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However, most of existing algorithms developed for this purpose take advantage of classical mechanisms, which may be long experimental, time-consuming, and ineffective for complex networks. To this purpose, a novel deep sparse autoencoder for community detection, named DSACD, is proposed in this paper. In DSACD, a similarity matrix is constructed to reveal the indirect connections between nodes and a deep sparse automatic encoder based on unsupervised learning is designed to reduce the dimension and extract the feature structure of complex networks. During the process of back propagation, L-BFGS avoid the calculation of Hessian matrix which can increase the calculation speed. The performance of DSACD is validated on synthetic and real-world networks. Experimental results demonstrate the effectiveness of DSACD and the systematic comparisons with four algorithms confirm a significant improvement in terms of three index<jats:italic>F<\/jats:italic><jats:sub>same<\/jats:sub>,<jats:italic>NMI<\/jats:italic>, and modularity<jats:italic>Q<\/jats:italic>. Finally, these achieved received signal strength indication (RSSI) data set can be aggregated into 64 correct communities, which further confirms its usability in indoor location systems.<\/jats:p>","DOI":"10.1186\/s13638-020-01706-4","type":"journal-article","created":{"date-parts":[[2020,5,11]],"date-time":"2020-05-11T12:03:48Z","timestamp":1589198628000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":16,"title":["A new deep sparse autoencoder for community detection in complex networks"],"prefix":"10.1186","volume":"2020","author":[{"given":"Rong","family":"Fei","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jingyuan","family":"Sha","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qingzheng","family":"Xu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bo","family":"Hu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kan","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shasha","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2020,5,11]]},"reference":[{"issue":"3-5","key":"1706_CR1","doi-asserted-by":"publisher","first-page":"75","DOI":"10.1016\/j.physrep.2009.11.002","volume":"486","author":"S. 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