A vector space model for automatic indexing
Communications of the ACM
On the design of a learning crawler for topical resource discovery
ACM Transactions on Information Systems (TOIS)
CMedPort: an integrated approach to facilitating Chinese medical information seeking
Decision Support Systems
Meeting medical terminology needs-the ontology-enhanced Medical Concept Mapper
IEEE Transactions on Information Technology in Biomedicine
A collaborative medical case authoring environment based on the UMLS
Journal of Biomedical Informatics
An ontology-based approach to learnable focused crawling
Information Sciences: an International Journal
State of the Art in Semantic Focused Crawlers
ICCSA '09 Proceedings of the International Conference on Computational Science and Its Applications: Part II
Learnable focused crawling based on ontology
AIRS'08 Proceedings of the 4th Asia information retrieval conference on Information retrieval technology
ROLEX-SP: Rules of lexical syntactic patterns for free text categorization
Knowledge-Based Systems
Knowledge retrieval in the anatomical domain
Proceedings of the 1st ACM International Health Informatics Symposium
Semantic service matchmaking for Digital Health Ecosystems
Knowledge-Based Systems
NCBO Resource Index: Ontology-based search and mining of biomedical resources
Web Semantics: Science, Services and Agents on the World Wide Web
Investigating interactive search behaviour of medical students: an exploratory survey
Proceedings of the 23rd Australian Computer-Human Interaction Conference
Collaboration-based medical knowledge recommendation
Artificial Intelligence in Medicine
AIRS'11 Proceedings of the 7th Asia conference on Information Retrieval Technology
Analysis of query entries of a job search engine
DUXU'13 Proceedings of the Second international conference on Design, User Experience, and Usability: web, mobile, and product design - Volume Part IV
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We present a new next generation domain search engine called MedicoPort. MedicoPort is a medical search engine designed for the users with no medical expertise. It is enhanced with the domain knowledge obtained from Unified Medical Language System (UMLS) to increase the effectiveness of the searches. The power of the system is based on the ability to understand the semantics of web pages and the user queries. MedicoPort transforms a keyword search into a conceptual search. Through our system we present a topical web crawling technique and indexing techniques empowered by the semantics information. MedicoPort aims to generate maximum output with semantic value using minimum input from the user. Since MedicoPort is designed to help people seeking information about health on the web, our target users are not medical specialists who can effectively use the special jargon of medicine and access medical databases. Medical experts have the advantage of shrinking the answer set by expressing several terms using medical terminology. MedicoPort provides the same advantage to its users through the automated use of the medical domain knowledge in the background. The results of our experiments indicate that, expanding the queries with domain knowledge, such as using the synonyms and partially or contextually relevant terms from UMLS, increase dramatically the relevance of an answer set produced by MedicoPort and the number of retrieved web pages that are relevant to the user request.