Limits...
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.


BioEve search framework architecture.
© Copyright Policy
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC3368157&req=5

fig1: BioEve search framework architecture.

Mentions: We developed BioEve Search (http://www.bioeve.org/) framework to provide fast and scalable search service, where users can quickly refine their queries and drill down to the articles they are looking for in a matter of seconds, corresponding to a few number of clicks. The system helps identify hidden relationships between entities (like drugs, diseases, and genes), by highlighting them using a tag cloud to give a quick visualization for efficient navigation. In order to have sufficient abstraction between various modules (and technologies used) in this system, we have divided this framework into four different layers (refer to Figure 1) and they are (a) Data Store layer, (b) Information Extraction layer, (c) Faceting layer, and (d) Web Interface layer. Next sections explain each layer of this framework in more details.


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

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

BioEve search framework architecture.
© Copyright Policy
Related In: Results  -  Collection

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

fig1: BioEve search framework architecture.
Mentions: We developed BioEve Search (http://www.bioeve.org/) framework to provide fast and scalable search service, where users can quickly refine their queries and drill down to the articles they are looking for in a matter of seconds, corresponding to a few number of clicks. The system helps identify hidden relationships between entities (like drugs, diseases, and genes), by highlighting them using a tag cloud to give a quick visualization for efficient navigation. In order to have sufficient abstraction between various modules (and technologies used) in this system, we have divided this framework into four different layers (refer to Figure 1) and they are (a) Data Store layer, (b) Information Extraction layer, (c) Faceting layer, and (d) Web Interface layer. Next sections explain each layer of this framework in more details.

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.