{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,5]],"date-time":"2025-07-05T03:10:10Z","timestamp":1751685010718,"version":"3.41.0"},"publisher-location":"Cham","reference-count":40,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783319936970"},{"type":"electronic","value":"9783319936987"}],"license":[{"start":{"date-parts":[[2018,1,1]],"date-time":"2018-01-01T00:00:00Z","timestamp":1514764800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2018,1,1]],"date-time":"2018-01-01T00:00:00Z","timestamp":1514764800000},"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":[[2018]]},"DOI":"10.1007\/978-3-319-93698-7_18","type":"book-chapter","created":{"date-parts":[[2018,6,11]],"date-time":"2018-06-11T19:30:25Z","timestamp":1528745425000},"page":"234-246","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Large Scale Retrieval of Social Network Pages by Interests of Their Followers"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0781-8633","authenticated-orcid":false,"given":"Elena","family":"Mikhalkova","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2346-402X","authenticated-orcid":false,"given":"Yuri","family":"Karyakin","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0683-6138","authenticated-orcid":false,"given":"Igor","family":"Glukhikh","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2018,6,12]]},"reference":[{"key":"18_CR1","doi-asserted-by":"crossref","unstructured":"Agichtein, E., Brill, E., Dumais, S., Ragno, R.: Learning user interaction models for predicting web search result preferences. In: Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 3\u201310. ACM (2006)","DOI":"10.1145\/1148170.1148175"},{"key":"18_CR2","doi-asserted-by":"crossref","unstructured":"Ahmed, A., Low, Y., Aly, M., Josifovski, V., Smola, A.J.: Scalable distributed inference of dynamic user interests for behavioral targeting. In: KDD (2011)","DOI":"10.1145\/2020408.2020433"},{"key":"18_CR3","doi-asserted-by":"crossref","unstructured":"Al-Kouz, A., Albayrak, S.: An interests discovery approach in social networks based on semantically enriched graphs. In: 2012 IEEE\/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), pp. 1272\u20131277. IEEE (2012)","DOI":"10.1109\/ASONAM.2012.219"},{"key":"18_CR4","unstructured":"Bakalov, F., K\u00f6nig-Ries, B., Nauerz, A., Welsch, M.: A hybrid approach to identifying user interests in web portals. In: IICS, pp. 123\u2013134 (2009)"},{"key":"18_CR5","volume-title":"The Process of Government","author":"AF Bentley","year":"1955","unstructured":"Bentley, A.F.: The Process of Government. Ripol Klassik, Moskva (1955)"},{"key":"18_CR6","series-title":"CISM International Centre for Mechanical Sciences","doi-asserted-by":"publisher","first-page":"99","DOI":"10.1007\/978-3-7091-2490-1_10","volume-title":"UM99 User Modeling","author":"D Billsus","year":"1999","unstructured":"Billsus, D., Pazzani, M.J.: A hybrid user model for news story classification. In: Kay, J. (ed.) UM99 User Modeling. CICMS, vol. 407, pp. 99\u2013108. Springer, Vienna (1999). https:\/\/doi.org\/10.1007\/978-3-7091-2490-1_10"},{"issue":"January","key":"18_CR7","first-page":"993","volume":"3","author":"DM Blei","year":"2003","unstructured":"Blei, D.M., Ng, A.Y., Jordan, M.I.: Latent Dirichlet allocation. J. Mach. Learn. Res. 3(January), 993\u20131022 (2003)","journal-title":"J. Mach. Learn. Res."},{"issue":"3","key":"18_CR8","doi-asserted-by":"publisher","first-page":"84","DOI":"10.1007\/s10550-006-0080-3","volume":"24","author":"P Bonhard","year":"2006","unstructured":"Bonhard, P., Sasse, M.A.: \u2018Knowing me, knowing you\u2019 - using profiles and social networking to improve recommender systems. BT Technol. J. 24(3), 84\u201398 (2006)","journal-title":"BT Technol. J."},{"issue":"3","key":"18_CR9","doi-asserted-by":"publisher","first-page":"2","DOI":"10.1002\/dir.20082","volume":"21","author":"J Brown","year":"2007","unstructured":"Brown, J., Broderick, A.J., Lee, N.: Word of mouth communication within online communities: conceptualizing the online social network. J. Interact. Mark. 21(3), 2\u201320 (2007)","journal-title":"J. Interact. Mark."