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Neural Document Expansion with User Feedback
2019
Proceedings of the 2019 ACM SIGIR International Conference on Theory of Information Retrieval - ICTIR '19
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This paper presents a neural document expansion approach (NeuDEF) that enriches document representations for neural ranking models. ...
NeuDEF harvests expansion terms from queries which lead to clicks on the document and weights these expansion terms with learned attention. ...
All neural ranking baselines leverage user feedback following Eq. 8. We implemented and compared with many document expansion baselines. ...
doi:10.1145/3341981.3344213
dblp:conf/ictir/YinXL019
fatcat:uexw6drg3bfohfghu4mjnlxoji
Incorporating Semantic Word Representations into Query Expansion for Microblog Information Retrieval
2019
Information Technology and Control
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In addition, we also combine the traditional pseudo-relevance feedback query expansion method with the proposed query expansion method. ...
To enhance microblog information retrieval, we propose a novel query expansion method to enrich user queries with semantic word representations. ...
[26] proposed to add user clicks as implicit feedback for secondary sorting of the document, and obtained better results. Kurland et al. ...
doi:10.5755/j01.itc.48.4.22487
fatcat:7nufcwuwabcyberduwvimkox4m
GQE-PRF: Generative Query Expansion with Pseudo-Relevance Feedback
[article]
2021
arXiv
pre-print
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Query expansion with pseudo-relevance feedback (PRF) is a powerful approach to enhance the effectiveness in information retrieval. ...
Recently, with the rapid advance of deep learning techniques, neural text generation has achieved promising success in many natural language tasks. ...
GQE-PRF Model
Model Overview Given an initial user query, we are aiming at generating related expansion terms with the benefits of both local relevant documents and pre-trained natural language generation ...
arXiv:2108.06010v1
fatcat:e3sjq7d345fqdmn2apazmibi6e
Incorporating agent based neural network model for adaptive meta-search
2005
Proceedings of the 43rd annual southeast regional conference on - ACM-SE 43
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This approach uses an adaptive agent based neural network model to improve the quality of the search results by incorporating user relevance feedback in to the system. ...
user queries. ...
Query Expansion Algorithm In this subsection, we describe our query expansion algorithm. After a user gives feedback, the top agent constructs a new DNF query from the feedback information. ...
doi:10.1145/1167350.1167376
dblp:conf/ACMse/XieMR05
fatcat:p7pwhjrbqvcmpk2ulvks2qw3b4
Deep Neural Network and Pseudo Relevance Feedback Based Query Expansion
2022
Computers Materials & Continua
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Vocabulary terms are obtained from the top "k" initially retrieved documents using the Pseudo relevance feedback model and then they are trained using the skip-gram model to find the expansion terms for ...
the user query. ...
The user has only a fuzzy idea about what he/she is looking for. Due to this retrieval system retrieves irrelevant documents along with relevant documents. ...
doi:10.32604/cmc.2022.022411
fatcat:d3jjldoysjh3rpj7ailiyndh7e
Pseudo-Relevance Feedback for Multiple Representation Dense Retrieval
[article]
2021
arXiv
pre-print
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Pseudo-relevance feedback mechanisms, from Rocchio to the relevance models, have shown the usefulness of expanding and reweighting the users' initial queries using information occurring in an initial set ...
Recently, dense retrieval -- through the use of neural contextual language models such as BERT for analysing the documents' and queries' contents and computing their relevance scores -- has shown a promising ...
In particular, Neural PRF uses neural ranking models, such as DRMM [13] and KNRM [33] , to score the similarity of a document to a top-ranked feedback document. ...
arXiv:2106.11251v1
fatcat:uq5qmuoxmrb5dovez2zemz4vb4
The paraphrase search assistant
1999
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval - SIGIR '99
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We present a new linguistic approach to the construction of terminological feedback for use in interactive query refinement. ...
Facet expansion: banking Term selection: "banking industry" Document selection: #6 Facet expansion: services Term selection: "financial services" Document selection: #1
: de500 Facet expansion: driver ...
There is some evidence from recent studies comparing "opaque" and "penetrable" relevance feedback suggesting that allowing end-users to interact directly with terminological feedback improves not only ...
doi:10.1145/312624.312670
dblp:conf/sigir/AnickT99
fatcat:6limkwgpvjchdaud2et56czt3e
HQE: A hybrid method for query expansion
2009
Expert systems with applications
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the most relevant web documents and their corresponding terms from these similar users' queries. ...
The HQE method employs a combination of ontology-based collaborative filtering and neural networks to improve query expansion. ...
