{"id":14052,"date":"2023-10-06T14:41:56","date_gmt":"2023-10-06T12:41:56","guid":{"rendered":"https:\/\/sano.science\/?post_type=seminars&#038;p=14052"},"modified":"2023-10-09T21:13:07","modified_gmt":"2023-10-09T19:13:07","slug":"107-exploring-information-retrieval-from-sparse-to-dense-vector-representations","status":"publish","type":"seminars","link":"https:\/\/sano.science\/seminars\/107-exploring-information-retrieval-from-sparse-to-dense-vector-representations\/","title":{"rendered":"107. Exploring Information Retrieval: From Sparse to Dense Vector Representations"},"content":{"rendered":"\n<h2 class=\"wp-block-heading eplus-wrapper\">Abstract<\/h2>\n\n\n\n<p class=\" eplus-wrapper\">This presentation delves into the diverse approaches to information retrieval, comparing classical sparse text representations with cutting-edge dense text representations.<\/p>\n\n\n\n<p class=\" eplus-wrapper\">In the initial segment, we embark on a journey into classical information retrieval methods, employing powerful software tools like ElasticSearch and SOLR. We delve into the intricacies of the BM25 model, shedding light on challenges pertaining to inflectional languages.<\/p>\n\n\n\n<p class=\" eplus-wrapper\">The second part of this presentation delves into contemporary advancements in information retrieval. We explore text representations grounded in the transformative architecture, navigating through a comprehensive search pipeline that encompasses a dense retriever, re-ranker, and a question-answering reader. Additionally, we showcase models proficient in generating dense representations, such as DPR and E5.<\/p>\n\n\n\n<p class=\" eplus-wrapper\">In closing, we weigh the performance of both sparse and dense retrievers, offering insightful considerations to conclude our exploration of these information retrieval methodologies.<\/p>\n\n\n\n<div style=\"height:50px\" aria-hidden=\"true\" class=\"wp-block-spacer eplus-wrapper\"><\/div>\n\n\n\n<h2 class=\"wp-block-heading eplus-wrapper\">About the author<\/h2>\n\n\n\n<p class=\" eplus-wrapper\">Dr. Aleksander Smywi\u0144ski-Pohl is a researcher in natural language processing. He received his Ph.D. in 2015 from AGH University of Science and Technology in Krakow for the work entitled: Automatic extraction of semantic relations from Polish texts. His primary research interests concentrate on the application of modern NLP techniques in a broad range of practical problems. In 2017, he started a research project funded by the Polish National Center for Research and Development (NCBR) devoted to the construction of an intelligent legal information system called 0\u201eLemkin\u201d. He also participated in other projects aimed at building the Polish language model for application in Automatic Speech Recognition, sentiment analysis of user-generated content, monitoring contents of the public media as well as cyberbullying and self-harm detection. Currently he works together with Tomer Libal in a grant sponsored by FNR and NCBR on automatic question answering for court cases.<\/p>\n\n\n\n<div style=\"height:50px\" aria-hidden=\"true\" class=\"wp-block-spacer eplus-wrapper\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"aligncenter size-large eplus-wrapper\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"536\" src=\"https:\/\/sano.science\/wp-content\/uploads\/2023\/10\/106_quantifying_microstructural_li_2-1024x536.jpg\" alt=\"\" class=\"wp-image-14060\" srcset=\"https:\/\/sano.science\/wp-content\/uploads\/2023\/10\/106_quantifying_microstructural_li_2-1024x536.jpg 1024w, https:\/\/sano.science\/wp-content\/uploads\/2023\/10\/106_quantifying_microstructural_li_2-300x157.jpg 300w, https:\/\/sano.science\/wp-content\/uploads\/2023\/10\/106_quantifying_microstructural_li_2-768x402.jpg 768w, https:\/\/sano.science\/wp-content\/uploads\/2023\/10\/106_quantifying_microstructural_li_2.jpg 1200w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><\/figure>\n<\/div>","protected":false},"excerpt":{"rendered":"<p>Aleksander Smywi\u0144ski-Pohl, PhD \u2013 Computer Science Institute, AGH University of Krakow, Poland<\/p>\n","protected":false},"featured_media":0,"template":"","class_list":["post-14052","seminars","type-seminars","status-publish","hentry"],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v27.5 (Yoast SEO v27.5) - https:\/\/yoast.com\/product\/yoast-seo-premium-wordpress\/ -->\n<title>107. 