},{"key":"18_CR10","doi-asserted-by":"crossref","unstructured":"Dugan, C., Muller, M., Millen, D.R., Geyer, W., Brownholtz, B., Moore, M.: The Dogear game: a social bookmark recommender system. In: Proceedings of the 2007 International ACM Conference on Supporting Group Work, pp. 387\u2013390. ACM (2007)","DOI":"10.1145\/1316624.1316683"},{"key":"18_CR11","doi-asserted-by":"crossref","unstructured":"Firan, C.S., Nejdl, W., Paiu, R.: The benefit of using tag-based profiles. In: Web Conference, LA-WEB 2007. Latin American, pp. 32\u201341. IEEE (2007)","DOI":"10.1109\/LA-Web.2007.13"},{"issue":"2","key":"18_CR12","doi-asserted-by":"publisher","first-page":"545","DOI":"10.1007\/s11067-015-9288-4","volume":"16","author":"M Fire","year":"2016","unstructured":"Fire, M., Puzis, R.: Organization mining using online social networks. Netw. Spat. Econ. 16(2), 545\u2013578 (2016)","journal-title":"Netw. Spat. Econ."},{"issue":"1","key":"18_CR13","doi-asserted-by":"publisher","first-page":"65","DOI":"10.1023\/A:1011145532042","volume":"11","author":"G Fischer","year":"2001","unstructured":"Fischer, G.: User modeling in human-computer interaction. User Model. User-Adap. Inter. 11(1), 65\u201386 (2001)","journal-title":"User Model. User-Adap. Inter."},{"key":"18_CR14","unstructured":"Frolov, S.: Sociology: personality and society. The main factors of personality development (1994)"},{"key":"18_CR15","doi-asserted-by":"crossref","unstructured":"Gomaa, W.H., Fahmy, A.A.: A survey of text similarity approaches. Int. J. Comput. Appl. 68(13) (2013)","DOI":"10.5120\/11638-7118"},{"key":"18_CR16","doi-asserted-by":"crossref","unstructured":"Groh, G., Ehmig, C.: Recommendations in taste related domains: collaborative filtering vs. social filtering. In: Proceedings of the 2007 International ACM Conference on Supporting Group Work, pp. 127\u2013136. ACM (2007)","DOI":"10.1145\/1316624.1316643"},{"key":"18_CR17","doi-asserted-by":"crossref","unstructured":"Guy, I., Zwerdling, N., Carmel, D., Ronen, I., Uziel, E., Yogev, S., Ofek-Koifman, S.: Personalized recommendation of social software items based on social relations. In: Proceedings of the Third ACM Conference on Recommender Systems, pp. 53\u201360. ACM (2009)","DOI":"10.1145\/1639714.1639725"},{"key":"18_CR18","doi-asserted-by":"crossref","unstructured":"Li, X., Guo, L., Zhao, Y.E.: Tag-based social interest discovery. In: Proceedings of the 17th International Conference on World Wide Web, pp. 675\u2013684. ACM (2008)","DOI":"10.1145\/1367497.1367589"},{"key":"18_CR19","doi-asserted-by":"crossref","unstructured":"Li, Y., Dong, M., Huang, R.: Special interest groups discovery and semantic navigation support within online discussion forums. In: IEEE International Joint Conference on Neural Networks, IJCNN 2008. (IEEE World Congress on Computational Intelligence), pp. 3904\u20133911. IEEE (2008)","DOI":"10.1109\/IJCNN.2008.4634359"},{"key":"18_CR20","unstructured":"McCallum, A., Corrada-Emmanuel, A., Wang, X.: Topic and role discovery in social networks. In: IJCAI, vol. 5, pp. 786\u2013791. Citeseer (2005)"},{"issue":"5","key":"18_CR21","doi-asserted-by":"publisher","first-page":"672","DOI":"10.2307\/2084686","volume":"3","author":"RK Merton","year":"1938","unstructured":"Merton, R.K.: Social structure and anomie. Am. Sociol. Rev. 3(5), 672\u2013682 (1938)","journal-title":"Am. Sociol. Rev."},{"key":"18_CR22","unstructured":"Mikhalkova, E., Karyakin, Y., Ganzherli, N.: A comparative analysis of social network pages by interests of their followers. arXiv preprint arXiv:1707.05481v2 (2017)"},{"issue":"2","key":"18_CR23","doi-asserted-by":"publisher","first-page":"026113","DOI":"10.1103\/PhysRevE.69.026113","volume":"69","author":"ME Newman","year":"2004","unstructured":"Newman, M.E., Girvan, M.: Finding and evaluating community structure in networks. Phys. Rev. E 69(2), 026113 (2004)","journal-title":"Phys. Rev. E"},{"issue":"5\u20136","key":"18_CR24","doi-asserted-by":"publisher","first-page":"393","DOI":"10.1023\/A:1006544522159","volume":"13","author":"MJ Pazzani","year":"1999","unstructured":"Pazzani, M.J.: A framework for collaborative, content-based and demographic filtering. Artif. Intell. Rev. 13(5\u20136), 393\u2013408 (1999)","journal-title":"Artif. Intell. Rev."