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A Comparison of Deep Learning Based Query Expansion with Pseudo-Relevance Feedback and Mutual Information [chapter]

Mohannad ALMasri, Catherine Berrut, Jean-Pierre Chevallet
2016 Lecture Notes in Computer Science  
Recently, several Natural Language Processing methods, based on Deep Learning, are proposed for learning high quality vector representations of terms from large amounts of unstructured text data with billions  ...  Selecting expansion terms is challenging and requires a framework capable of extracting term relationships.  ...  We showed that deep learning vectors are a promising source for query expansion by comparing it with two e↵ective methods for query expansion: pseudo-relevance feedback and mutual information.  ... 
doi:10.1007/978-3-319-30671-1_57 fatcat:qqe45dm3cbfeleyh5jpw2bzjyu

Query Expansion Techniques for Information Retrieval: a Survey [article]

Hiteshwar Kumar Azad, Akshay Deepak
2017 arXiv   pre-print
With the ever increasing size of web, relevant information extraction on the Internet with a query formed by a few keywords has become a big challenge.  ...  To overcome this, query expansion (QE) plays a crucial role in improving the Internet searches, where the user's initial query is reformulated to a new query by adding new meaningful terms with similar  ...  Reference [10] proposed deep learning based QE technique and compared it with PRF and other expansion models; the results show a notable improvement over other techniques using various language models  ... 
arXiv:1708.00247v1 fatcat:42st2xre5ndejggyo7ighn2yau

Response Ranking with Deep Matching Networks and External Knowledge in Information-seeking Conversation Systems

Liu Yang, Minghui Qiu, Chen Qu, Jiafeng Guo, Yongfeng Zhang, W. Bruce Croft, Jun Huang, Haiqing Chen
2018 The 41st International ACM SIGIR Conference on Research & Development in Information Retrieval - SIGIR '18  
We incorporate external knowledge into deep neural models with pseudo-relevance feedback and QA correspondence knowledge distillation.  ...  In this paper, we propose a learning framework on the top of deep neural matching networks that leverages external knowledge for response ranking in information-seeking conversation systems.  ...  The results demonstrate that candidate response expansion with pseudo-relevance feedback could improve the ranking performance of responses in conversations.  ... 
doi:10.1145/3209978.3210011 dblp:conf/sigir/YangQQGZCHC18 fatcat:xt6767facjezpd6umj3ojrrgh4

Semantic concept-based query expansion and re-ranking for multimedia retrieval

Apostol (Paul) Natsev, Alexander Haubold, Jelena Tešić, Lexing Xie, Rong Yan
2007 Proceedings of the 15th international conference on Multimedia - MULTIMEDIA '07  
Three general approaches are illustrated for identifying relevant semantic concepts to a query-based on textual query analysis, visual content-based query modeling, and pseudorelevance feedback.  ...  We study the problem of semantic concept-based query expansion and re-ranking for multimedia retrieval.  ...  This approach is called pseudo-relevance feedback, or blind feedback [35] .  ... 
doi:10.1145/1291233.1291448 dblp:conf/mm/NatsevHTXY07 fatcat:lqjfylum3bgwtkepponnjx6f3i

Optimal Query Expansion Based on Hybrid Group Mean Enhanced Chimp Optimization Using Iterative Deep Learning

Ram Kumar, Kuldeep Narayan Tripathi, Subhash Chander Sharma
2022 Electronics  
This paper presents a hybrid group mean-based optimizer-enhanced chimp optimization (GMBO-ECO) algorithm for pseudo-relevance-based query expansion, whereby the actual queries are expanded with their related  ...  The proposed methodology has been compared to the state-of-the-art methods with and without a query expansion approach.  ...  Informed Consent Statement: Not applicable.  ... 
doi:10.3390/electronics11101556 fatcat:53iznxcukza3hor65ycm6py2tu

Fake News Data Collection and Classification: Iterative Query Selection for Opaque Search Engines with Pseudo Relevance Feedback [article]

Aviad Elyashar, Maor Reuben, Rami Puzis
2021 arXiv   pre-print
The proposed iterative query selection algorithm (IQS) interacts with the opaque search engine to iteratively improve the query.  ...  IQS is applied to automatically collect a large-scale fake news dataset of about 70K true and fake news items.  ...  [27] suggested a system that uses pseudo-relevance feedback and topic-based query expansion method.  ... 
arXiv:2012.12498v2 fatcat:4zwpqnweyjgqvitauj65o6qqfy

An adaptive term proximity based rocchio's model for clinical decision support retrieval

Min Pan, Yue Zhang, Qiang Zhu, Bo Sun, Tingting He, Xingpeng Jiang
2019 BMC Medical Informatics and Decision Making  
Pseudo Relevance Feedback (PRF) is a kind of classical query modification technique that has shown to be effective in many retrieval models and thus suitable for handling terse language and clinical jargons  ...  However, in the feedback document, the importance degree of candidate term and the co-occurrence relationship between a candidate term and a query term.  ...  The Rocchio's model is a classical framework to realize pseudo relevance feedback representation, which incorporates the information of pseudo relevance feedback in the first-pass retrieval [27] .  ... 
doi:10.1186/s12911-019-0986-6 pmid:31830960 pmcid:PMC6907113 fatcat:yvl5yreyzbchbg6lhskk4teo5i

Neural Information Retrieval: A Literature Review [article]

