{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,28]],"date-time":"2025-03-28T07:41:19Z","timestamp":1743147679334,"version":"3.40.3"},"publisher-location":"Cham","reference-count":35,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783031140532"},{"type":"electronic","value":"9783031140549"}],"license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022]]},"DOI":"10.1007\/978-3-031-14054-9_23","type":"book-chapter","created":{"date-parts":[[2022,8,10]],"date-time":"2022-08-10T17:02:44Z","timestamp":1660150964000},"page":"239-252","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Systematic Review for Selecting Methods of Document Clustering on Semantic Similarity of Online Laboratories Repository"],"prefix":"10.1007","author":[{"given":"Saad Hikmat","family":"Haji","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Karwan","family":"Jacksi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Razwan Mohmed","family":"Salah","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,8,11]]},"reference":[{"key":"23_CR1","doi-asserted-by":"publisher","first-page":"9","DOI":"10.1016\/j.eswa.2021.114710","volume":"174","author":"V Mehta","year":"2021","unstructured":"Mehta, V.: Stamantic clustering: combining statistical and semantic features for clustering of large text datasets. Expert Syst. Appl. 174, 9 (2021)","journal-title":"Expert Syst. Appl."},{"issue":"1","key":"23_CR2","doi-asserted-by":"publisher","first-page":"664","DOI":"10.11591\/ijece.v11i1.pp664-670","volume":"11","author":"AA Jalal","year":"2021","unstructured":"Jalal, A.A., Ali, B.H.: Text documents clustering using data mining techniques. Int. J. Electr. Comput. Eng. IJECE 11(1), 664 (2021). https:\/\/doi.org\/10.11591\/ijece.v11i1.pp664-670","journal-title":"Int. J. Electr. Comput. Eng. IJECE"},{"doi-asserted-by":"publisher","unstructured":"Haji, S.H., Abdulazeez, A.M., Zeebaree, D.Q., Ahmed, F.Y.H., Zebari, D.A.: The impact of different data mining classification techniques in different datasets. In: 2021 IEEE Symposium on Industrial Electronics and Applications (ISIEA), Langkawi Island, Malaysia, pp. 1\u20136 (2021). https:\/\/doi.org\/10.1109\/ISIEA51897.2021.9510006","key":"23_CR3","DOI":"10.1109\/ISIEA51897.2021.9510006"},{"key":"23_CR4","doi-asserted-by":"publisher","first-page":"663","DOI":"10.1007\/s13042-021-01295-8","volume":"13","author":"B Diallo","year":"2022","unstructured":"Diallo, B.: Multi-view document clustering based on geometrical similarity measurement. Int. J. Mach. Learn. Cybern. 13, 663\u2013675 (2022). https:\/\/doi.org\/10.1007\/s13042-021-01295-8","journal-title":"Int. J. Mach. Learn. Cybern."},{"issue":"1","key":"23_CR5","first-page":"8","volume":"26","author":"P Zandieh","year":"2017","unstructured":"Zandieh, P., Shakibapoor, E.: Clustering data text based on semantic. Int. J. Comput. 26(1), 8 (2017)","journal-title":"Int. J. Comput."},{"doi-asserted-by":"crossref","unstructured":"Saiyad, N.Y., Prajapati, H.B., Dabhi, V.K.: A survey of document clustering using semantic approach, p. 8 (2016)","key":"23_CR6","DOI":"10.1109\/ICEEOT.2016.7755154"},{"doi-asserted-by":"publisher","unstructured":"Ali, I., Melton, A.: Semantic-based text document clustering using cognitive semantic learning and graph theory. In: 2018 IEEE 12th International Conference on Semantic Computing (ICSC), Laguna Hills, CA, USA, pp. 243\u2013247 (2018). https:\/\/doi.org\/10.1109\/ICSC.2018.00042","key":"23_CR7","DOI":"10.1109\/ICSC.2018.00042"},{"doi-asserted-by":"crossref","unstructured":"Polus, M.E., Abbas, T.: Intelligent text clustering based on semantics similarity, p. 