G-Bean: an ontology-graph based web tool for biomedical literature retrieval
원문 초록
Currently, most people use PubMed to search the MEDLINE database, an important bibliographical information source for life science and biomedical information. However, PubMed has some drawbacks that make it difficult to find relevant publications pertaining to users' individual intentions, especially for non-expert users. To ameliorate the disadvantages of PubMed, we developed G-Bean, a graph based biomedical search engine, to search biomedical articles in MEDLINE database more efficiently.G-Bean addresses PubMed's limitations 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 OHSUMED benchmark queries shows that G-Bean returns more relevant results than PubMed does when using these queries to search the MEDLINE database. PubMed could not even return any search result for some OHSUMED queries because it failed to form the appropriate Boolean query statement automatically from the natural language query strings. 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 discovery. It shows significant advantages in finding relevant articles from the MEDLINE database to meet the information need of the user.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
RMIT-ADM+S at the SIGIR 2025 LiveRAG Challenge
SimpleDoc: Multi-Modal Document Understanding with Dual-Cue Page Retrieval and Iterative Refinement
Query-Focused Retrieval Heads Improve Long-Context Reasoning and Re-ranking
MCoT-RE: Multi-Faceted Chain-of-Thought and Re-Ranking for Training-Free Zero-Shot Composed Image Retrieval
SAMURAI: Shape-Aware Multimodal Retrieval for 3D Object Identification
CORONA: A Coarse-to-Fine Framework for Graph-based Recommendation with Large Language Models
토론
이 논문과 연결된 포럼 글이 아직 없습니다.