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Exploring Information Retrieval: From Sparse to Dense Vector Representations\" \/>\n<meta property=\"og:description\" content=\"Aleksander Smywi\u0144ski-Pohl, PhD \u2013 Computer Science Institute, AGH University of Krakow, Poland\" \/>\n<meta property=\"og:url\" content=\"https:\/\/sano.science\/seminars\/107-exploring-information-retrieval-from-sparse-to-dense-vector-representations\/\" \/>\n<meta property=\"og:site_name\" content=\"Centre for Computational Personalized Medicine\" \/>\n<meta property=\"article:publisher\" content=\"https:\/\/www.facebook.com\/sano.science\/\" \/>\n<meta property=\"article:modified_time\" content=\"2023-10-09T19:13:07+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/sano.science\/wp-content\/uploads\/2023\/10\/106_quantifying_microstructural_li_2-1024x536.jpg\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:site\" content=\"@sanoscience\" \/>\n<meta name=\"twitter:label1\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data1\" content=\"2 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\\\/\\\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\\\/\\\/sano.science\\\/seminars\\\/107-exploring-information-retrieval-from-sparse-to-dense-vector-representations\\\/\",\"url\":\"https:\\\/\\\/sano.science\\\/seminars\\\/107-exploring-information-retrieval-from-sparse-to-dense-vector-representations\\\/\",\"name\":\"107. 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We delve into the intricacies of the BM25 model, shedding light on challenges pertaining to inflectional languages.<\/p>\n","innerContent":["\n<p class=\" eplus-wrapper\">In the initial segment, we embark on a journey into classical information retrieval methods, employing powerful software tools like ElasticSearch and SOLR. We delve into the intricacies of the BM25 model, shedding light on challenges pertaining to inflectional languages.<\/p>\n"]},{"blockName":"core\/paragraph","attrs":{"epAnimationGeneratedClass":"edplus_anim-QVF8ta","epGeneratedClass":"eplus-wrapper"},"innerBlocks":[],"innerHTML":"\n<p class=\" eplus-wrapper\">The second part of this presentation delves into contemporary advancements in information retrieval. We explore text representations grounded in the transformative architecture, navigating through a comprehensive search pipeline that encompasses a dense retriever, re-ranker, and a question-answering reader. Additionally, we showcase models proficient in generating dense representations, such as DPR and E5.<\/p>\n","innerContent":["\n<p class=\" eplus-wrapper\">The second part of this presentation delves into contemporary advancements in information retrieval. We explore text representations grounded in the transformative architecture, navigating through a comprehensive search pipeline that encompasses a dense retriever, re-ranker, and a question-answering reader. Additionally, we showcase models proficient in generating dense representations, such as DPR and E5.<\/p>\n"]},{"blockName":"core\/paragraph","attrs":{"epAnimationGeneratedClass":"edplus_anim-J7Ec9h","epGeneratedClass":"eplus-wrapper"},"innerBlocks":[],"innerHTML":"\n<p class=\" eplus-wrapper\">In closing, we weigh the performance of both sparse and dense retrievers, offering insightful considerations to conclude our exploration of these information retrieval methodologies.