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Biomedical Document Retrieval for Clinical Decision Support System
2018
Proceedings of ACL 2018, Student Research Workshop
In this work, we are focusing on biomedical document retrieval from literature for clinical decision support systems. ...
We compare statistical and NLP based approaches of query reformulation for biomedical document retrieval. Also, we have modeled the biomedical document retrieval as a learning to rank problem. ...
Here, we have used terrier plateform for the experiments. Summary part of the query is used for retrieval with top 10 and 50 top documents for feedback in expansion. ...
doi:10.18653/v1/p18-3012
dblp:conf/acl/Sankhavara18
fatcat:ggpycr4cfvckrl7j4ddy733hum
Feature Weighting in Finding Feedback Documents for Query Expansion in Biomedical Document Retrieval
2020
SN Computer Science
This paper describes a novel approach for finding relevant documents for feedback in query expansion for biomedical document retrieval. ...
The experiments performed on CDS 2014, 2015 and 2016 datasets show that the feature weighting in finding feedback documents for query expansion approach gives good results as compared to the results of ...
The fusion of automatic and manual feedback for query expansion in biomedical information retrieval experiments shows that manual feedback helps to improve the performance of biomedical IR systems [16 ...
doi:10.1007/s42979-020-0069-x
fatcat:gqczonzbcvc5fofu3dp7mc7dce
Document Retrieval for Precision Medicine Using a Deep Learning Ensemble Method
2021
JMIR Medical Informatics
As shown in the experiments, the strategies we used in the initial retrieval phase such as query expansion and query boosting are effective. ...
Methods In the initial retrieval stage, we supplemented query terms through query expansion strategies and applied query boosting to obtain an initial ranking list of relevant documents. ...
Query Expansion Experiment To explore the impact of query expansion on retrieval performance, we conducted corresponding experiments with different expansion strategies. ...
doi:10.2196/28272
pmid:34185006
fatcat:36l77khdnncn7pngfnolqletnq
Applying Biomedical Ontologies on Semantic Query Expansion
2009
Nature Precedings
This poster presents an ongoing work on using biomedical ontologies to improve efficiency on information retrieval. ...
Semantic Query Expansion To try to answer some of these questions, we run a query expansion experiment using the Gene Ontology (GO) as domain knowledge. ...
In most of the cases, those mechanisms are based on keyword matching, and thus are excessively dependant on the query and document terms. ...
doi:10.1038/npre.2009.3550.1
fatcat:5mb3d7mnvfc67mu3c64uotceba
Applying Biomedical Ontologies on Semantic Query Expansion
2009
Nature Precedings
This poster presents an ongoing work on using biomedical ontologies to improve efficiency on information retrieval. ...
Semantic Query Expansion To try to answer some of these questions, we run a query expansion experiment using the Gene Ontology (GO) as domain knowledge. ...
In most of the cases, those mechanisms are based on keyword matching, and thus are excessively dependant on the query and document terms. ...
doi:10.1038/npre.2009.3550
fatcat:klbn7krs5jfajef2vmevuw7byy
Exploring criteria for successful query expansion in the genomic domain
2008
Information retrieval (Boston)
In general, query expansion experiments exhibit mixed results. ...
Query Expansion is commonly used in Information Retrieval to overcome vocabulary mismatch issues, such as synonymy between the original query terms and a relevant document. ...
However, the experiments described in this paper are performed on a collection of domain specific documents and queries. ...
doi:10.1007/s10791-008-9073-9
fatcat:rpfredqpjzdulds7b7q5qrjuhq
Factors affecting the effectiveness of biomedical document indexing and retrieval based on terminologies
2013
Artificial Intelligence in Medicine
In addition, our experimental results show that document expansion using preferred terms in combination with query expansion using terms from top ranked expanded documents improve the biomedical IR effectiveness ...
Through this study, we presented many factors affecting the effectiveness of biomedical IR system including term weighting, query expansion, and document expansion models. ...
We would like to thank people at the IRIT laboratory who develop and maintain the OSIRIM platform, which is an infrastructure of several interconnected computers for undertaking experimental research in ...
doi:10.1016/j.artmed.2012.08.006
pmid:23092678
fatcat:2ss3cba3njfhzpk76rbd6isuga
A supervised term ranking model for diversity enhanced biomedical information retrieval
2019
BMC Bioinformatics
We address the diversity-oriented biomedical retrieval task using a supervised term ranking model. The model is learned through a supervised query expansion process for term refinement. ...
The number of biomedical research articles have increased exponentially with the advancement of biomedicine in recent years. ...
