MiSTeRy Visualizer Farhan Jamal Khan [firstname.lastname@example.org] Mine Search Transform (MiSTeRy) Visualizer Ishan Patel [email@example.com] System Design Mine Search Semantic types Concepts related_to Is_a relations relations associated_with relations Concept 1 Concept 2 Query UMLS Semantic UMLS Concept 3 Entrez EUtilities Term 1 Network Metathesaurus Term 2 Results / Articles Set Results / Articles Set Term 3 Meta Map Concept 4 Semantic Techniques Term 4 Concept 1 Score [Semantic Type] Concept 2 Score [Semantic Type] Concept 3 Score [Semantic Type] PubMed Concept N Score [Semantic Type] Java Mine Search Transform Visualize Vaadin Transform Visualize Text Mining Database Searching Ranking Presentation MeSH Concepts Relevance Result 1 Result 2 Concept 1 Score Result 3 Title Concept 2 Publi ca Sema tion Info Concept 3 ntic Conc Type epts Result 4 Concept 4 Result 1 Result 2 List List Result 3 Clinical Text Query Query + Domain Domain Semantic Types/ PubMed Database Relevance Relevance Relevance Result 4 Sorting/ Concepts/ Graph Meta Map Scores MedLine Index Categorization Interactive Scoring Semantic MeSH Mine, Search, Transform (MiSTery) Visualizer Type Concepts Ranked Results Ranked Results Ranked Results Ranked Results Ranked Results Ranked Results Application Design MiSTeRy Visualizer Abstract: Search Results Page Graphical Representation Classical Keyword-based search has a number of limitations. These limitations include missing semantic information for terms, single-document retrieval, and lack of contextual ranking. Current research in tackling these constraints deals with concept-based information retrieval User Query Search and search. Mine, Search, Transform (MiSTeRy) Visualizer is a concept-based search application tion ssocia which utilizes the state-of-the-art research for incorporating semantic techniques in the Article Name Refine Results hasA domain of retrieving evidence-based literature from PubMed. The articles in PubMed are Score Authors, Publication Details Semantic Types Semantic Type, Concepts Type 1 indexed with MeSH (Medical Subject Headings) concepts. The Medical Subject Headings Type 2 Type 3 Semantic Type2 (MeSH®) thesaurus is a controlled vocabulary produced by the U.S. National Library of Medicine Article Name (NLM) and used for indexing, cataloging, and searching for biomedical and health-related Score Authors, Publication Details Semantic Concepts  Semantic Type3 Semantic Type, Concepts Concept 1  information and documents. We have utilized the MeSH indexing of PubMed database to Sub Concept 1 Semantic Type1 improve the precision/recall ratio for the retrieved documents. The user of the system is a Sub Concept 2Ranked Articles Article Name Sub Concept 3  researcher who has a set of terms and is looking for the literature relevant to those terms. The Score Authors, Publication Details Concept 2 Concept 1 Semantic Type, Concepts query provided by the user is expanded using the NLMs MetaMap tool. MetaMap uses UMLS Ranking Criteria Query Relevance Metathesaurus and Semantic Network to employ knowledge-intensive approach for identifying Article Name Concept 1  nouns and corresponding scored concepts and semantic types from the provided text. The Score Domain Relevance Authors, Publication Details Query + Domain Relevance Semantic Type, Concepts Concept 1.1  retrieved concepts are used to perform a query on PubMed to retrieve a set of articles. These Authors Concept 1  Concept 1.2  articles are ranked based on the commulative MeSH concept scores (query relevance) as well as Author 1 Article Name Concept 1.1  on the basis of frequency of occurrence of a concept in retrieved set vs. the whole of PubMed Score Author 2 Authors, Publication Details Author 3 Semantic Type, Concepts Concept 1.2  (domain relevance). Moreover, the concepts and semantic types of the MeSH terms in the Country Concept 2  retrieved resultset are used to provide user with an option of refining (specializing/ Article Name Country 1 generalizing) the search and present a graphical summary of the results. Score Authors, Publication Details Country 2 Semantic Type, Concepts Country 3 Refine Concept 10  Keywords: Keyword-based search, Concept-based search, MeSH, semantic search.