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第3期 王大玲,等:社会媒体多模态、多层次资源推荐技术研究 ·275. systems by weighting multiple relations [C]//Machine International Conference on Knowledge Discovery and Data Learning and Knowledge Discovery in Databases-European Mining.San Diego,CA,USA,2011:753-756. Conference.Athens,Greece,2011:328-334. [40]CUI B,TUNG A,ZHANG C,et al.Multiple feature fu- [26]LIU L,XU H,XING J,et al."Wow!You are so beautiful sion for social media applications[C]//Proc ACM SIG- today!"[C]//ACM Multimedia,Barcelona,Spain,2013: MOD,Conference.Indianapolis,Indiana,USA,2010: 3-12. 435-446. [27]SUN Y,NORICK B,HAN J,et al.Integrating meta-path [41]SAXTON G,OH O,KISHORE R.Rules of crowdsourc- selection with user-guided object clustering in heterogene- ing:models,issues,and systems of control[].Informa- ous information networks[C//ACM SIGKDD Conference. tion Systems Management,2013,30(1):2-20. Beijing,China,2012:1348-1356. [42]RAWASHDEH M,KIM H,EL-SADDIK A.Social media 28]GUY I,JACOVI M,PERER A,et al.Same places,same annotation and tagging based on folksonomy link prediction things,same people?:Mining user similarity on social in a tripartite graph[C]//Advances in Multimedia Model- media C//ACM Conference on Computer Supported Co- ing.Huangshan,China,2013:24-35. operative Work.Savannah,Georgia,USA,2010:41-50. [43]LIU L,ZHU F,JIANG M,et al.Mining diversity on so- [29]BARBIER G,TANG L,LIU H.Understanding online cial media networks[J].Multimedia Tools and Applica- groups through social media[J].Wiley Interdisciplinary tion3,2012,56(1):179-205. Reviews:Data Mining and Knowledge Discovery,2011,I [44]LING L,ZHAI X,PENG Y.Tri-space and ranking based (4):330-338. heterogeneous similarity measure for cross-media retrieval [30]YANG C,YANG H,TANG X,et al.Identifying implicit [C]//International Conference on Pattern Recognition. relationships between social media users to support social Tsukuba,Japan,2012:230-233. commerce [C]//International Conference on Electronic [45]ZHAI X,PENG Y,XIAO J.Effective heterogeneous simi- Commerce.Singapore 2012:41-47. larity measure with nearest neighbors for cross-media re- [31]JORGE C,ALNEU L.Exploiting behaviors of communities trieval[C]//Advances in Multimedia Modeling.Klagen- of twitter users for link prediction[J].Social Network A- furt,Austria,2012:312-322. nalysis and Mining,2013,3(4):1063-1074. [46]JIA Y,SALZMANN M,DARRELL T.Learning cross-mo- [32]TANG J,WANG M,HUA X,et al.Social media mining dality similarity for multinomial data[C]//IEEE Interna- and search[J].Multimedia Tools and Applications,2012, tional Conference on Computer Vision.Barcelona,Spain, 56(1):1-7. 2011:2407-2414. [33]LEE C.Unsupervised and supervised learning to evaluate [47]WU F,LU X,ZHANG Z,et al.Cross-media semantic event relatedness based on content mining from social- representation via bi-directional learning to rank [C]/ media streams [J].Expert Systems with Applications, ACM Multimedia.Barcelona,Spain,2013:877-886 2012,39(18):13338-13356. [48]XIE L,SHAMMA D,SNOEK C.Content is dead:long- [34]JIN X,LIN C,LUO J,et al.SocialSpamGuard:A data live content!C ]//ACM Multimedia.Nara,Japan, mining-based spam detection system for social media net- 2012:7-8. works[J].Proceedings of the VLDB Endowment,2011,4 作者简介: (12):1458-1461. 王大玲,女,1962年生,教授,中国 [35]LEE C,CROFT W,KIM J.Evaluating search in personal 计算机学会高级会员,中国计算机学会 social media collections[C]//International Conference on 中文信息技术专业委员会委员,主要研 Web Search and Web Data Mining.Seattle,WA,USA, 究方向为数据挖掘、信息检索、Wb推 2012:683-692. 荐等,主持国家自然科学基金项目3 [36]CHOUDHURY M,COUNTS S,CZERWINSKI M.Find me 项,参与国家自然科学基金项目2项。 the right content!diversity-based sampling of social media spaces for topic-centric search[C]//International Confer- 冯时,男,1981年生,讲师,主要研 ence on Weblogs and Social Media.Barcelona,Catalonia, 究方向情感挖掘、网络舆情分析。 Spain 2011. [37]TSAI F.Probabilistic models for social media mining[J]. International Journal of Information Technology and Web Engineering,2011,6(1):13-24. [38]KASCHESKY M,SOBKOWICZ P,BOUCHARD G.Opin- 张一飞,女,1977年生,讲师,主要研 ion mining in social media:modeling,simulating,and vis- 究方向为图像处理、多媒体数据挖掘。 