7 (2020)","key":"23_CR8","DOI":"10.1109\/IT-ELA50150.2020.9253127"},{"doi-asserted-by":"publisher","unstructured":"Ibrahim, R.K., Zeebaree, S.R.M., Jacksi, K., Sadeeq, M.A.M., Shukur, H.M., Alkhayyat, A.: Clustering document based semantic similarity system using TFIDF and k-mean. In: 2021 International Conference on Advanced Computer Applications (ACA), Maysan, Iraq, pp. 28\u201333 (2021). https:\/\/doi.org\/10.1109\/ACA52198.2021.9626822","key":"23_CR9","DOI":"10.1109\/ACA52198.2021.9626822"},{"doi-asserted-by":"crossref","unstructured":"Bafna, P., Pramod, D., Vaidya, A.: Document clustering: TF-IDF approach, p. 6 (2016)","key":"23_CR10","DOI":"10.1109\/ICEEOT.2016.7754750"},{"doi-asserted-by":"publisher","unstructured":"Qona\u2019ah, N., Devi, A.R., Dana, I.M.G.M.: Laboratory clustering using k-means, k-medoids, and model-based clustering. Indones. J. Appl. Stat. 3(1), 64 (2020). https:\/\/doi.org\/10.13057\/ijas.v3i1.40823","key":"23_CR11","DOI":"10.13057\/ijas.v3i1.40823"},{"key":"23_CR12","first-page":"24","volume":"18","author":"R Lakshmi","year":"2021","unstructured":"Lakshmi, R., Baskar, S.: Efficient text document clustering with new similarity measures. Int. J. Bus. Intell. Data Min. 18, 24 (2021)","journal-title":"Int. J. Bus. Intell. Data Min."},{"doi-asserted-by":"publisher","unstructured":"Fatimi, S., El, C., Alaoui, L.: A framework for semantic text clustering. Int. J. Adv. Comput. Sci. Appl. 11(6) (2020). https:\/\/doi.org\/10.14569\/IJACSA.2020.0110657","key":"23_CR13","DOI":"10.14569\/IJACSA.2020.0110657"},{"doi-asserted-by":"crossref","unstructured":"Alian, M.: Semantic similarity for English and Arabic texts: a review, p. 29 (2020)","key":"23_CR14","DOI":"10.1142\/S0219649220500331"},{"doi-asserted-by":"publisher","unstructured":"Jacksi, K., Ibrahim, R.K., Zeebaree, S.R., Zebari, R.R., Sadeeq, M.A.: Clustering documents based on semantic similarity using HAC and k-mean algorithms. In: 2020 International Conference on Advanced Science and Engineering (ICOASE), Duhok, Iraq, pp. 205\u2013210 (2020). https:\/\/doi.org\/10.1109\/ICOASE51841.2020.9436570","key":"23_CR15","DOI":"10.1109\/ICOASE51841.2020.9436570"},{"doi-asserted-by":"publisher","unstructured":"Desai, S.S., Laxminarayana, J.A.: WordNet and semantic similarity based approach for document clustering. In: 2016 International Conference on Computation System and Information Technology for Sustainable Solutions (CSITSS), Bengaluru, India, pp. 312\u2013317 (2016). https:\/\/doi.org\/10.1109\/CSITSS.2016.7779377","key":"23_CR16","DOI":"10.1109\/CSITSS.2016.7779377"},{"doi-asserted-by":"publisher","unstructured":"Mohammed, S.M., Jacksi, K., Zeebaree, S.R.M.: Glove word embedding and DBSCAN algorithms for semantic document clustering. In: 2020 International Conference on Advanced Science and Engineering (ICOASE), Duhok, Iraq, pp. 1\u20136 (2020). https:\/\/doi.org\/10.1109\/ICOASE51841.2020.9436540","key":"23_CR17","DOI":"10.1109\/ICOASE51841.2020.9436540"},{"doi-asserted-by":"publisher","unstructured":"Radu, R.-G., Radulescu, I.-M., Truica, C.-O., Apostol, E.