Background: There exist many academic search solutions and most of them can be put on either ends of spectrum: general-purpose search and domain-specific "deep" search systems. The general-purpose search systems, such as PubMed, offer flexible query interface, but churn out a list of matching documents that users have to go through the results in order to find the answers to their queries. On the other hand, the "deep" search systems, such as PPI Finder and iHOP, return the precompiled results in a structured way. Their results, however, are often found only within some predefined contexts. In order to alleviate these problems, we introduce a new search engine, BOSS, Biomedical Object Search System. Methods. Unlike the conventional search systems, BOSS indexes segments, rather than documents. A segment refers to a Maximal Coherent Semantic Unit (MCSU) such as phrase, clause or sentence that is semantically coherent in the given context (e.g., biomedical objects or their relations). For a user query, BOSS finds all matching segments, identifies the objects appearing in those segments, and aggregates the segments for each object. Finally, it returns the ranked list of the objects along with their matching segments. Results: The working prototype of BOSS is available at http://boss.korea.ac.kr. The current version of BOSS has indexed abstracts of more than 20 million articles published during last 16 years from 1996 to 2011 across all science disciplines. Conclusion: BOSS fills the gap between either ends of the spectrum by allowing users to pose context-free queries and by returning a structured set of results. Furthermore, BOSS exhibits the characteristic of good scalability, just as with conventional document search engines, because it is designed to use a standard document-indexing model with minimal modifications. Considering the features, BOSS notches up the technological level of traditional solutions for search on biomedical information.
Bibliographical noteFunding Information:
This project was supported by the Second Brain Korea 21 Project Grant, the National Research Foundation of Korea (NRF) grant funded by the Korean government (MEST) (2009-0077688, 2009-0086140), National IT Industry Promotion Agency (NIPA) grant funded by the Ministry of Knowledge Economy (MKE) (C1810-1002-0027) and the Small & Medium Business Administration (SMBA) grant funded by the Ministry of Knowledge Economy (MKE) (00047622). This work was a result of a collaborative effort with KISTI. We especially thank Woondong Yeo for his help on the initial setup for this research.
ASJC Scopus subject areas
- Health Policy
- Health Informatics