Multi-Perspective Semantic Information Retrieval in the Biomedical Domain
Table A.18: BioASQ 7B Phase A Batch 3 Snippet Ranking results.
['System', 'MPrec Docs', 'MRec Docs', 'F-Measure Docs', 'MAP Docs', 'GMAP Docs']
\degreeName Master of Science \paperTypeThesis \degreeNameMaster of Science \defensemonthApril \gradmonthMay \gradyear2020 \chairChitta Baral \memberOneMurthy Devarakonda \memberTwoSaadat Anwar \doublespace \dedicationpage I would like to dedicate this work to my family, friends, and mentors who have always supported me. {acknowledgements} I would like to thank Dr. Chitta Baral for his support and guidance over the past six years, both as a research advisor and mentor. His steady encouragement has been invaluable in enabling me to pursue research and participate in projects related to my interest in clinical Natural Language Processing. Next, I would like to thank Dr. Saadat Anwar for his mentorship and advice over the past several years. From my early years as an undergraduate student up until now, he has offered valuable feedback and guidance that has helped me grow. I would also like to thank Dr. Murthy Devarakonda for serving as a mentor to me and introducing me to many ways computer science can have clinical applications. Finally, I would like to thank my family and friends, including my parents and brother, as well as my colleagues at Arizona State University. Specifically, I would like to thank Arpit Sharma, who was one of my earliest student mentors and taught me much of what I know today about conducting research. I would also like to thank my friends Ishan Shrivastava, Aurgho Bhattacharjee, Arindam Mitra, Sanjay Narayana, Swaroop Mishra, Pratyay Banerjee, Kuntal Pal, Shailaja Sampat, and many others for their help and encouragement throughout my time at the lab. \doublespace Perhaps most widely utilized in the form of search engines, the ability to take a query and use it to find relevant information from a repository of knowledge is essential to effectively making use of large amounts of data. The field of study that deals with finding and ranking relevant information based on certain criteria is Information Retrieval (IR), which utilizes many components from the field of Natural Language Processing (NLP), particularly when dealing with textual data such as webpages or research papers. NLP can be considered to be a subfield of Artificial Intelligence (AI) that deals with the semantic interpretation of natural language by machines. Over the decades, several NLP statistical metric- and machine learning-based techniques, such as term frequency–inverse document frequency, bag-of-words, and deep neural networks, have been applied to IR systems with varying degrees of success.