-S., Mocanu, M.: Clustering documents using the document to vector model for dimensionality reduction. In: 2020 IEEE International Conference on Automation, Quality and Testing, Robotics (AQTR), Cluj-Napoca, Romania, pp. 1\u20136 (2020). https:\/\/doi.org\/10.1109\/AQTR49680.2020.9129967","key":"23_CR18","DOI":"10.1109\/AQTR49680.2020.9129967"},{"doi-asserted-by":"publisher","unstructured":"Salih, N.M., Jacksi, K.: Semantic document clustering using k-means algorithm and ward\u2019s method. In: 2020 International Conference on Advanced Science and Engineering (ICOASE), Duhok, Iraq, pp. 1\u20136 (2020). https:\/\/doi.org\/10.1109\/ICOASE51841.2020.9436588","key":"23_CR19","DOI":"10.1109\/ICOASE51841.2020.9436588"},{"doi-asserted-by":"publisher","unstructured":"Stanchev, L.: Semantic document clustering using a similarity graph. In: 2016 IEEE Tenth International Conference on Semantic Computing (ICSC), Laguna Hills, CA, USA, pp. 1\u20138 (2016). https:\/\/doi.org\/10.1109\/ICSC.2016.8","key":"23_CR20","DOI":"10.1109\/ICSC.2016.8"},{"doi-asserted-by":"publisher","unstructured":"Hssina, B., Bouikhalene, B., Merbouha, A.: Evaluation of semantic similarity using vector space model based on textual corpus. In: 2016 13th International Conference on Computer Graphics, Imaging and Visualization (CGiV), Beni Mellal, Morocco, pp. 295\u2013300 (2016). https:\/\/doi.org\/10.1109\/CGiV.2016.64","key":"23_CR21","DOI":"10.1109\/CGiV.2016.64"},{"doi-asserted-by":"publisher","unstructured":"Stanchev, L.: Semantic document clustering using information from WordNet and DBPedia. In: 2018 IEEE 12th International Conference on Semantic Computing (ICSC), Laguna Hills, CA, USA, pp. 100\u2013107 (2018). https:\/\/doi.org\/10.1109\/ICSC.2018.00023","key":"23_CR22","DOI":"10.1109\/ICSC.2018.00023"},{"doi-asserted-by":"publisher","unstructured":"Banik, P., Gaikwad, S., Awate, A., Shaikh, S., Gunjgur, P., Padiya, P.: Semantic analysis of Wikipedia documents using ontology. In: 2018 IEEE International Conference on System, Computation, Automation and Networking (ICSCA), Pondicherry, pp. 1\u20136 (2018). https:\/\/doi.org\/10.1109\/ICSCAN.2018.8541162","key":"23_CR23","DOI":"10.1109\/ICSCAN.2018.8541162"},{"unstructured":"Zafar, A., Awais, M., Aftab, M.A.: Ontology based document data analysis, p. 7 (2018)","key":"23_CR24"},{"issue":"2","key":"23_CR25","doi-asserted-by":"publisher","first-page":"1017","DOI":"10.1007\/s11192-017-2298-x","volume":"111","author":"S Wang","year":"2017","unstructured":"Wang, S., Koopman, R.: Clustering articles based on semantic similarity. Scientometrics 111(2), 1017\u20131031 (2017). https:\/\/doi.org\/10.1007\/s11192-017-2298-x","journal-title":"Scientometrics"},{"doi-asserted-by":"publisher","unstructured":"Al-Azzawy, D.S., Al-Rufaye, F.M.L.: Arabic words clustering by using k-means algorithm. In: 2017 Annual Conference on New Trends in Information and Communications Technology Applications (NTICT), Baghdad, Iraq, pp. 263\u2013267 (2017). https:\/\/doi.org\/10.1109\/NTICT.2017.7976098","key":"23_CR26","DOI":"10.1109\/NTICT.2017.7976098"},{"key":"23_CR27","doi-asserted-by":"publisher","first-page":"715","DOI":"10.1016\/j.procs.2017.11.428","volume":"122","author":"I Blokh","year":"2017","unstructured":"Blokh, I., Alexandrov, V.: News clustering based on similarity analysis. Procedia Comput. Sci. 122, 715\u2013719 (2017). https:\/\/doi.org\/10.1016\/j.procs.2017.11.428","journal-title":"Procedia Comput. Sci."},{"unstructured":"Afreen, S., Srinivasu, D.B.: Semantic based document clustering using lexical chains, vol. 04, no. 01, p. 7 (2017)","key":"23_CR28"},{"issue":"4","key":"23_CR29","doi-asserted-by":"publisher","first-page":"2315","DOI":"10.1007\/s10586-016-0649-7","volume":"19","author":"J Jang","year":"2016","unstructured":"Jang, J., Lee, Y., Lee, S., Shin, D., Kim, D., Rim, H.: A novel density-based clustering method using word embedding features for dialogue intention recognition. Cluster Comput. 19(4), 2315\u20132326 (2016). https:\/\/doi.org\/10.1007\/s10586-016-0649-7","journal-title":"Cluster Comput."