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Co-reranking by mutual reinforcement for image search

Ting Yao, Tao Mei, Chong-Wah Ngo
2010 Proceedings of the ACM International Conference on Image and Video Retrieval - CIVR '10  
Observing that multi-modality cues carry complementary relevant information, we propose the idea of co-reranking for image search, by jointly exploring the visual and textual information.  ...  Co-reranking couples two random walks, while reinforcing the mutual exchange and propagation of information relevancy across different modalities.  ...  Figure 2 : 2 The approach overview of co-reranking for image search: (a) initial ranked list obtained by the text-based search; (b) co-reranking by mutual reinforcement of visual and text information via  ... 
doi:10.1145/1816041.1816048 dblp:conf/civr/YaoMN10 fatcat:6jeidijmmbbm3cqeb7sx5jwpam

Circular Reranking for Visual Search

Ting Yao, Chong-Wah Ngo, Tao Mei
2013 IEEE Transactions on Image Processing  
This paper proposes a new reranking algorithm, named circular reranking, that reinforces the mutual exchange of information across multiple modalities for improving search performance, following the philosophy  ...  The problem nevertheless is not trivial especially when there are multiple features or modalities to be considered for search, which often happens in image and video retrieval.  ...  (c) Circular reranking: iteratively updates the image ranks by circular mutual reinforcement (this paper).  ... 
doi:10.1109/tip.2012.2236341 pmid:23288334 fatcat:frzjcivr5rfm3c4bnx3nmqnutm

A reranking approach for context-based concept fusion in video indexing and retrieval

Lyndon S. Kennedy, Shih-Fu Chang
2007 Proceedings of the 6th ACM international conference on Image and video retrieval - CIVR '07  
patterns with detection results for hundreds of other concepts, thereby refining and reranking the initial video search result.  ...  The approach takes initial search results from established video search methods (which typically are conservative in usage of concept detectors) and mines these results to discover and leverage co-occurrence  ...  ACKNOWLEDGMENTS This research was funded in part by the U.S. Government VACE program. The views and conclusions are those of the authors, not of the US Government or its agencies.  ... 
doi:10.1145/1282280.1282331 dblp:conf/civr/KennedyC07 fatcat:7gwjpfya7reetji5ob5jfofffu

Harvesting visual concepts for image search with complex queries

Liqiang Nie, Shuicheng Yan, Meng Wang, Richang Hong, Tat-Seng Chua
2012 Proceedings of the 20th ACM international conference on Multimedia - MM '12  
These mutually reinforced layers are established among the complex query and its involved visual concepts, by harnessing the contents of images and their associated textual cues.  ...  This paper presents a scheme to enhance web image reranking for complex queries by fully exploring the information from simple visual concepts.  ...  The three layers are strongly connected by a probabilistic model. The layers mutually reinforce each other to facilitate the estimation of relevance scores for new reanking list generation.  ... 
doi:10.1145/2393347.2393363 dblp:conf/mm/NieYWHC12 fatcat:q2jm5vohlnfb5nfhnxhyqn7w6i

Multi-Level Interaction Reranking with User Behavior History

Yunjia Xi, Weiwen Liu, Jieming Zhu, Xilong Zhao, Xinyi Dai, Ruiming Tang, Weinan Zhang, Rui Zhang, Yong Yu
2022 Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval  
We design a novel SLAttention structure for modeling the set-to-list interactions with personalized long-short term interests.  ...  Lastly, estimating the reranking score on the ordered initial list before reranking may lead to the early scoring problem, thereby yielding suboptimal reranking performance.  ...  The work is also sponsored by Huawei Innovation Research Program. We thank MindSpore [1], a new deep learning computing framework, for the partial support of this work.  ... 
doi:10.1145/3477495.3532026 fatcat:7bmfyvhwn5c4hhion4nfm5hp4u

Multi-Level Interaction Reranking with User Behavior History [article]

Yunjia Xi, Weiwen Liu, Jieming Zhu, Xilong Zhao, Xinyi Dai, Ruiming Tang, Weinan Zhang, Rui Zhang, Yong Yu
2022 arXiv   pre-print
We design a novel SLAttention structure for modeling the set-to-list interactions with personalized long-short term interests.  ...  Lastly, estimating the reranking score on the ordered initial list before reranking may lead to the early scoring problem, thereby yielding suboptimal reranking performance.  ...  The work is also sponsored by Huawei Innovation Research Program. We thank MindSpore [1], a new deep learning computing framework, for the partial support of this work.  ... 
arXiv:2204.09370v1 fatcat:gsvuqbxj4bhcvm33m5kmh7n32i

Unified entity search in social media community

Ting Yao, Yuan Liu, Chong-Wah Ngo, Tao Mei
2013 Proceedings of the 22nd international conference on World Wide Web - WWW '13  
The search for entities is the most common search behavior on the Web, especially in social media communities where entities (such as images, videos, people, locations, and tags) are highly heterogeneous  ...  To infer the strength of intrarelations, we propose a circular propagation scheme, which reinforces the mutual exchange of information across different entity types in a cyclic manner.  ...  [12] utilized a co-clustering method to extract latent interest dimensions, and rerank the images by coming latent interest based user Integral multi-level graph with three types of entity sets, i.e  ... 
doi:10.1145/2488388.2488515 dblp:conf/www/YaoLNM13 fatcat:j46utwq46favxescus6qtmcika

Teaching Machines to Converse [article]

