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Incorporating Semantic Word Representations into Query Expansion for Microblog Information Retrieval

Bo Xu, Hongfei Lin, Yuan Lin, Kan Xu, Lin Wang, Jiping Gao
2019 Information Technology and Control  
In addition, we also combine the traditional pseudo-relevance feedback query expansion method with the proposed query expansion method.  ...  In this sense, we represent keywords in user queries as vectors, sum all the keyword vectors, and use the obtained query vectors to select the expansion words.  ...  PSeudo-Relevance feedback).  ... 
doi:10.5755/j01.itc.48.4.22487 fatcat:7nufcwuwabcyberduwvimkox4m

Temporal feedback for tweet search with non-parametric density estimation

Miles Efron, Jimmy Lin, Jiyin He, Arjen de Vries
2014 Proceedings of the 37th international ACM SIGIR conference on Research & development in information retrieval - SIGIR '14  
Temporal feedback improves over standard lexical feedback (with and without human judgments), illustrating that temporal relevance signals exist independently of document content.  ...  We explore this question in the context of tweet search and temporal feedback: starting with an initial set of results from a baseline retrieval model, we estimate the temporal density of relevant documents  ...  From the top k reranked documents, estimate feedback models: in the pseudo-relevance feedback case, this involves selecting the top k documents and assuming that they are relevant. 3 Training γ led to  ... 
doi:10.1145/2600428.2609575 dblp:conf/sigir/EfronLHV14 fatcat:7keb47pfyrcozfaex47te42hae

Estimation and use of uncertainty in pseudo-relevance feedback

Kevyn Collins-Thompson, Jamie Callan
2007 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval - SIGIR '07  
Existing pseudo-relevance feedback methods typically perform averaging over the top-retrieved documents, but ignore an important statistical dimension: the risk or variance associated with either the individual  ...  We find that resampling documents helps increase individual feedback model precision by removing noise terms, while sampling from the query improves robustness (worst-case performance) by emphasizing terms  ...  [17] proposed an approach to improving the robustness of pseudo-relevance feedback using a method they call selective sampling.  ... 
doi:10.1145/1277741.1277795 dblp:conf/sigir/Collins-ThompsonC07 fatcat:3grvnr7a3ze7rnzwszwnvpz33i

Query expansion using path-constrained random walks

Jianfeng Gao, Gu Xu, Jinxi Xu
2013 Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval - SIGIR '13  
The method is shown to be generic in that it covers most of the popular QE models as special cases and flexible in that it provides a principled mathematical framework in which a wide variety of information  ...  The methods based on automatic relevance feedback (e.g., explicit feedback and pseudo relevance feedback (PRF)) have been proved to be useful for improving the performance of IR on TREC datasets [10,  ...  It is also encouraging to see that its relevant document (www.acmebread.com) is ranked top in its pseudo-relevant document set obtained via similar queries (RD1).  ... 
doi:10.1145/2484028.2484058 dblp:conf/sigir/GaoXX13 fatcat:tizvpq6w4beltp5d2lfowht2xa

SalFBNet: Learning Pseudo-Saliency Distribution via Feedback Convolutional Networks [article]

Guanqun Ding, Nevrez Imamoglu, Ali Caglayan, Masahiro Murakawa, Ryosuke Nakamura
2022 arXiv   pre-print
Furthermore, we present a novel Selective Fixation and Non-Fixation Error (sFNE) loss to make proposed feedback model better learn distinguishable eye-fixation-based features.  ...  We first use the proposed feedback model to learn saliency distribution from pseudo-ground-truth. Afterwards, we fine-tune the feedback model on existing eye-fixation datasets.  ...  In this experiment, we use a mixture training set with Pseudo-Saliency (900 samples) and MIT1003 (900 samples) for fine-tuning.  ... 
arXiv:2112.03731v2 fatcat:5w4k3s6fvramfkacrr44okb5c4

Unsupervised Dual-Cascade Learning with Pseudo-Feedback Distillation for Query-based Extractive Summarization [article]

Haggai Roitman, Guy Feigenblat, David Konopnicki, Doron Cohen, Odellia Boni
2018 arXiv   pre-print
To this end, Dual-CES employs a two-step dual-cascade optimization approach with saliency-based pseudo-feedback distillation.  ...  By distilling saliency-based pseudo-feedback between step transitions, Dual-CES manages to better utilize the CE-method for selecting a more promising subset of sentences.  ...  As a future work, we would like to learn to distill from additional pseudo-feedback sources.  ... 
arXiv:1811.00436v1 fatcat:7hmsm37cybafhetflrl5htp4m4

A unified optimization framework for robust pseudo-relevance feedback algorithms

Joshua V. Dillon, Kevyn Collins-Thompson
2010 Proceedings of the 19th ACM international conference on Information and knowledge management - CIKM '10  
We present a flexible new optimization framework for finding effective, reliable pseudo-relevance feedback models that unifies existing complementary approaches in a principled way.  ...  Acknowledgements We thank Guy Lebanon for his valuable feedback, Tao Tao for helpful discussions of the TZ model, and several anonymous reviewers for their comments. References  ...  Finally, pseudo-relevance feedback can be seen as an instance of a broader feature selection problem under uncertainty, so better techniques for pseudo-relevance feedback may lead to better, more generally  ... 
doi:10.1145/1871437.1871573 dblp:conf/cikm/DillonC10 fatcat:w3r557nwdrdv7cb4q4a3xvjxu4

Fast Interactive Information Retrieval with Sampling-Based MDS on GPU Architectures [chapter]