},{"doi-asserted-by":"publisher","unstructured":"Lwin, W.: Impressive approach for documents clustering using semantics relations in feature extraction. In: 2019 the 9th International Workshop on Computer Science and Engineering (2019). https:\/\/doi.org\/10.18178\/wcse.2019.03.007","key":"23_CR30","DOI":"10.18178\/wcse.2019.03.007"},{"doi-asserted-by":"publisher","unstructured":"Rafi, M., Naveed, M., Arshad, W., Rafay, H.: Exploiting document level semantics in document clustering. Int. J. Adv. Comput. Sci. Appl. 7(6) (2016). https:\/\/doi.org\/10.14569\/IJACSA.2016.070660","key":"23_CR31","DOI":"10.14569\/IJACSA.2016.070660"},{"doi-asserted-by":"publisher","unstructured":"Rafi, M., Sharif, M.N., Arshad, W., Mohsin, S., Rafay, H.: Multi-layer semantics based document clustering. In: Proceedings of the 6th International Conference on Web Intelligence, Mining and Semantics, N\u00eemes France, pp. 1\u20134, June 2016. https:\/\/doi.org\/10.1145\/2912845.2912880","key":"23_CR32","DOI":"10.1145\/2912845.2912880"},{"doi-asserted-by":"publisher","unstructured":"Singh, K.N., Devi, S.D., Devi, H.M., Mahanta, A.K.: A novel approach for dimension reduction using word embedding: an enhanced text classification approach. Int. J. Inf. Manag. Data Insights 2(1), 100061 (2022).https:\/\/doi.org\/10.1016\/j.jjimei.2022.100061","key":"23_CR33","DOI":"10.1016\/j.jjimei.2022.100061"},{"key":"23_CR34","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1155\/2021\/6661035","volume":"2021","author":"C Shan","year":"2021","unstructured":"Shan, C., Du, Y.: A web service clustering method based on semantic similarity and multidimensional scaling analysis. Sci. Program. 2021, 1\u201312 (2021). https:\/\/doi.org\/10.1155\/2021\/6661035","journal-title":"Sci. Program."},{"key":"23_CR35","doi-asserted-by":"publisher","first-page":"17","DOI":"10.1002\/cpe.5971","volume":"33","author":"M Han","year":"2021","unstructured":"Han, M., Zhang, X., Yuan, X., Jiang, J., Yun, W., Gao, C.: A survey on the techniques, applications, and performance of short text semantic similarity. Concur. Comput. Pract. Exp. 33, 17 (2021)","journal-title":"Concur. Comput. Pract. Exp."}],"container-title":["Advances in Intelligent Systems and Computing","Proceedings of the ICR\u201922 International Conference on Innovations in Computing Research"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-14054-9_23","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,8,10]],"date-time":"2022-08-10T17:05:02Z","timestamp":1660151102000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-14054-9_23"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9783031140532","9783031140549"],"references-count":35,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-14054-9_23","relation":{},"ISSN":["2194-5357","2194-5365"],"issn-type":[{"type":"print","value":"2194-5357"},{"type":"electronic","value":"2194-5365"}],"subject":[],"published":{"date-parts":[[2022]]},"assertion":[{"value":"11 August 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICR","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"The International Conference on Innovations in Computing Research","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Athens","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Greece","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2022","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"29 August 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"31 August 2022","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icr12022","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/iicser.org\/icr22","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}