{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,2]],"date-time":"2025-08-02T17:51:07Z","timestamp":1754157067313,"version":"3.41.2"},"reference-count":17,"publisher":"Emerald","issue":"1","license":[{"start":{"date-parts":[[2013,1,4]],"date-time":"2013-01-04T00:00:00Z","timestamp":1357257600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.emerald.com\/insight\/site-policies"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2013,1,4]]},"abstract":"<jats:sec><jats:title content-type=\"abstract-heading\">Purpose<\/jats:title><jats:p>The purpose of this paper is to effectively deal with querying of classification with membership.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-heading\">Design\/methodology\/approach<\/jats:title><jats:p>The authors propose a scheme comprising a layer of Bloom filter for membership checking and a second layer based on neural network for dealing with the classification requirement.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-heading\">Findings<\/jats:title><jats:p>Not only could false positives be dramatically decreased, but also classification could be achieved with the proposed scheme.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-heading\">Research limitations\/implications<\/jats:title><jats:p>The experimental data were randomly generated instead of real\u2010world ones.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-heading\">Practical implications<\/jats:title><jats:p>It is difficult to implement this scheme in a real\u2010world environment, such as the internet. Second, the neural network requires time to converge to a satisfactory level.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-heading\">Social implications<\/jats:title><jats:p>Internet ethic might be compromised by hackers once they find a way around the filtering mechanism.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-heading\">Originality\/value<\/jats:title><jats:p>The neural network was moditified and utilized for the first time to be suitable for our purpose. Second, the two\u2010layer design shows effectiveness.<\/jats:p><\/jats:sec>","DOI":"10.1108\/03684921311295493","type":"journal-article","created":{"date-parts":[[2013,3,25]],"date-time":"2013-03-25T14:13:18Z","timestamp":1364220798000},"page":"82-93","source":"Crossref","is-referenced-by-count":1,"title":["A two\u2010layer scheme for membership and classification querying"],"prefix":"10.1108","volume":"42","author":[{"given":"Heng","family":"Ma","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hung\u2010Yu","family":"Cheng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"140","reference":[{"key":"key2022022020291248000_b2","doi-asserted-by":"crossref","unstructured":"Alagu Priya, A.G. and Lim, H. (2010), \u201cHierarchical packet classification using a bloom filter and rule\u2010priority tries\u201d, Computer Communications, Vol. 33, pp. 1215\u201026.","DOI":"10.1016\/j.comcom.2010.03.009"},{"key":"key2022022020291248000_b1","doi-asserted-by":"crossref","unstructured":"Albus, J.S. (1975), \u201cA new approach to manipulator control: the cerebellar model articulation controller (CMAC)\u201d, ASME J. Dynamic Systems, Measurement, Control, Vol. 97, pp. 220\u20107.","DOI":"10.1115\/1.3426922"},{"key":"key2022022020291248000_b3","doi-asserted-by":"crossref","unstructured":"Almeida, P.S., Baquero, C., Pregui\u00e7a, N. and Hutchison, D. (2007), \u201cScalable bloom filters\u201d, Information Processing Letters, Vol. 101, pp. 255\u201061.","DOI":"10.1016\/j.ipl.2006.10.007"},{"key":"key2022022020291248000_b4","doi-asserted-by":"crossref","unstructured":"Antichi, G., Ficara, D., Giordano, S., Procissi, G. and Vitucci, F. (2009), \u201cCounting bloom filters for pattern matching and anti\u2010evasion at the wire speed\u201d, IEEE Networking, Vol. 23 No. 1, pp. 30\u20105.","DOI":"10.1109\/MNET.2009.4804321"},{"key":"key2022022020291248000_b5","doi-asserted-by":"crossref","unstructured":"Bonomi, F., Mitzenmacher, M., Panigrahy, R., Singh, S. and Varghese, G. (2006), \u201cAn improved construction for counting bloom filters\u201d, 14th Annual European Symposium, Zurich, Switzerland, September, pp. 684\u201095.","DOI":"10.1007\/11841036_61"},{"key":"key2022022020291248000_b6","unstructured":"Chen, H., Jin, H., Chen, L., Liu, Y. and Ni, L.M. (2011), \u201cOptimizing bloom filter settings in peer\u2010to\u2010peer multi\u2010keyword searching\u201d, IEEE Transactions on Knowledge and Data Engineering, Vol. 23 No. 1, pp. 1282\u201095."