{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,2]],"date-time":"2026-05-02T06:51:30Z","timestamp":1777704690748,"version":"3.51.4"},"reference-count":28,"publisher":"SAGE Publications","issue":"6","license":[{"start":{"date-parts":[[2018,12,24]],"date-time":"2018-12-24T00:00:00Z","timestamp":1545609600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Journal of Intelligent &amp; Fuzzy Systems"],"published-print":{"date-parts":[[2018,12,24]]},"abstract":"<jats:p>\n                    Similarity search for content-based retrieval - a sustained problem; many applications endures. Most of the similarity measures intend focusing the least possible set of elements to find an answer. In the literature, most work is based on splitting the target data set into subsets using balls. However, in the era of big data, where efficient indexing is of vital importance, the subspace volumes grow exponentially, which could degenerate the index. This problem arises due to inherent insufficiency of space partitioning interlaced with the overlap factor among the regions. This affects the search algorithms thereby rendering these methods ineffective as it gets hard to store, manage and analyze the aforementioned quantities. A good topology should avoid biased allocation of objects for separable sets and should not influence the structure of the index. We put-forward a novel technique for indexing;\n                    <jats:italic>IMB-tree<\/jats:italic>\n                    , which limits the volume space, excludes the empty sets; the separable partitions, does not contain objects and creates eXtended regions that will be inserted into a new index named\n                    <jats:italic>eXtended index<\/jats:italic>\n                    , implemented in a P2P environment. These can reunite all objects in one of the subsets-partitions; either in a separable set or in the exclusion set, keeping the others empty. We also discussed the efficiency of construction and search algorithms, as well as the quality of the index. The experimental results show interesting performances.\n                  <\/jats:p>","DOI":"10.3233\/jifs-18398","type":"journal-article","created":{"date-parts":[[2018,12,24]],"date-time":"2018-12-24T12:55:54Z","timestamp":1545656154000},"page":"6469-6478","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":1,"title":["Indexing through separable partitioning for complex data sharing in P2P systems"],"prefix":"10.1177","volume":"35","author":[{"given":"Zineddine","family":"Kouahla","sequence":"first","affiliation":[{"name":"Department of Computer Science, LABSTIC Laboratory, Guelma, Algeria"}]},{"given":"Adeel","family":"Anjum","sequence":"additional","affiliation":[{"name":"COMSATS University Islamabad, Islamabad, Pakistan"}]},{"given":"Hamid","family":"Seridi","sequence":"additional","affiliation":[{"name":"Department of Computer Science, LABSTIC Laboratory, Guelma, Algeria"}]}],"member":"179","published-online":{"date-parts":[[2018,12,24]]},"reference":[{"key":"e_1_3_1_2_2","doi-asserted-by":"publisher","DOI":"10.14778\/3204028.3204034"},{"key":"e_1_3_1_3_2","first-page":"2014","volume-title":"Similarity Search and Applications - 7th International Conference, SISAP 2014","author":"Arroyuelo D.","unstructured":"ArroyueloD. A dynamic pivoting algorithm based on spatial approximation indexes, in Similarity Search and Applications - 7th International Conference, SISAP 2014, Los Cabos, Mexico, Proceedings, 2014."},{"key":"e_1_3_1_4_2","doi-asserted-by":"publisher","DOI":"10.1023\/A:1009670119569"},{"key":"e_1_3_1_5_2","first-page":"20","volume-title":"Proceedings of the 1st International Conference on Scalable Information Systems (InfoScale)","author":"Batko M.","year":"2006","unstructured":"BatkoM., NovakD., FalchiF., ZezulaP. On scalability of the similarity search in the world of peers, in, Proceedings of the 1st International Conference on Scalable Information Systems (InfoScale), Hong Kong, China, ACM Press, 2006, pp. 20\u201331."},{"key":"e_1_3_1_6_2","first-page":"88","article-title":"Searching 100m images by content similarity, in","author":"Bolettieri P.","year":"2009","unstructured":"BolettieriP., FalchiF., LuccheseC., MassY., PeregoR., RabittiF., Shmueli-ScheuerM. Searching 100m images by content similarity, in, Postproceedings of the 5th Italian Research Conference on Digital Library Systems (IRCD), Padova, Italy, 2009, pp. 88\u201399.","journal-title":"Postproceedings of the 5th Italian Research Conference on Digital Library Systems (IRCD)"},{"key":"e_1_3_1_7_2","doi-asserted-by":"publisher","DOI":"10.1145\/328939.328959"},{"key":"e_1_3_1_8_2","doi-asserted-by":"publisher","DOI":"10.1145\/362003.362025"},{"key":"e_1_3_1_9_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.is.2010.06.004"},{"key":"e_1_3_1_10_2","article-title":"Clustering and singular value decomposition for approximate similarity searches in high dimensional spaces","author":"Castelli V.","year":"2000","unstructured":"CastelliV., ThomasianA., LiC.-S. Clustering and singular value decomposition for approximate similarity searches in high dimensional spaces, IEEE Transactions on Knowledge and Data Eng (TKDE) (2000).","journal-title":"IEEE Transactions on Knowledge and Data Eng (TKDE)"},{"key":"e_1_3_1_11_2","doi-asserted-by":"publisher","DOI":"10.1145\/502807.502808"},{"key":"e_1_3_1_12_2","article-title":"Dynamic vp-tree indexing for nnearest neighbor search given pair-wise distances","author":"Fu A.W.-C.","year":"2012","unstructured":"FuA.W.-C., ChanP.M.-S., CheungY.