Expansion terms employed are not based on frequencies in the top-ranked documents, similarly to local feedback, but on cooccurrences with the query terms. ...
doi:10.1016/j.eswa.2008.10.060
fatcat:y7xf5jxglrcopapaa32vbbx2da
RLIRank: Learning to Rank with Reinforcement Learning for Dynamic Search
2020
Proceedings of The Web Conference 2020
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2021 pre-print arXiv:2105.10124v1 fatcat:svlnzsjn3zehnpa2qzarypoyu4
To support this dynamic ranking paradigm effectively, search result ranking must incorporate both the user feedback received, and the information displayed so far. ...
To incorporate the user's feedback, we develop a word-embedding variation of the classic Rocchio Algorithm, to help guide the ranking towards the high-value documents. ...
Figure 1 : 1 Flow of Dynamic Search with user feedback. The returned results are dynamically re-ranked based on the user's feedback.
Figure 1 1 illustrates the dynamic search process. ...
doi:10.1145/3366423.3380047
dblp:conf/www/ZhouA20
fatcat:hivnsj2zlbdkjcbnhttmc3gh4y
Query expansion based on relevance feedback and latent semantic analysis
2014
Journal of Artificial Intelligence and Data Mining
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The method is evaluated and compared with the Rocchio relevance feedback. ...
This method which is a combination of relevance feedback and latent semantic analysis, finds the relative terms to the topics of user original query based on relevant documents selected by the user in ...
The proposed method consists of three steps: 1) User initial search, 2) User relevance feedback and 3) Query expansion. ...
doi:10.22044/jadm.2014.188
doaj:0fdc398bda9d47bdaddeebd63a7f04b6
fatcat:svg4p6mwm5dhlcttxpiqd2ubv4
Web document clustering using a hybrid neural network
2004
Applied Soft Computing
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This paper describes a method developed for the automatic clustering of World Wide Web documents, according to their relevance to the user's information needs, by using a hybrid neural network. ...
and the user. ...
The document clustering and ranking technique developed by us is meant to form an intelligent interface between the typical Web search engine and the user. ...
doi:10.1016/j.asoc.2004.02.003
fatcat:wxtx7t6fgjc5jgfb5tp3kiypnq
Feature Weighting in Finding Feedback Documents for Query Expansion in Biomedical Document Retrieval
2020
SN Computer Science
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This proposed approach uses an NLP-based feature weighting technique with classification and clustering method on the documents and identifies relevant documents for feedback. ...
Finding good feedback documents for query expansion is a well-known problem in the field of information retrieval. ...
The comparison of results of two feature weighting techniques with the results of original queries without expansion, expansion with relevance feedback and expansion with feedback document discovery without ...
doi:10.1007/s42979-020-0069-x
fatcat:gqczonzbcvc5fofu3dp7mc7dce
Query modification and expansion in a network with adaptive architecture
1991
Proceedings of the 14th annual international ACM SIGIR conference on Research and development in information retrieval - SIGIR '91
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This paper shows how a newtwork view of probabilistic information indexing and retrieval with components may implement query expansion and modification (based on user relevance feedback) by growing new ...
Experimental results with two collections and partial feedback confirm that the process can lead to much improved performance. Learning from irrelvant documents however was not effective. ...
Conclusion No Feedback I both will serve as basis for comparison modification with expansion for both relevant or irrelevant with feedback [CroR3] Croft, W. B (1983). ...
doi:10.1145/122860.122879
dblp:conf/sigir/Kwok91
fatcat:f6lgf2ajzncrnpuoal74hynigm
Rethinking Query Expansion for BERT Reranking
[chapter]
2020
Lecture Notes in Computer Science
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Recent studies have shown promising results of using BERT for Information Retrieval with its advantages in understanding the text content of documents and queries. ...
We find that traditional word-based query expansion is not entirely applicable, and provide insight into methods that produce better experimental results. ...
These allow users to more effectively express their information need and help systems to better disambiguate documents with similar-looking content. ...
doi:10.1007/978-3-030-45442-5_37
fatcat:yhwdokljpjc33p62t4frshefd4
Relevance and reinforcement in interactive browsing
2000
Proceedings of the ninth international conference on Information and knowledge management - CIKM '00
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We describe an interactive relevance feedback agent that analyzes the inter-document similarities and can help the user to locate the interesting information quickly. ...
We show how such an agent can be designed and improved by using neural networks and reinforcement learning. ...
The highest numbers reported earlier did not much exceed the interactive relevance feedback baseline with 10 terms expansion (Table 1 , column 3). ...
doi:10.1145/354756.354809
dblp:conf/cikm/Leuski00
fatcat:vrt77ofqo5b5noiefy3re2zgpy
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