query of cross-media scientific research results is not mature, so how to effectively learn the semantic information of cross-media scientific research results has become ...
arXiv:2204.12121v1
fatcat:z7aosynjdvch7jync3vddoyouq
Cross-Modal Retrieval using Random Multimodal Deep Learning
2019
JOURNAL OF MECHANICS OF CONTINUA AND MATHEMATICAL SCIENCES
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This paper proposed a Random Multimodal Deep Learning (RMDL) based Recurrent Neural Network (RNN) for cross-media retrieval. ...
Since strongly supervised strategies use the class labels that might be missing in practice, this paper mainly concentrates on weakly managed learning for cross-media recovery, in which only textimage ...
Mean Rank for Text Query This section presents the performance of the proposed RMDL-based retrieval method on Twitter100k. ...
doi:10.26782/jmcms.2019.04.00016
fatcat:jkpne7zeenbolhyllbuhgcqwjy
Internet cross-media retrieval based on deep learning
2017
Journal of Visual Communication and Image Representation
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Based on the traditional content of cross media learning research, we can
. 1 .1. ...
In this paper, we propose a real time internet cross-media retrieval based on deep learning. ...
doi:10.1016/j.jvcir.2017.02.011
fatcat:jxefua77mrf63i57ikpkhwvsbm
A New Benchmark and Approach for Fine-grained Cross-media Retrieval
2019
Proceedings of the 27th ACM International Conference on Multimedia - MM '19
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2019 pre-print arXiv:1907.04476v1 fatcat:w7juuszan5fy5kuda7ppwlu5kyOther Versions
Cross-media retrieval is to return the results of various media types corresponding to the query of any media type. Existing researches generally focus on coarse-grained cross-media retrieval. ...
However, few researches focus on fine-grained cross-media retrieval, which is a highly challenging and practical task. ...
It will encourage further researches on fine-grained cross-media retrieval. (2) A new approach -We have proposed the FGCrossNet, which is a uniform deep model to simultaneously learn the common representations ...
doi:10.1145/3343031.3350974
dblp:conf/mm/HePX19
fatcat:3h54vm5hobblphrwapxsyywyf4
Mining and searching association relation of scientific papers based on deep learning
[article]
2022
arXiv
pre-print
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Therefore, the research on mining and searching the association relationship of scientific papers based on deep learning has far-reaching practical significance. ...
technological big data and help to design applications to serve scientific researchers. ...
Based on interest ranking, relevance ranking, feedback mechanism, and ranking optimization mechanism, one can realize the retrieval and sorting of scientific papers and efficient partition indexing of ...
arXiv:2204.11488v1
fatcat:zxwvpnids5bopberzumjofgupq
Second order probabilistic models for within-document novelty detection in academic articles
2014
Proceedings of the 37th international ACM SIGIR conference on Research & development in information retrieval - SIGIR '14
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Incorporating Query-Specific Feedback Into
Learning-To-Rank Models
Ethem Can, Bruce Croft, R. Manmatha
3. Diversifying Query Suggestions Based on
Query Documents
Youngho Kim, Bruce Croft
4. ...
Item Group Based Pairwise Preference Learning for Personalized Ranking Shuang Qiu, Jian Cheng, Ting Yuan, Cong Leng, Hanqing Lu 100. Where Not to Go? ...
doi:10.1145/2600428.2609520
dblp:conf/sigir/ParkS14
fatcat:ye2rtri2xjbyrjvkkzgt7srcfu
A Semantic Approach to Cross-Disciplinary Research Collaboration
2012
International Journal of Emerging Technologies in Learning (iJET)
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We propose an environment that improves the scientific research and learning process by allowing researchers to efficiently browse the information and concepts represented as learning objects. ...
The research data is extracted from many online resources and Social Media. We implement learning objects as an abstraction of the semantically modeled research data. ...
ACKNOWLEDGMENT The research activities that have been described in this paper were funded by Ghent University, the Social Learning Department at Graz University of Technology, the Interdisciplinary Institute ...
doi:10.3991/ijet.v7is2.2331
fatcat:l3ykdo4bsfh4nnchw2u6ig55v4
Online social image ranking in diversified preferences
2020
EURASIP Journal on Image and Video Processing
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By re-ranking the rank output of OMKR based on each preference ranking model, we obtain a set of ranking lists encoding different potential aspects of user preference. ...
By optimizing the ranking performance with multi-dimensional queries, the semantic consistency between the image ranking and textual query input is directly maximized without relying on the intermediate ...