},{"key":"key2022022020291248000_b7","doi-asserted-by":"crossref","unstructured":"Cohen, S. and Matias, Y. (2003), \u201cSpectral bloom filters\u201d, 22nd ACM International Conference on Management of Data (SIGMOD), June, pp. 241\u201052.","DOI":"10.1145\/872757.872787"},{"key":"key2022022020291248000_b8","doi-asserted-by":"crossref","unstructured":"Dharmapurikar, S., Krishnamurthy, P., Sproull, T.S. and Lockwood, J.W. (2004), \u201cDeep packet inspection using parallel bloom filters\u201d, IEEE Micro, Vol. 24 No. 1, pp. 52\u201061.","DOI":"10.1109\/MM.2004.1268997"},{"key":"key2022022020291248000_b9","doi-asserted-by":"crossref","unstructured":"Guo, D., Liu, Y., Li, X. and Yang, P. (2010a), \u201cFalse negative problem of counting bloom filter\u201d, IEEE Transactions on Knowledge and Data Engineering, Vol. 22 No. 5, pp. 651\u201064.","DOI":"10.1109\/TKDE.2009.209"},{"key":"key2022022020291248000_b10","doi-asserted-by":"crossref","unstructured":"Guo, D., Wu, J., Chen, H., Yuan, Y. and Luo, X. (2010b), \u201cThe dynamic bloom filters\u201d, IEEE Transactions on Knowledge and Data Engineering, Vol. 22 No. 1, pp. 120\u201033.","DOI":"10.1109\/TKDE.2009.57"},{"key":"key2022022020291248000_b12","doi-asserted-by":"crossref","unstructured":"Lee, C.\u2010H. and Chung, C.\u2010W. (2011), \u201cAn approximate duplicate elimination in RFID data streams\u201d, Data & Knowledge Engineering, Vol. 70, pp. 1070\u201087.","DOI":"10.1016\/j.datak.2011.07.007"},{"key":"key2022022020291248000_b13","doi-asserted-by":"crossref","unstructured":"Li, K. and Zhong, Z. (2006), \u201cFast statistical spam filter by approximate classifications\u201d, SIGMetrics\/Performance'06, Saint Malo, France, June, pp. 347\u201058.","DOI":"10.1145\/1140103.1140317"},{"key":"key2022022020291248000_b14","doi-asserted-by":"crossref","unstructured":"Mitzenmacher, M. (2002), \u201cCompressed bloom filters\u201d, IEEE\/ACM Transactions Networking, Vol. 10 No. 5, pp. 604\u201012.","DOI":"10.1109\/TNET.2002.803864"},{"key":"key2022022020291248000_b15","doi-asserted-by":"crossref","unstructured":"Rothenberg, C.E., Macapuna, C.A.B., Verdi, F.L. and Magalh\u00e3es, M.F. (2010), \u201cThe deletable bloom filter: a new member of the bloom family\u201d, IEEE Communications, Vol. 14 No. 6, pp. 557\u20109.","DOI":"10.1109\/LCOMM.2010.06.100344"},{"key":"key2022022020291248000_b16","doi-asserted-by":"crossref","unstructured":"Xiao, B. and Hua, Y. (2010), \u201cUsing parallel bloom filters for multiattribute representation on network services\u201d, IEEE Transactions on Parallel and Distributed Systems, Vol. 21 No. 1, pp. 20\u201032.","DOI":"10.1109\/TPDS.2009.39"},{"key":"key2022022020291248000_b17","doi-asserted-by":"crossref","unstructured":"Yu, H. and Mahapatra, R.N. (2011), \u201cA power and throughput\u2010efficient packet classifier with n bloom filters\u201d, IEEE Transactions on Computers, Vol. 60 No. 8, pp. 1182\u201093.","DOI":"10.1109\/TC.2010.213"},{"key":"key2022022020291248000_frd1","doi-asserted-by":"crossref","unstructured":"Huang, K., Zhang, D. and Qin, Z. (2010), \u201cAccelerating the bit\u2010split string matching algorithm using bloom filters\u201d, Computer Communications, Vol. 33, pp. 1785\u201094.","DOI":"10.1016\/j.comcom.2010.04.043"}],"container-title":["Kybernetes"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/www.emeraldinsight.com\/doi\/full-xml\/10.1108\/03684921311295493","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.emerald.com\/insight\/content\/doi\/10.1108\/03684921311295493\/full\/xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.emerald.com\/insight\/content\/doi\/10.1108\/03684921311295493\/full\/html","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,7,24]],"date-time":"2025-07-24T23:27:46Z","timestamp":1753399666000},"score":1,"resource":{"primary":{"URL":"http:\/\/www.emerald.com\/k\/article\/42\/1\/82-93\/446501"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2013,1,4]]},"references-count":17,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2013,1,4]]}},"alternative-id":["10.1108\/03684921311295493"],"URL":"https:\/\/doi.org\/10.1108\/03684921311295493","relation":{},"ISSN":["0368-492X"],"issn-type":[{"type":"print","value":"0368-492X"}],"subject":[],"published":{"date-parts":[[2013,1,4]]}}}