Ye Zhang, Md Mustafizur Rahman, Alex Braylan, Brandon Dang, Heng-Lu Chang, Henna Kim, Quinten McNamara, Aaron Angert, Edward Banner, Vivek Khetan, Tyler McDonnell, An Thanh Nguyen (+3 others)
2017 arXiv   pre-print
In this work, we survey the current landscape of Neural IR research, paying special attention to the use of learned representations of queries and documents (i.e., neural embeddings).  ...  Stemming from this tide of NN work, a number of researchers have recently begun to investigate NN approaches to Information Retrieval (IR).  ...  Additional Authors The following additional students at the University of Texas at Austin contributed indirectly to the writing of this literature review: Manu Agarwal, Edward Babbe, Anuparna Banerjee,  ... 
arXiv:1611.06792v3 fatcat:i2eqfj5l25epjcytgvifta4y4i

Information retrieval with query hypergraphs

Michael Bendersky
2012 SIGIR Forum  
His critical thinking, deep appreciation of the prior work, constant pursuit of advancing the state-of-the-art, and boundless intellectual curiosity had, and will continue to have, a profound impact on  ...  my work and my worldview.  ...  Pseudo-Relevance Feedback Query expansion using related terms or concepts has a long history of success in information retrieval.  ... 
doi:10.1145/2422256.2422273 fatcat:6qycajgmcvhlja7yehghwvsexi

Neural information retrieval: at the end of the early years

Kezban Dilek Onal, Ye Zhang, Ismail Sengor Altingovde, Md Mustafizur Rahman, Pinar Karagoz, Alex Braylan, Brandon Dang, Heng-Lu Chang, Henna Kim, Quinten McNamara, Aaron Angert, Edward Banner (+7 others)
2017 Information retrieval (Boston)  
Recent years have witnessed an explosive growth of research into NN-based approaches to information retrieval (IR). A significant body of work has now been created.  ...  A recent "third wave" of neural network (NN) approaches now delivers state-ofthe-art performance in many machine learning tasks, spanning speech recognition, computer vision, and natural language processing  ...  Acknowledgements We would like to thank Christophe van Gysel from the University of Amsterdam, for his valuable feedback and comments.  ... 
doi:10.1007/s10791-017-9321-y fatcat:plrhhwkppjgb7l5r5daiyryj4q

A review of ontology based query expansion

J. Bhogal, A. Macfarlane, P. Smith
2007 Information Processing & Management  
This paper examines the meaning of context in relation to ontology based query expansion and contains a review of query expansion approaches.  ...  The various query expansion approaches include relevance feedback, corpus dependent knowledge models and corpus independent knowledge models.  ...  Comparison of ontology-based query expansion techniques with relevance feedback techniques When we compare ontology based query expansion techniques with those that do not rely on knowledge bases there  ... 
doi:10.1016/j.ipm.2006.09.003 fatcat:thcrluuhuvbgrcqmc43amhwqsm

Semantic Mapping in Video Retrieval

Maaike H.T. de Boer
2018 SIGIR Forum  
Relevance feedback can be done in different ways: implicit, explicit and blind/pseudo. In implicit relevance feedback, implicit information, such 1.  ...  This is one of the architectures used in deep learning Data Source A source that collects (raw) data that has not been processed into valuable information, related to modality Deep Learning A branch in  ... 
doi:10.1145/3190580.3190606 fatcat:a7agjytxhng4na47sfv7xsoy2a

Getting Started with Neural Models for Semantic Matching in Web Search [article]

Kezban Dilek Onal, Ismail Sengor Altingovde, Pinar Karagoz, Maarten de Rijke
2016 arXiv   pre-print
We include a section on resources and best practices that we believe will help readers who are new to the area. We conclude with an assessment of the state-of-the-art and suggestions for future work.  ...  The vocabulary mismatch problem is a long-standing problem in information retrieval. Semantic matching holds the promise of solving the problem.  ...  experimental conditions, very much like the reliable information access (RIA) workshop that was run in the early 2000s to gain a deeper understanding of query expansion and pseudo relevance feedback  ... 
arXiv:1611.03305v1 fatcat:agdgj7allbczxcyteuomswn574

A Systematic Literature Review of Automated Query Reformulations in Source Code Search [article]

Mohammad Masudur Rahman, Chanchal K. Roy
2021 arXiv   pre-print
Then they execute the query with a code search engine (e.g., Lucene) and attempt to find out the exact locations within the software code that need to be changed.  ...  As a part of change implementation, they often choose a few important keywords from a change request as an ad hoc query.  ...  [118] Query expansion using Rocchio's method and pseudo-relevance feedback from Stack Overflow S35 Huang et al.  ... 
arXiv:2108.09646v1 fatcat:7eweftlz4bff5gitbru7et5644

Web Image Re-Ranking UsingQuery-Specific Semantic Signatures

Xiaogang Wang, Shi Qiu, Ke Liu, Xiaoou Tang
2014 IEEE Transactions on Pattern Analysis and Machine Intelligence  
Given a query keyword, a pool of images are first retrieved based on textual information.  ...  By asking the user to select a query image from the pool, the remaining images are re-ranked based on their visual similarities with the query image.  ...  ACKNOWLEDGEMENT This work is partially supported by Hong Kong SAR through RGC project 416510 and by Guangdong Province through Introduced Innovative R&D Team of Guangdong Province 201001D0104648280.  ... 
doi:10.1109/tpami.2013.214 pmid:26353202 fatcat:uohsjl4h6jegfcnyr7nr26rtly
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