ualizing political opinion formation in the Web[C]//12th Annual International Conference on Digital Government Re- search.MD,USA,2011:317-326. [39 ]JIN X,WANG C.LUO J,et al.LikeMiner:a system for mining the power of'like'in social media networks[C]/systems by weighting multiple relations [ C ] / / Machine Learning and Knowledge Discovery in Databases⁃ European Conference. Athens, Greece, 2011: 328⁃334. [26]LIU L, XU H, XING J, et al. " Wow! You are so beautiful today!" [C] / / ACM Multimedia, Barcelona, Spain, 2013: 3⁃12. [27]SUN Y, NORICK B, HAN J, et al. Integrating meta⁃path selection with user⁃guided object clustering in heterogene⁃ ous information networks[C] / / ACM SIGKDD Conference. Beijing, China, 2012: 1348⁃1356. [28]GUY I, JACOVI M, PERER A, et al. Same places, same things, same people?: Mining user similarity on social media[C] / / ACM Conference on Computer Supported Co⁃ operative Work. Savannah, Georgia, USA, 2010: 41⁃50. [29] BARBIER G, TANG L, LIU H. Understanding online groups through social media [ J]. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 2011, 1 (4): 330⁃338. [30]YANG C, YANG H, TANG X, et al. Identifying implicit relationships between social media users to support social commerce [ C ] / / International Conference on Electronic Commerce. Singapore 2012: 41⁃47. [31]JORGE C, ALNEU L. Exploiting behaviors of communities of twitter users for link prediction[ J]. Social Network A⁃ nalysis and Mining, 2013, 3(4): 1063⁃1074. [32]TANG J, WANG M, HUA X, et al. Social media mining and search[J]. Multimedia Tools and Applications, 2012, 56(1): 1⁃7. [33]LEE C. Unsupervised and supervised learning to evaluate event relatedness based on content mining from social⁃ media streams [ J ]. Expert Systems with Applications, 2012, 39(18): 13338⁃13356. [34]JIN X, LIN C, LUO J, et al. SocialSpamGuard: A data mining⁃based spam detection system for social media net⁃ works[J]. Proceedings of the VLDB Endowment, 2011, 4 (12): 1458⁃1461. [35]LEE C, CROFT W, KIM J. Evaluating search in personal social media collections[ C] / / International Conference on Web Search and Web Data Mining. Seattle, WA, USA, 2012: 683⁃692. [36]CHOUDHURY M, COUNTS S, CZERWINSKI M. Find me the right content! diversity⁃based sampling of social media spaces for topic⁃centric search[C] / / International Confer⁃ ence on Weblogs and Social Media. Barcelona, Catalonia, Spain 2011. [37]TSAI F. Probabilistic models for social media mining[ J]. International Journal of Information Technology and Web Engineering, 2011, 6(1): 13⁃24. [38]KASCHESKY M, SOBKOWICZ P, BOUCHARD G. Opin⁃ ion mining in social media: modeling, simulating, and vis⁃ ualizing political opinion formation in the Web[C] / / 12th Annual International Conference on Digital Government Re⁃ search. MD, USA, 2011: 317⁃326. [39]JIN X, WANG C, LUO J, et al. LikeMiner: a system for mining the power of ‘like’ in social media networks[C] / / International Conference on Knowledge Discovery and Data Mining. San Diego, CA, USA, 2011: 753⁃756. [40]CUI B, TUNG A, ZHANG C, et al. Multiple feature fu⁃ sion for social media applications [ C] / / Proc ACM SIG⁃ MOD, Conference. Indianapolis, Indiana, USA, 2010: 435⁃446. [41] SAXTON G, OH O, KISHORE R. Rules of crowdsourc⁃ ing: models, issues, and systems of control[ J]. Informa⁃ tion Systems Management, 2013, 30(1): 2⁃20. [42]RAWASHDEH M, KIM H, EL⁃SADDIK A. Social media annotation and tagging based on folksonomy link prediction in a tripartite graph[C] / / Advances in Multimedia Model⁃ ing. Huangshan, China, 2013: 24⁃35. [43]LIU L, ZHU F, JIANG M, et al. Mining diversity on so⁃ cial media networks [ J]. Multimedia Tools and Applica⁃ tions, 2012, 56(1): 179⁃205. [44]LING L, ZHAI X, PENG Y. Tri⁃space and ranking based heterogeneous similarity measure for cross⁃media retrieval [ C ] / / International Conference on Pattern Recognition. Tsukuba, Japan, 2012: 230⁃233. [45]ZHAI X, PENG Y, XIAO J. Effective heterogeneous simi⁃ larity measure with nearest neighbors for cross⁃media re⁃ trieval [ C] / / Advances in Multimedia Modeling. Klagen⁃ furt, Austria, 2012: 312⁃322. [46]JIA Y, SALZMANN M, DARRELL T. Learning cross⁃mo⁃ dality similarity for multinomial data[ C] / / IEEE Interna⁃ tional Conference on Computer Vision. Barcelona, Spain, 2011: 2407⁃2414. [47] WU F, LU X, ZHANG Z, et al. Cross⁃media semantic representation via bi⁃directional learning to rank [ C] / / ACM Multimedia. Barcelona, Spain, 2013: 877⁃886 [48] XIE L, SHAMMA D, SNOEK C. Content is dead: long⁃ live content! [ C ] / / ACM Multimedia. Nara, Japan, 2012: 7⁃8. 作者简介: 王大玲,女,1962 年生,教授,中国 计算机学会高级会员,中国计算机学会 中文信息技术专业委员会委员,主要研 究方向为数据挖掘、信息检索、Web 推 荐等,主持国家自然科学基金项目 3 项,参与国家自然科学基金项目 2 项。 冯时,男,1981 年生,讲师,主要研 究方向情感挖掘、网络舆情分析。 张一飞,女,1977 年生,讲师,主要研 究方向为图像处理、多媒体数据挖掘。 第 3 期 王大玲,等:社会媒体多模态、多层次资源推荐技术研究 ·275·
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