Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Finding highly relevant articles from biomedical databases is challenging because it is often very difficult to accurately express a user's underlying intention through keywords, and a keyword-based query normally returns a long list of hits.  proposes a novel biomedical literature search system, called BiomedSearch, which supports complex queries and relevance feedback. In this system,  developed a ighted interest measure and an association mining algorithm to find the strength of association beten the query and each concept in the article(s) selected by the user as feedback. The top ?? concepts re utilized to form a k-profile used for the next-round search. BiomedSearch relies on Unified Medical Language System (UMLS) knowledge sources to map text files to standard biomedical concepts. It was designed to support queries with any levels of complexity. The prototype system was preliminarily evaluated using three topics and related Genomics data from TREC (Text Retrieval Conference) 2006 Genomics Track. Initial results indicated that BiomedSearch could effectively utilize users' relevance feedback to improve search performance.
['Yanqing Ji', 'Hao Ying', 'John C. Tran', 'Peter Dews', 'R. Michael Massanari']
I am writing a research paper on a idea Integrating association mining into relevance feedback for biomedical literature search
[{"from": "human", "value": "I am writing a research paper on a idea Integrating association mining into relevance feedback for biomedical literature search"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Finding highly relevant articles from biomedical databases is challenging because it is often very difficult to accurately express a user's underlying intention through keywords, and a keyword-based query normally returns a long list of hits.  proposes a novel biomedical literature search system, called BiomedSearch, which supports complex queries and relevance feedback. In this system,  developed a ighted interest measure and an association mining algorithm to find the strength of association beten the query and each concept in the article(s) selected by the user as feedback. The top ?? concepts re utilized to form a k-profile used for the next-round search. BiomedSearch relies on Unified Medical Language System (UMLS) knowledge sources to map text files to standard biomedical concepts. It was designed to support queries with any levels of complexity. The prototype system was preliminarily evaluated using three topics and related Genomics data from TREC (Text Retrieval Conference) 2006 Genomics Track. Initial results indicated that BiomedSearch could effectively utilize users' relevance feedback to improve search performance."}]