It takes as input a set of training queries as well as a set of ranked online social media images, and outputs a trained model to achieve high ranking performance on new queries. ...
doi:10.1186/s13640-020-00540-4
fatcat:mkva766gh5cdxbztsbcfiz6lse
Cross-Media Similarity Evaluation for Web Image Retrieval in the Wild
[article]
2018
arXiv
pre-print
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Image retrieval experiments on the challenging Clickture dataset show that the proposed text2image compares favorably to recent deep learning based alternatives. ...
Queries are automatically categorized according to the proposed query visualness measure, and later connected to the evaluation of multiple cross-media similarity models on three test sets. ...
Yuxiao Hu) for evaluating our results on IRC-MM15-test. The authors also thank the anonymous reviewers for their insightful comments. ...
arXiv:1709.01305v2
fatcat:adfiz723k5d7vopelt2l7vriri
SciEv: Finding Scientific Evidence Papers for Scientific News
[article]
2022
arXiv
pre-print
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The system achieves a P@1=50%, P@5=71%, and P@10=74% when it uses a TFIDF-based text representation. The transformer-based re-ranker achieves a comparable performance but costs twice as much time. ...
In the past decade, many scientific news media that report scientific breakthroughs and discoveries emerged, bringing science and technology closer to the general public. ...
We trained a multi-disciplinary transformer-based transfer-learning model that beats other heuristic and learning-based models, achieving an F1=0.93-1. ...
arXiv:2205.00126v1
fatcat:bouw4n5xxvdftoyko5nd3dvsga
High diversity transforms multimedia information retrieval into a cross-cutting field
2007
SIGMOD record
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It has address algorithms for region-based query systems with semantics localization, efficient queries by example, query by concepts, aspects of the on-line learning of user queries, propagation of semantic ...
Liu et al. explored image annotation based on manifold ranking. Gao and Fan proposed a multilevel image annotation approach using salient objects and concept ontology. ...
doi:10.1145/1276301.1276315
fatcat:cdowdmpllbcf3mea7m2wotbuyq
Content Facets For Individual Information Needs In Media
2018
Zenodo
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From the media consumer perspective, navigating the haystack of information produced by media as well as finding content that meets ones quality demands is challenging. ...
Several proposed content facets have successfully been implemented in APA Labs, a Web-based framework for faceted search in traditional and social me- dia. ...
The uogTr group used a Machine Learning approach based on a Voting Model as well as a learning-to-rank method, specifically the AdaRank to learn ranking models for the fact inclinations [Macdonald et ...
doi:10.5281/zenodo.1195993
fatcat:ce3ljnthjfhkpir3y4atnnlicy
Content Facets For Individual Information Needs In Media
2018
Zenodo
Preserved Fulltext
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From the media consumer perspective, navigating the haystack of information produced by media as well as finding content that meets ones quality demands is challenging. ...
Several proposed content facets have successfully been implemented in APA Labs, a Web-based framework for faceted search in traditional and social me- dia. ...
The uogTr group used a Machine Learning approach based on a Voting Model as well as a learning-to-rank method, specifically the AdaRank to learn ranking models for the fact inclinations [Macdonald et ...
doi:10.5281/zenodo.1196397
fatcat:udr3736ejbek5lzl34tu4g4ppq
Gathering training sample automatically for social event visual modeling
2012
Proceedings of the 2012 international workshop on Socially-aware multimedia - SAM '12
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In recent years, the emergence of social media on the Internet has derived many of interesting research and applications. ...
A novel ranking approach is devised to select a set of negative samples. The visual event models are learned from automatically collected samples using SVM. ...
Common tags, along with their corresponding photos, are identified based on a novel approach inspired from learning to rank [10] , which we detail in section 3.2. ...
doi:10.1145/2390876.2390881
dblp:conf/mm/LiuH12
fatcat:4q565k2nmzazzpunzs5z74swly
Guest Editorial: Large-Scale Multimedia Content Analysis on Social Media
2016
Multimedia tools and applications
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.), where people record, share/broadcast, and comment on media content, i.e., images and videos, leading to an accelerated proliferation of social media on the Internet. ...
The rapid increase of social media has raised numerous new research challenges to multimedia content analysis. ...
Two image ranking methods, i.e., distance weights based re-ranking and bit importance based re-ranking methods are developed to rerank the hashing indexed images for the given query. ...
doi:10.1007/s11042-016-3255-z
fatcat:t6pi6bjigfg57dj5aaa7hbafgy
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