<\/p>\n","innerContent":["\n<p class=\" eplus-wrapper\">In closing, we weigh the performance of both sparse and dense retrievers, offering insightful considerations to conclude our exploration of these information retrieval methodologies.<\/p>\n"]},{"blockName":"core\/spacer","attrs":{"height":"50px","epAnimationGeneratedClass":"edplus_anim-qyYNrE","epGeneratedClass":"eplus-wrapper"},"innerBlocks":[],"innerHTML":"\n<div style=\"height:50px\" aria-hidden=\"true\" class=\"wp-block-spacer eplus-wrapper\"><\/div>\n","innerContent":["\n<div style=\"height:50px\" aria-hidden=\"true\" class=\"wp-block-spacer eplus-wrapper\"><\/div>\n"]},{"blockName":"core\/heading","attrs":{"epAnimationGeneratedClass":"edplus_anim-pM9Spo","epGeneratedClass":"eplus-wrapper"},"innerBlocks":[],"innerHTML":"\n<h2 class=\"wp-block-heading eplus-wrapper\">About the author<\/h2>\n","innerContent":["\n<h2 class=\"wp-block-heading eplus-wrapper\">About the author<\/h2>\n"]},{"blockName":"core\/paragraph","attrs":{"epAnimationGeneratedClass":"edplus_anim-fYpuxT","epGeneratedClass":"eplus-wrapper"},"innerBlocks":[],"innerHTML":"\n<p class=\" eplus-wrapper\">Dr. Aleksander Smywi\u0144ski-Pohl is a researcher in natural language processing. He received his Ph.D. in 2015 from AGH University of Science and Technology in Krakow for the work entitled: Automatic extraction of semantic relations from Polish texts. His primary research interests concentrate on the application of modern NLP techniques in a broad range of practical problems. In 2017, he started a research project funded by the Polish National Center for Research and Development (NCBR) devoted to the construction of an intelligent legal information system called 0\u201eLemkin\u201d. He also participated in other projects aimed at building the Polish language model for application in Automatic Speech Recognition, sentiment analysis of user-generated content, monitoring contents of the public media as well as cyberbullying and self-harm detection. Currently he works together with Tomer Libal in a grant sponsored by FNR and NCBR on automatic question answering for court cases.<\/p>\n","innerContent":["\n<p class=\" eplus-wrapper\">Dr. Aleksander Smywi\u0144ski-Pohl is a researcher in natural language processing. He received his Ph.D. in 2015 from AGH University of Science and Technology in Krakow for the work entitled: Automatic extraction of semantic relations from Polish texts. His primary research interests concentrate on the application of modern NLP techniques in a broad range of practical problems. In 2017, he started a research project funded by the Polish National Center for Research and Development (NCBR) devoted to the construction of an intelligent legal information system called 0\u201eLemkin\u201d. He also participated in other projects aimed at building the Polish language model for application in Automatic Speech Recognition, sentiment analysis of user-generated content, monitoring contents of the public media as well as cyberbullying and self-harm detection. Currently he works together with Tomer Libal in a grant sponsored by FNR and NCBR on automatic question answering for court cases.<\/p>\n"]},{"blockName":"core\/spacer","attrs":{"height":"50px","epAnimationGeneratedClass":"edplus_anim-iyq7Gn","epGeneratedClass":"eplus-wrapper"},"innerBlocks":[],"innerHTML":"\n<div style=\"height:50px\" aria-hidden=\"true\" class=\"wp-block-spacer eplus-wrapper\"><\/div>\n","innerContent":["\n<div style=\"height:50px\" aria-hidden=\"true\" class=\"wp-block-spacer eplus-wrapper\"><\/div>\n"]},{"blockName":"core\/image","attrs":{"align":"center","id":14060,"sizeSlug":"large","linkDestination":"none","epAnimationGeneratedClass":"edplus_anim-jZcZEH","epGeneratedClass":"eplus-wrapper"},"innerBlocks":[],"innerHTML":"\n<figure class=\"wp-block-image aligncenter size-large eplus-wrapper\"><img src=\"https:\/\/sano.science\/wp-content\/uploads\/2023\/10\/106_quantifying_microstructural_li_2-1024x536.jpg\" alt=\"\" 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