},{"key":"18_CR25","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"325","DOI":"10.1007\/978-3-540-72079-9_10","volume-title":"The Adaptive Web","author":"MJ Pazzani","year":"2007","unstructured":"Pazzani, M.J., Billsus, D.: Content-based recommendation systems. In: Brusilovsky, P., Kobsa, A., Nejdl, W. (eds.) The Adaptive Web. LNCS, vol. 4321, pp. 325\u2013341. Springer, Heidelberg (2007). https:\/\/doi.org\/10.1007\/978-3-540-72079-9_10"},{"key":"18_CR26","first-page":"2825","volume":"12","author":"F Pedregosa","year":"2011","unstructured":"Pedregosa, F., Varoquaux, G., Gramfort, A., Michel, V., Thirion, B., Grisel, O., Blondel, M., Prettenhofer, P., Weiss, R., Dubourg, V., Vanderplas, J., Passos, A., Cournapeau, D., Brucher, M., Perrot, M., Duchesnay, E.: Scikit-learn: machine learning in Python. J. Mach. Learn. Res. 12, 2825\u20132830 (2011)","journal-title":"J. Mach. Learn. Res."},{"key":"18_CR27","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"496","DOI":"10.1007\/978-3-319-49004-5_32","volume-title":"Knowledge Engineering and Knowledge Management","author":"G Piao","year":"2016","unstructured":"Piao, G., Breslin, J.G.: Interest representation, enrichment, dynamics, and propagation: a study of the synergetic effect of different user modeling dimensions for personalized recommendations on Twitter. In: Blomqvist, E., Ciancarini, P., Poggi, F., Vitali, F. (eds.) EKAW 2016. LNCS (LNAI), vol. 10024, pp. 496\u2013510. Springer, Cham (2016). https:\/\/doi.org\/10.1007\/978-3-319-49004-5_32"},{"key":"18_CR28","doi-asserted-by":"crossref","unstructured":"Piao, S., Whittle, J.: A feasibility study on extracting Twitter users\u2019 interests using NLP tools for serendipitous connections. In: 2011 IEEE Third International Conference on Privacy, Security, Risk and Trust (PASSAT) and 2011 IEEE Third International Conference on Social Computing (SocialCom), pp. 910\u2013915. IEEE (2011)","DOI":"10.1109\/PASSAT\/SocialCom.2011.164"},{"issue":"1","key":"18_CR29","first-page":"16","volume":"10","author":"D Ramage","year":"2010","unstructured":"Ramage, D., Dumais, S.T., Liebling, D.J.: Characterizing microblogs with topic models. ICWSM 10(1), 16 (2010)","journal-title":"ICWSM"},{"key":"18_CR30","unstructured":"Reicher, S.: The determination of collective behaviour. Soc. Ident. Intergroup Relat., pp. 41\u201383 (1982)"},{"key":"18_CR31","doi-asserted-by":"crossref","DOI":"10.4135\/9781529716597","volume-title":"Social Network Analysis","author":"J Scott","year":"2017","unstructured":"Scott, J.: Social Network Analysis. SAGE Publications, Thousand Oaks (2017)"},{"key":"18_CR32","doi-asserted-by":"crossref","unstructured":"Sen, S., Vig, J., Riedl, J.: Tagommenders: connecting users to items through tags. In: Proceedings of the 18th International Conference on World Wide Web, pp. 671\u2013680. ACM (2009)","DOI":"10.1145\/1526709.1526800"},{"key":"18_CR33","doi-asserted-by":"crossref","unstructured":"Shen, W., Wang, J., Luo, P., Wang, M.: Linking named entities in tweets with knowledge base via user interest modeling. In: Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 68\u201376. ACM (2013)","DOI":"10.1145\/2487575.2487686"},{"key":"18_CR34","doi-asserted-by":"publisher","first-page":"20953","DOI":"10.1109\/ACCESS.2017.2675839","volume":"5","author":"Lei-Lei Shi","year":"2017","unstructured":"Shi, L.L., Liu, L., Wu, Y., Jiang, L., Hardy, J.: Event detection and user interest discovering in social media data streams. IEEE Access 5, 20953\u201320964 (2017)","journal-title":"IEEE Access"},{"key":"18_CR35","doi-asserted-by":"crossref","unstructured":"Stefani, A., Strapparava, C.: Exploiting NLP techniques to build user model for web sites: the use of WordNet in SiteIF project. In: Proceedings of the 2nd Workshop on Adaptive Systems and User Modeling on the WWW (1999)","DOI":"10.1007\/3-540-44595-1_53"},{"key":"18_CR36","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"632","DOI":"10.1007\/978-3-540-88564-1_40","volume-title":"The Semantic Web - ISWC 2008","author":"M Szomszor","year":"2008","unstructured":"Szomszor, M., Alani, H., Cantador, I., O\u2019Hara, K., Shadbolt, N.: Semantic modelling of user interests based on cross-folksonomy analysis. In: Sheth, A., Staab, S., Dean, M., Paolucci, M., Maynard, D., Finin, T., Thirunarayan, K. (eds.) ISWC 2008. LNCS, vol. 5318, pp. 632\u2013648. Springer, Heidelberg (2008). https:\/\/doi.org\/10.1007\/978-3-540-88564-1_40"},{"key":"18_CR37","doi-asserted-by":"crossref","unstructured":"Volkova, S., Coppersmith, G., Van Durme, B.: Inferring user political preferences from streaming communications. In: Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Long Papers), vol. 1, pp. 186\u2013196 (2014)","DOI":"10.3115\/v1\/P14-1018"},{"key":"18_CR38","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"209","DOI":"10.1007\/978-3-319-12844-3_18","volume-title":"Information Retrieval Technology","author":"Q Wang","year":"2014","unstructured":"Wang, Q., Xu, J., Li, H.: User message model: a new approach to scalable user modeling on microblog. In: Jaafar, A., Mohamad Ali, N., Mohd Noah, S.A., Smeaton, A.F., Bruza, P., Bakar, Z.A., Jamil, N., Sembok, T.M.T. (eds.) AIRS 2014. LNCS, vol. 8870, pp. 209\u2013220. Springer, Cham (2014). https:\/\/doi.org\/10.1007\/978-3-319-12844-3_18"},{"issue":"4","key":"18_CR39","doi-asserted-by":"publisher","first-page":"280892","DOI":"10.1155\/2014\/280892","volume":"10","author":"Shuo Xu","year":"2014","unstructured":"Xu, S., Shi, Q., Qiao, X., Zhu, L., Zhang, H., Jung, H., Lee, S., Choi, S.P.: Adynamic users\u2019 interest discovery model with distributed inference algorithm. Int. J. Distrib. Sens. Netw. 10(4), Article ID 280892 (2014)","journal-title":"International Journal of Distributed Sensor Networks"},{"issue":"1","key":"18_CR40","doi-asserted-by":"publisher","first-page":"181","DOI":"10.1007\/s10115-013-0693-z","volume":"42","author":"J Yang","year":"2015","unstructured":"Yang, J., Leskovec, J.: Defining and evaluating network communities based on ground-truth. Knowl. Inf. Syst. 42(1), 181\u2013213 (2015)","journal-title":"Knowl. Inf. Syst."}],"container-title":["Lecture Notes in Computer Science","Computational Science \u2013 ICCS 2018"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-319-93698-7_18","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,7,5]],"date-time":"2025-07-05T02:29:44Z","timestamp":1751682584000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-319-93698-7_18"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018]]},"ISBN":["9783319936970","9783319936987"],"references-count":40,"URL":"https:\/\/doi.org\/10.1007\/978-3-319-93698-7_18","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2018]]},"assertion":[{"value":"12 June 2018","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICCS","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Computational Science","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Wuxi","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2018","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"11 June 2018","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"13 June 2018","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"18","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"iccs-computsci2018","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/www.iccs-meeting.org\/iccs2018\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"EasyChair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"406","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"148","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"60","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"36% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Acceptance rate in the Main Track is 28%. Acceptance rate in the workshops is 43%. A high acceptance rate in the workshops is explained by the nature of these thematic sessions, where many experts in a particular field are personally invited by workshop organisers to participate in their sessions.","order":10,"name":"additional_info_on_review_process","label":"Additional Info on Review Process","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"This content has been made available to all.","name":"free","label":"Free to read"}]}}