Information Need Question Understanding Selecting Sources Information Retrieval and Extraction Answer Determina tion Answer Presentation This work is supported.

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Information Need Question Understanding Selecting Sources Information Retrieval and Extraction Answer Determina tion Answer Presentation This work is supported by the NSF Division of Undergraduate Education Award number and the IDeA Networks of Biomedical Research Excellence (INBRE) Program of the National Center for Research Resources. INTRODUCTION HyperGlossary INTEGRATIONEXAMPLE CASE CONCLUSIONS AND IMPLICATIONS An example interaction with the system: 1.The user asks the system a question that is sent to each of the agents to process in its own way. 2.In this case more information was needed to reduce the number of possible answers so the system asked if the user could provide any additional terms. 3.The additional information allows the system to find an answer that is processed by the HyperGlossary. 4. The term ‘acetone’ was matched in the chosen glossary. 5.A definition of acetone is presented with a Spanish translation and the 3D structure of the molecule. The HyperGlossary (HG), located at a tool that we developed to automate the insertion of hyperlinks into a digital text document or Web page which can connect words or phrases to relevant textual material such as definitions of words, multimedia content, or multidimensional structures for molecules. When a user reads a word or phrase in a document that is connected to a glossary term, the information associated with the term can be viewed without leaving the original document. Information Accessibility - The QA system is designed to be a tool used by biomedical domain experts and also be useful and informative to students. Biological Data Mashup - The integration of the HyperGlossary will allow the answer to not only be linked back to the original document, but also keywords and phrases found in a chosen glossary will be linked to additional sources of information. The system brings together traditional textual information and dedicated biological databases to present a concise answer to the user. Balloon Smile -> mol2 Balloon Smile -> mol2 Open Babel InChI -> Smile Open Babel InChI -> Smile Display Select Term Query by InChI JMOL Returned JMOL Returned Mol2 file Available on Local Server Mol2 file Available on Local Server ChemEd DL Save mol2 file Display JMOL WHG Word Management Features Chemical Identifier Field Question Answering System Score and Rank Document Management HyperGlossary External Sources Answers Document Representations Document Representations Parse and Identify Glossary Terms Client Browser Search Agents Glossaries Results Marked-Up Answers Question ChemEd DL PubChem NCBI Knowledge Base SYSTEM DIAGRAM In clinical and biomedical settings researchers use specialized search engines to acquire answers to technical questions or to quickly get verification of experimental results. The outcome of such queries result in the reading and scanning of multiple Web pages and documents. Question answering (QA) is a specialized type of information retrieval with the aim of returning precise short answers to queries posed as natural language questions Display Relevant Information Select Term Term Type Sources Chemical (InChI) Chemical (InChI) Protein (GI Number) Protein (GI Number) Gene (Gene ID) Gene (Gene ID) Structures Sequences Definitions Query by ID ChemEd DL PubChem NCBI Protein NCBI Gene ChemSpider Jmol allows you to interact with molecules in multiple ways beyond simple measurements, like connecting vibrations to IR Spectra and visualizing symmetry operations The HG does not just insert link but is also a Glossary Generating Program which can be used to develop glossaries for any field at any competency level. Terms in a glossary can be given a type, such as protein, gene, or chemical, and be used to access the appropriate supplemental data sources. Answers will be automatically marked up and linked to semantically relevant content in other databases using the HyperGlossary. Terms that are designated as a particular type will have a common ID for the type and be used to access additional resources. Highlighted in yellow are the ID and sources currently implemented in the HG. In the event that a resource does not have the information requested for a chemical term, the HG has the ability to generate its own structure file from the ID. Open Babel and Balloon, two open source chemistry resources, are used to create a JMOL file on the fly. Basic Elements of a QA System Potential answers chosen by the QA system will be piped through the HyperGlossary before being returned to the user. HyperGlossary Core Information Need Textual Information Relevant Information Similarity Measure ? Query Formation Create Intermediate Form Basic Information Retrieval System