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BioEve Search: A Novel Framework to Facilitate Interactive Literature Search.

Ahmed ST, Davulcu H, Tikves S, Nair R, Zhao Z - Adv Bioinformatics (2012)

Bottom Line: It enables guided step-by-step search query refinement, by suggesting concepts and entities (like genes, drugs, and diseases) to quickly filter and modify search direction, and thereby facilitating an enriched paradigm where user can discover related concepts and keywords to search while information seeking.Conclusions.The BioEve Search framework makes it easier to enable scalable interactive search over large collection of textual articles and to discover knowledge hidden in thousands of biomedical literature articles with ease.

View Article: PubMed Central - PubMed

Affiliation: Department of Biomedical Informatics, Vanderbilt University, Nashville, TN 37232, USA.

ABSTRACT
Background. Recent advances in computational and biological methods in last two decades have remarkably changed the scale of biomedical research and with it began the unprecedented growth in both the production of biomedical data and amount of published literature discussing it. An automated extraction system coupled with a cognitive search and navigation service over these document collections would not only save time and effort, but also pave the way to discover hitherto unknown information implicitly conveyed in the texts. Results. We developed a novel framework (named "BioEve") that seamlessly integrates Faceted Search (Information Retrieval) with Information Extraction module to provide an interactive search experience for the researchers in life sciences. It enables guided step-by-step search query refinement, by suggesting concepts and entities (like genes, drugs, and diseases) to quickly filter and modify search direction, and thereby facilitating an enriched paradigm where user can discover related concepts and keywords to search while information seeking. Conclusions. The BioEve Search framework makes it easier to enable scalable interactive search over large collection of textual articles and to discover knowledge hidden in thousands of biomedical literature articles with ease.

No MeSH data available.


A sample screen shot of the main search screen. Left panel shows clickable top relevant entities, which if selected refines the query and results dynamically. User can deselect any of the previously selected entities to refine query more, and the results are updated dynamically to reflect the current selected list of entities.
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fig2: A sample screen shot of the main search screen. Left panel shows clickable top relevant entities, which if selected refines the query and results dynamically. User can deselect any of the previously selected entities to refine query more, and the results are updated dynamically to reflect the current selected list of entities.

Mentions: Search interface is divided into left and right panels, see Figure 2, basically displaying enriched keywords and results, respectively.


BioEve Search: A Novel Framework to Facilitate Interactive Literature Search.

Ahmed ST, Davulcu H, Tikves S, Nair R, Zhao Z - Adv Bioinformatics (2012)

A sample screen shot of the main search screen. Left panel shows clickable top relevant entities, which if selected refines the query and results dynamically. User can deselect any of the previously selected entities to refine query more, and the results are updated dynamically to reflect the current selected list of entities.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3368157&req=5

fig2: A sample screen shot of the main search screen. Left panel shows clickable top relevant entities, which if selected refines the query and results dynamically. User can deselect any of the previously selected entities to refine query more, and the results are updated dynamically to reflect the current selected list of entities.
Mentions: Search interface is divided into left and right panels, see Figure 2, basically displaying enriched keywords and results, respectively.

Bottom Line: It enables guided step-by-step search query refinement, by suggesting concepts and entities (like genes, drugs, and diseases) to quickly filter and modify search direction, and thereby facilitating an enriched paradigm where user can discover related concepts and keywords to search while information seeking.Conclusions.The BioEve Search framework makes it easier to enable scalable interactive search over large collection of textual articles and to discover knowledge hidden in thousands of biomedical literature articles with ease.

View Article: PubMed Central - PubMed

Affiliation: Department of Biomedical Informatics, Vanderbilt University, Nashville, TN 37232, USA.

ABSTRACT
Background. Recent advances in computational and biological methods in last two decades have remarkably changed the scale of biomedical research and with it began the unprecedented growth in both the production of biomedical data and amount of published literature discussing it. An automated extraction system coupled with a cognitive search and navigation service over these document collections would not only save time and effort, but also pave the way to discover hitherto unknown information implicitly conveyed in the texts. Results. We developed a novel framework (named "BioEve") that seamlessly integrates Faceted Search (Information Retrieval) with Information Extraction module to provide an interactive search experience for the researchers in life sciences. It enables guided step-by-step search query refinement, by suggesting concepts and entities (like genes, drugs, and diseases) to quickly filter and modify search direction, and thereby facilitating an enriched paradigm where user can discover related concepts and keywords to search while information seeking. Conclusions. The BioEve Search framework makes it easier to enable scalable interactive search over large collection of textual articles and to discover knowledge hidden in thousands of biomedical literature articles with ease.

No MeSH data available.