Jiwei Li
2020 arXiv   pre-print
This dates back to Alan Turing's epoch-making work in the early 1950s, which proposes that a machine's intelligence can be tested by how well it, the machine, can fool a human into believing that the machine  ...  interactive question-answering dialogue systems by (a) giving the agent the ability to ask questions and (b) training a conversation agent through interactions with humans in an online fashion, where  ...  The output is generated using the mutual information model (Li et al., 2016a) in which an N-best list is first obtained using beam search based on p(t|s) and reranked by linearly combining the backward  ... 
arXiv:2001.11701v1 fatcat:ym74xbxnfrea7aaj7y5opnxopy

Optimizing web search using web click-through data

Gui-Rong Xue, Hua-Jun Zeng, Zheng Chen, Yong Yu, Wei-Ying Ma, WenSi Xi, WeiGuo Fan
2004 Proceedings of the Thirteenth ACM conference on Information and knowledge management - CIKM '04  
In this paper, we propose a novel iterative reinforced algorithm to utilize the user click-through data to improve search performance.  ...  User click-through data can be used to introduce more accurate description (metadata) for web pages, and to improve the search performance.  ...  Figure 3 . 3 Example of our iterative algorithmHere, similarity of queries and similarity of web pages are mutually reinforcing notions:Web pages are similar if they are visited by similar queries.Queries  ... 
doi:10.1145/1031171.1031192 dblp:conf/cikm/XueZCYMXF04 fatcat:c7usbwolxvg6rg37kgexspf6vu

A Dual-Network Progressive Approach to Weakly Supervised Object Detection

Xuanyi Dong, Deyu Meng, Fan Ma, Yi Yang
2017 Proceedings of the 2017 ACM on Multimedia Conference - MM '17  
Further, to leverage the mutual bene ts of the two tasks, the two neural networks are jointly trained and reinforced iteratively in a progressive manner, starting with easy and reliable instances and then  ...  A typical approach to WSOD is to 1) generate a series of region proposals for each image and assign the image-level label to all the proposals in that image; 2) train a classi er using all the proposals  ...  and instance selection (for classi er updates) can be reinforced by each other.  ... 
doi:10.1145/3123266.3123455 dblp:conf/mm/DongMMY17 fatcat:uybobtsuqvg5bnv5ajqcqrfot4

Review for Feature Based Image Re-Ranking

Nishakumari Lodha, Minakshi Somanath Bagad
unpublished
This paper suggests a new kind of reranking algorithm, the circular reranking, that supports the mutual exchange of information across multiple modalities for improving search performance and follows the  ...  Image re-ranking, as an effective way to improve the results of web-based image search however the problem is not trivial especially when we are considering multiple features or modalities for search in  ...  Co-Reranking Co-reranking for image search [4] jointly explores the visual and textual information.  ... 
fatcat:6stlueetlncg7pycopey35sg34

Pretrained Transformers for Text Ranking: BERT and Beyond [article]

Jimmy Lin, Rodrigo Nogueira, Andrew Yates
2021 arXiv   pre-print
There are two themes that pervade our survey: techniques for handling long documents, beyond typical sentence-by-sentence processing in NLP, and techniques for addressing the tradeoff between effectiveness  ...  Although the most common formulation of text ranking is search, instances of the task can also be found in many natural language processing applications.  ...  Acknowledgements This research was supported in part by the Canada First Research Excellence Fund and the Natural Sciences and Engineering Research Council (NSERC) of Canada.  ... 
arXiv:2010.06467v3 fatcat:obla6reejzemvlqhvgvj77fgoy

Online image classifier learning for Google image search improvement

Yuchai Wan, Xiabi Liu, Jie, Yunpeng Chen
2011 2011 IEEE International Conference on Information and Automation  
The images returned by Google are used to learn a statistical binary classifier for measuring their relevance to the query. The learning process includes three stages.  ...  This paper proposes a content based method to improve image search results from Google search engine.  ...  [15] proposed the idea of co-reranking for image search, by coupling two random walks for visual and textual information, while reinforcing the mutual exchange and propagation of information relevancy  ... 
doi:10.1109/icinfa.2011.5948971 fatcat:l4sjpmworre73dlbtyzdo35zyu

DOLG: Single-Stage Image Retrieval with Deep Orthogonal Fusion of Local and Global Features [article]

Min Yang, Dongliang He, Miao Fan, Baorong Shi, Xuetong Xue, Fu Li, Errui Ding, Jizhou Huang
2021 arXiv   pre-print
A common image retrieval practice is to firstly retrieve candidate images via similarity search using global image features and then re-rank the candidates by leveraging their local features.  ...  Specifically, we propose a Deep Orthogonal Local and Global (DOLG) information fusion framework for end-to-end image retrieval.  ...  Though state-of-the-art performance has been achieved by previous two-stage solutions, they need to rank images twice, and the second reranking stage is conducted using the expensive RANSAC [13] or AMSK  ... 
arXiv:2108.02927v2 fatcat:goywykicubgaxo3ypommsoesc4

A comparative survey of Personalised Information Retrieval and Adaptive Hypermedia techniques

Ben Steichen, Helen Ashman, Vincent Wade
2012 Information Processing & Management  
A key driver for next generation web information retrieval systems is becoming the degree to which a user's search and presentation experience is adapted to individual user properties and contexts of use  ...  PIR typically aims to bias search results towards more personally relevant information by modifying traditional document ranking algorithms.  ...  Acknowledgements This research is supported by the Science Foundation Ireland (Grant 07/CE/I1142) as part of the Centre for Next Generation Localisation (http://www.cngl.ie) at Trinity College Dublin.  ... 
doi:10.1016/j.ipm.2011.12.004 fatcat:tkohqt4rijenzohmnqrwckp4na
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