-L., MoonY.S. Dynamic vp-tree indexing for nnearest neighbor search given pair-wise distances, The VLDB Journal Very Large Data Bases (2012).","journal-title":"The VLDB Journal Very Large Data Bases"},{"key":"e_1_3_1_13_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-25087-8_7"},{"key":"e_1_3_1_14_2","doi-asserted-by":"publisher","DOI":"10.1145\/280277.280279"},{"key":"e_1_3_1_15_2","article-title":"A new division operator to handle complex objects in very large relational datasets, in","author":"Gonzaga A.S.","year":"2017","unstructured":"GonzagaA.S., CordeiroR.L.F. A new division operator to handle complex objects in very large relational datasets, in, EDBT, 2017.","journal-title":"EDBT"},{"key":"e_1_3_1_16_2","article-title":"A queries-based structure for similarity searching in static and dynamic metric spaces","author":"Hanyf Y.","year":"2018","unstructured":"HanyfY., SilkanH. A queries-based structure for similarity searching in static and dynamic metric spaces, Journal of King Saud University - Computer and Information Sciences (2018).","journal-title":"Journal of King Saud University - Computer and Information Sciences"},{"key":"e_1_3_1_17_2","first-page":"375","article-title":"Dahctree: An effective index for approximate search in high-dimensional metric spaces","volume":"1","author":"Almeida J.","year":"2010","unstructured":"AlmeidaJ., ValleE., TorresR.da.S., LeiteN.J. Dahctree: An effective index for approximate search in high-dimensional metric spaces, Journal of Information and Data Management 1 (2010), 375\u2013390.","journal-title":"Journal of Information and Data Management"},{"key":"e_1_3_1_18_2","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2015.2506556"},{"key":"e_1_3_1_19_2","article-title":"Bregman vantage point trees for efficient nearest neighbor queries","author":"Nielsen F.","year":"2009","unstructured":"NielsenF. Bregman vantage point trees for efficient nearest neighbor queries, in Proceedings of Multimedia and Exp (ICME) IEEE, 2009.","journal-title":"Proceedings of Multimedia and Exp (ICME) IEEE"},{"key":"e_1_3_1_20_2","first-page":"247","volume-title":"Spatial kd-Tree: A Data Structure for Geographic Database","author":"Ooi B.C.","year":"1987","unstructured":"OoiB.C., Spatial kd-Tree: A Data Structure for Geographic Database, Springer Berlin Heidelberg, Berlin Heidelberg, 1987, pp. 247\u2013258."},{"key":"e_1_3_1_21_2","article-title":"Approximate furthest neighbor in high dimensions, in","author":"Pagh R.","year":"2015","unstructured":"PaghR., SilvestriF., SivertsenJ., SkalaM. Approximate furthest neighbor in high dimensions, in, Similarity Search and Applications - 8th International Conference, SISAP 2015, Glasgow, UK, 2015, Proceedings.","journal-title":"Similarity Search and Applications - 8th International Conference, SISAP 2015"},{"key":"e_1_3_1_22_2","doi-asserted-by":"crossref","unstructured":"PolaI.R.V. TrainaA.J.M. TrainaC. KasterD.S. Improving metric access methods with bucket files in Similarity Search and Applications AmatoG. ConnorR. FalchiF. and GennaroC. eds. Cham 2015 Springer International Publishing pp. 65\u201376.","DOI":"10.1007\/978-3-319-25087-8_6"},{"key":"e_1_3_1_23_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.datak.2014.09.001"},{"key":"e_1_3_1_24_2","author":"Revathi B.","year":"2018","unstructured":"RevathiB., SudhaG., Retrieval performance analysis of multibiometric database using optimised multidimensional spectral hashing based indexing, 2018.","journal-title":"Retrieval performance analysis of multibiometric database using optimised multidimensional spectral hashing based indexing"},{"key":"e_1_3_1_25_2","doi-asserted-by":"publisher","DOI":"10.1109\/34.895972"},{"key":"e_1_3_1_26_2","doi-asserted-by":"publisher","DOI":"10.3233\/IDA-150418"},{"key":"e_1_3_1_27_2","unstructured":"YianilosP.N. Data structures and algorithms for nearest neighbor search in general metric spaces Proceedings of the 4th Annual In ACM-SIAM Symposium on Discrete Algorithms 1993 pp. 311\u2013321."},{"key":"e_1_3_1_28_2","first-page":"220","volume-title":"Similarity Search: The Metric Space Approach","author":"Zezula P.","year":"2010","unstructured":"ZezulaP., AmatoG., DohnalV., BatkoM., Similarity Search: The Metric Space Approach, Springer, 2010, p. 220."},{"key":"e_1_3_1_29_2","first-page":"1","volume-title":"10th International Workshop on Content-Based Multimedia Indexing, CBMI 2012","author":"Zineddine K.","year":"2012","unstructured":"ZineddineK., MartinezJ. A new intersection tree for content-based image retrieval, in 10th International Workshop on Content-Based Multimedia Indexing, CBMI 2012 Annecy, France, 2012, pp. 1\u20136."}],"container-title":["Journal of Intelligent &amp; Fuzzy Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.3233\/JIFS-18398","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/full-xml\/10.3233\/JIFS-18398","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.3233\/JIFS-18398","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T09:41:47Z","timestamp":1777455707000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/10.3233\/JIFS-18398"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,12,24]]},"references-count":28,"journal-issue":{"issue":"6","published-print":{"date-parts":[[2018,12,24]]}},"alternative-id":["10.3233\/JIFS-18398"],"URL":"https:\/\/doi.org\/10.3233\/jifs-18398","relation":{},"ISSN":["1064-1246","1875-8967"],"issn-type":[{"value":"1064-1246","type":"print"},{"value":"1875-8967","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,12,24]]}}}