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To improve the safety, comfort, and convenience of residents\u2019 lives with minimal cost, daily activity recognition aims to know resident\u2019s daily activity in non\u2010invasive manner. The performance of daily activity recognition heavily depends on solving strategy of activity feature. However, the current common employed solving strategy based on statistical information of individual activity does not support well the activity recognition. To improve the common employed solving strategy, an activity feature solving strategy based on TF\u2010IDF is proposed in this paper. The proposed strategy exploits statistical information related to both individual activity and the whole of activities. Two distinct datasets have been commissioned, to mitigate against any possible effect of coupling between dataset and sensor configuration. Finally, a number of machine learning (ML) techniques and deep learning technique have been evaluated to assess their performance for residents activity recognition.<\/jats:p>","DOI":"10.1155\/2019\/5245373","type":"journal-article","created":{"date-parts":[[2019,3,24]],"date-time":"2019-03-24T23:31:13Z","timestamp":1553470273000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":31,"title":["Activity Feature Solving Based on TF\u2010IDF for Activity Recognition in Smart Homes"],"prefix":"10.1155","volume":"2019","author":[{"given":"Jinghuan","family":"Guo","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7999-8429","authenticated-orcid":false,"given":"Yong","family":"Mu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mudi","family":"Xiong","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6168-7385","authenticated-orcid":false,"given":"Yaqing","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4714-8251","authenticated-orcid":false,"given":"Jingxuan","family":"Gu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2019,3,24]]},"reference":[{"key":"e_1_2_10_1_2","doi-asserted-by":"publisher","DOI":"10.18356\/d5a97f23-en"},{"key":"e_1_2_10_2_2","first-page":"e13","article-title":"Aging populations: the health and quality of life of the elderly","volume":"162","author":"De Luca d\u2032Alessandro E.","year":"2011","journal-title":"La Clinica Terapeutica"},{"key":"e_1_2_10_3_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.cmpb.2008.02.001"},{"key":"e_1_2_10_4_2","doi-asserted-by":"publisher","DOI":"10.1145\/1273961.1273981"},{"key":"e_1_2_10_5_2","doi-asserted-by":"publisher","DOI":"10.1007\/s11042-015-3000-z"},{"key":"e_1_2_10_6_2","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2013.2280849"},{"key":"e_1_2_10_7_2","doi-asserted-by":"publisher","DOI":"10.1109\/MIS.2015.18"},{"key":"e_1_2_10_8_2","doi-asserted-by":"publisher","DOI":"10.1007\/s11390-011-9430-9"},{"key":"e_1_2_10_9_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2017.09.027"},{"key":"e_1_2_10_10_2","first-page":"1","article-title":"Using an improved SMOTE algorithm to deal imbalanced activity classes in smart homes","author":"Guo S. 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