[25] matched concept pairs between queries and documents using a semantic query expansion method. These studies motivate us to optimize query expansion in consideration of domain knowledge. ...
doi:10.1186/s12859-019-3080-2
pmid:31787087
pmcid:PMC6886246
fatcat:ikcldl4fjbg5bkqatdqcyvhegy
A2A: a platform for research in biomedical literature search
2020
BMC Bioinformatics
However, they are limited in how users can control the processing of queries and articles—or as we call them documents—by the search engine. ...
Our experiments report well-known information retrieval metrics such as precision at a cutoff of ranked documents. ...
Acknowledgements We acknowledge the contributions of our colleagues in the previous versions of the A2A system: Falk Scholer (RMIT University), Sara Falamaki (ex-CSIRO), and Brian Jin (CSIRO). ...
doi:10.1186/s12859-020-03894-8
pmid:33349237
fatcat:dy45nsg2mvf3nlwrxf4s5wpe3a
Probabilistic and machine learning-based retrieval approaches for biomedical dataset retrieval
2018
Database: The Journal of Biological Databases and Curation
Our experiments with probabilistic information retrieval methods, such as query term weight optimization, automatic query expansion and simulated user relevance feedback, demonstrate that automatically ...
We describe experiments in applying a data-driven, machine learningbased approach to biomedical dataset retrieval as part of this challenge. ...
Query and document mismatch: The key terms in the query often do not appear in the relevant dataset descriptions, suggesting the necessity for query reformulation and expansion. ...
doi:10.1093/database/bax104
pmid:29688379
pmcid:PMC5887275
fatcat:6bwnrhh4u5g6jefw5xzg2ewdru
An empirical study of gene synonym query expansion in biomedical information retrieval
2008
Information retrieval (Boston)
Due to the heavy use of gene synonyms in biomedical text, people have tried many query expansion techniques using synonyms in order to improve performance in biomedical information retrieval. ...
TREC biomedical text collections for ad hoc document retrieval. ...
Acknowledgments This material is based in part upon work supported by the National Science Foundation under award number 0425852 and work supported by NIH/NLM grant 1 R01 LM009153-01. ...
doi:10.1007/s10791-008-9075-7
fatcat:luqi4sdwenepzlfkt4rxf65f7y
Improving biomedical information retrieval by linear combinations of different query expansion techniques
2016
BMC Bioinformatics
In IR one of the main problems is to determine which documents are relevant and which are not to the user's needs. ...
Query expansions expand the search query, for example, by finding synonyms and reweighting original terms. ...
Rivas et al. in [4] have developed pre-processing techniques of query expansion for retrieving documents in several fields of biomedical articles belonging to the corpus Cystic Fibrosis, a corpus of ...
doi:10.1186/s12859-016-1092-8
pmid:27455377
pmcid:PMC4965722
fatcat:ab3x524lezdovl7e5fnoadwnvy
G-Bean: an ontology-graph based web tool for biomedical literature retrieval
[article]
2015
arXiv
pre-print
with three innovations: parallel document index creation,ontology-graph based query expansion, and retrieval and re-ranking of documents based on user's search intention.Performance evaluation with 106 ...
G-Bean is available at http://bioinformatics.clemson.edu/G-Bean/index.php.G-Bean addresses PubMed's limitations with ontology-graph based query expansion, automatic document indexing, and user search intention ...
Ontology-graph based query expansion scheme Query expansion is widely used to reconstruct a seed query by adding extra related words to the input query with the purpose of matching additional related documents ...
arXiv:1401.1766v5
fatcat:qwpwxvkidfapvpzh76a3pept4u
A system for finding biological entities that satisfy certain conditions from texts
2008
Proceeding of the 17th ACM conference on Information and knowledge mining - CIKM '08
This paper presents an effective IR system for this task, in which 1) domain knowledge is incorporated to improve retrieval effectiveness; 2) query expansion with related concepts on multiple semantic ...
It is essential for many biomedical applications, such as drug discovery which normally requires collecting existing scientific facts from documents. ...
In comparison, we study more levels of related terms in the biomedical domain for query expansion. ...
doi:10.1145/1458082.1458251
dblp:conf/cikm/ZhouYM08
fatcat:i7iavpmljngs3fgkli42bqtzq4
Cluster-based query expansion using external collections in medical information retrieval
2015
Journal of Biomedical Informatics
Extensive experiments on three medical collections (TREC CDS, CLEF eHealth, and OHSUMED) were performed, and the results were compared with a representative expansion approach utilizing the external collections ...
Improving medical information retrieval has also gained much attention as various types of medical documents have become available to researchers ever since they started storing them in machine processable ...
Query expansion aims at dealing with the vocabulary mismatch problem between a query Q and a document D [7] . ...
doi:10.1016/j.jbi.2015.09.017
pmid:26429592
fatcat:jr62ceqpujfdbblct55mau3nr4
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