{"id":400433,"date":"2019-01-17T09:47:01","date_gmt":"2019-01-17T17:47:01","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/?post_type=msr-research-item&#038;p=400433"},"modified":"2019-01-17T09:47:01","modified_gmt":"2019-01-17T17:47:01","slug":"improving-search-engines-via-large-scale-physiological-sensing","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/improving-search-engines-via-large-scale-physiological-sensing\/","title":{"rendered":"Improving Search Engines via Large-Scale Physiological Sensing"},"content":{"rendered":"<p>Result ranking in commercial web search engines is based on a\u00a0wide array of signals, from keywords appearing on web pages to behavioral\u00a0(clickthrough) data aggregated across many users or from\u00a0the current user only. The recent emergence of wearable devices\u00a0has enabled the collection of physiological data such as heart rate,\u00a0skin temperature, and galvanic skin response at a population scale. These data are useful for many public health tasks, but they may\u00a0also provide novel clues about people\u2019s interests and intentions as\u00a0they engage in online activities. In this paper, we focus on heart\u00a0rate and show that there are strong relationships between heart\u00a0rate and various measures of user interest in a search result. We\u00a0integrate features of heart rate, including heart rate dynamics, as\u00a0additional attributes in a competitive machine-learned web search ranking algorithm. We show that we can obtain significant relevance\u00a0improvements from this physiological sensing that vary\u00a0depending on the search topic.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Result ranking in commercial web search engines is based on a\u00a0wide array of signals, from keywords appearing on web pages to behavioral\u00a0(clickthrough) data aggregated across many users or from\u00a0the current user only. The recent emergence of wearable devices\u00a0has enabled the collection of physiological data such as heart rate,\u00a0skin temperature, and galvanic skin response at a [&hellip;]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","msr-author-ordering":null,"msr_publishername":"ACM","msr_publisher_other":"","msr_booktitle":"","msr_chapter":"","msr_edition":"SIGIRfi17, August 7\u201311, 2017, Shinjuku, Tokyo, Japan","msr_editors":"","msr_how_published":"","msr_isbn":"978-1-4503-5022-8\/17\/08","msr_issue":"","msr_journal":"","msr_number":"","msr_organization":"","msr_pages_string":"","msr_page_range_start":"","msr_page_range_end":"","msr_series":"","msr_volume":"","msr_copyright":"","msr_conference_name":"SIGIRfi17, Shinjuku, Tokyo, 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