Hasmik Osipyan, April Morton, Stéphane Marchand-Maillet
2014 Lecture Notes in Computer Science  
Relevance feedback algorithms improve content-based image retrieval (CBIR) systems by effectively using relevant/non-relevant images labeled by users.  ...  In this paper, we suggest a fast interactive interface for CBIR which includes the conventional ranked list view along with two additional views based on fast kmeans clustering and fast sampling-based  ...  Interactive Information Access (MU-MIA) via the Swiss State Secretariat for Education and Research (SER grant C11.0043).  ... 
doi:10.1007/978-3-319-12979-2_9 fatcat:63wpip2rd5amrmxja3dx4ospju

SamWalker++: recommendation with informative sampling strategy [article]

Can Wang, Jiawei Chen, Sheng Zhou, Qihao Shi, Yan Feng, Chun Chen
2021 arXiv   pre-print
. (2) To handle massive volume of the unobserved feedback data, most of the existing methods rely on stochastic inference and data sampling strategies.  ...  Recommendation from implicit feedback is a highly challenging task due to the lack of reliable negative feedback data.  ...  Then we add the feedback data of user u on these selected items into sampled set S. (2) With probability (1 − c), we continue our random walk.  ... 
arXiv:2011.07734v2 fatcat:viztewi3hvhpnoklxvbqvd62we

Improving pseudo-relevance feedback in web information retrieval using web page segmentation

Shipeng Yu, Deng Cai, Ji-Rong Wen, Wei-Ying Ma
2003 Proceedings of the twelfth international conference on World Wide Web - WWW '03  
By using our VIPS algorithm to assist the selection of query expansion terms in pseudo-relevance feedback in web information retrieval, we achieve 27% performance improvement on Web Track dataset.  ...  Step 4: Expansion Term Selection We use an approach similar to the traditional pseudo-relevance feedback algorithm to select expansion terms.  ...  Pseudo-relevance feedback, also known as local feedback or blind feedback, is a technique commonly used to improve retrieval performance [3, 10] .  ... 
doi:10.1145/775152.775155 dblp:conf/www/YuCWM03 fatcat:n3lcmfafxvakhbwerq6bfzcmrm

Improving pseudo-relevance feedback in web information retrieval using web page segmentation

Shipeng Yu, Deng Cai, Ji-Rong Wen, Wei-Ying Ma
2003 Proceedings of the twelfth international conference on World Wide Web - WWW '03  
By using our VIPS algorithm to assist the selection of query expansion terms in pseudo-relevance feedback in web information retrieval, we achieve 27% performance improvement on Web Track dataset.  ...  Step 4: Expansion Term Selection We use an approach similar to the traditional pseudo-relevance feedback algorithm to select expansion terms.  ...  Pseudo-relevance feedback, also known as local feedback or blind feedback, is a technique commonly used to improve retrieval performance [3, 10] .  ... 
doi:10.1145/775153.775155 fatcat:lypjpteijnaq3eglyg5wb7dy24

Age-differences in cognitive flexibility when overcoming a preexisting bias through feedback

Cristina G. Wilson, Amy T. Nusbaum, Paul Whitney, John M. Hinson
2017 Journal of Clinical and Experimental Neuropsychology  
Age-differences in task performance were based on differences in learning and corresponding representations of task-relevant information. ARTICLE HISTORY  ...  Results: Both older and younger adults demonstrated flexibility by reducing the impact of bias over trials, but younger adults had better performance overall.  ...  In sum, our findings provide converging evidence that age-related changes in the learning of relevant information impact the ability to flexibly overcome a preexisting bias.  ... 
doi:10.1080/13803395.2017.1398311 pmid:29161963 fatcat:rookyolxznbhhnouovjunilyby

Cognitive distortions mediate depression and affective response to social acceptance and rejection

Justin D. Caouette, Amanda E. Guyer
2016 Journal of Affective Disorders  
At Visit 2 they completed self-reports of depressive and social anxiety symptoms, and cognitive flexibility, then received acceptance or rejection feedback from each peer and rated their affective response  ...  Limitations-A community sample was used to assess depression. Rumination and current mood state were omitted as potential predictors of affective response.  ...  Feedback was pseudo-randomized, with participants receiving equal numbers of acceptances and rejections by individuals from each selection bin and by gender.  ... 
doi:10.1016/j.jad.2015.11.015 pmid:26625091 pmcid:PMC4745658 fatcat:oim5a2anabcl3dkjui2gfvs6e4

Open Source Software for Efficient and Transparent Reviews [article]

Rens van de Schoot, Jonathan de Bruin, Raoul Schram, Parisa Zahedi, Jan de Boer, Felix Weijdema, Bianca Kramer, Martijn Huijts, Maarten Hoogerwerf, Gerbrich Ferdinands, Albert Harkema, Joukje Willemsen (+5 others)
2020 arXiv   pre-print
This is error prone and inefficient because of extremely imbalanced data: only a fraction of the screened studies is relevant.  ...  Setting up a project, selecting a dataset and finding prior knowledge is now more intuitive and flexible.  ...  In one 3.5-hour session, the participants used the software and provided feedback via unstructured interviews and group discussions.  ... 
arXiv:2006.12166v3 fatcat:e2veqi6y6rgf7mpst2qsxgnj74

Informatics in Radiology (infoRAD)

Paul F. Whelan, Robert J. T. Sadleir, Ovidiu Ghita
2004 Radiographics  
A wide range of computer aided diagnostic sample applications will also be presented to illustrate the flexibility of the environment.  ...  This additional freely available plug-in features, automatic source code generation, compilation with full error feedback and dynamic algorithm updates.  ...  This is achieved by selecting the relevant compile option from the 'Project' menu.  ... 
doi:10.1148/rg.246045021 pmid:15537985 fatcat:5i5paiyl6fde3a2vhnwriqrbfa
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