QueryShare: QueryShare. Query-by-Example [5][6] [7][8][9] QueryShare [10][11] [12] CGM Consumer Generated Media [13] 0.2. QueryShare.

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Transcription:

QueryShare: 1,a) 1,b) QueryShare 1. [1][2] [3][4] Query-by-Example [5][6] [7][8][9] [10][11] [12] CGM Consumer Generated Media [13] 1 AIST, 1-1-1 Umezono, Tsukuba, Ibaraki 305-8568, Japan a) masahiro.hamasaki at aist.go.jp b) m.goto at aist.go.jp QueryShare QueryShare 7 10 0.2 0.4 0.6 c 2014 Information Processing Society of Japan 1

2 3 4 5 6 2. QueryShare: QueryShare QueryShare 1-(b) QueryShare QueryShare 1 [14][15] [16] [17] 1-a QueryShare 1-b QueryShare Web 2.1 QueryShare 2 QueryShare Web Wiki Web c 2014 Information Processing Society of Japan 2

2 Wiki QueryShare 2.2 QueryShare QueryShare CGM 3. QueryShare QueryShare QueryShare QueryShare 3.1 QueryShare 3.1.1 2.1 Semantic Gap QueryShare c 2014 Information Processing Society of Japan 3

3.1.2 3.1.3 Query by Example Query by Example 3.2 QueryShare 3.2.1 3.2.2 4. 4.1 1 2 ID ID ID ID ID ID / *1 YouTube *2 65 100 200 100 VOCALOID 363,518 64,774 13,138 3,514 1 2 4.2 3 *1 http://www.nicovideo.jp *2 http://youtube.com c 2014 Information Processing Society of Japan 4

1 SQL WHERE SQL ORDER BY SQL GROUP BY Web Web 1 2 AND ID 1 2 4.3 2 3 4.4 3 QueryShare 4.4.1 QueryShare 3 AND 4.4.2 QueryShare c 2014 Information Processing Society of Japan 5

4 Songrium 4.5 QueryShare Web Web QueryShare QueryShare QueryShare QueryShare Songrium [18][19] Songle [20][21] Songrium 4 5. QueryShare Folkquery 5.1 [16] [22] [23][24] [16] [25] QueryShare QueryShare QueryShare Yahoo! Pipes *3 SQL SPARQL GUI [26][27] Yahoo! Pipes GUI Yahoo! Pipes QueryShare 5.2 Folk + Query = Folkquery (Folksonomy) [28] [29] QueryShare *3 http://pipes.yahoo.com/pipes/ c 2014 Information Processing Society of Japan 6

(Folk+Query=Folkquery) 5.3 [30] QueryShare QueryShare 2 E 1 1 0.8 1 0.8 QueryShare 5.4 vs (1) (2) 6. QueryShare QueryShare QueryShare QueryShare QueryShare c 2014 Information Processing Society of Japan 7

QueryShare Linked Open Data QueryShare JST CREST OngaCREST [1] Ghias, A., Logan, J., Chamberlin, D. and Smith, B. C.: Query by humming: musical information retrieval in an audio database, Proc. ACM Multimedia 95, pp. 231 236 (1995). [2] che Wang, C., shing Roger, J. and Wang, J. W.: An Improved Query by Singing/Humming System Using Melody and Lyrics Information, Proc. ISMIR 2010, pp. 45 50 (2010). [3] Kashino, K., Kurozumi, T. and Murase, H.: A quick search method for audio and video signals based on histogram pruning, IEEE Trans. on Multimedia, Vol. 5, No. 3, pp. 348 357 (2003). [4] Chandrasekhar, V., Sharifi, M. and Ross, D. A.: Survey and Evaluation of Audio Fingerprinting Schemes for Mobile Query-by-Example Applications, Proc. ISMIR 2011, pp. 801 806 (2011). [5] Tsai, W. H., Yu, H. M. and Wang, H. M.: A Queryby-Example Technique for Retrieving Cover Versions of Popular Songs with Similar Melodies, Proc. ISMIR 2005, pp. 183 190 (2005). [6] Itoyama, K., Goto, M., Komatani, K., Ogata, T. and Okuno, H. G.: Instrument Equalizer for Query-by- Example Retrieval: Improving Sound Source Separation Based on Integrated Harmonic and Inharmonic Models, Proc. ISMIR 2008, pp. 133 138 (2008). [7] Pardo, B.(ed.): Special issue: Music information retrieval, Communications of the ACM, Vol. 49, No. 8, pp. 28 58, ACM (2006). [8] Song, Y., Dixon, S. and Pearce, M.: Survey of Music Recommendation Systems and Future Perspectives, Proc. CMMR 2012, pp. 395 410 (2012). [9] Knees, P. and Schedl, M.: A Survey of Music Similarity and Recommendation from Music Context Data, ACM Trans. on Multimedia Computing, Communications and Applications, Vol. 10, No. 1, pp. 1 21 (2013). [10] Pampalk, E., Rauber, A. and Merkl, D.: Content-based Organization and Visualization of Music Archives, Proc. ACM Multimedia 2002, pp. 570 579 (2002). [11] Goto, M. and Goto, T.: Musicream: Integrated Music- Listening Interface for Active, Flexible, and Unexpected Encounters with Musical Pieces, IPSJ Journal ( ) Vol. 50, No. 12, pp. 2923 2936 (2009). [12] Marchionini, G.: Exploratory search: from finding to understanding, Communications of the ACM, Vol. 49, No. 4, pp. 41 46, ACM (2006). [13] CGM ( ) Vol. 53, No. 5, pp. 466 471 (2012). [14] Cucerzan, S. and Brill, E.: Spelling correction as an iterative process that exploits the collective knowledge of web users, Proc. EMNLP 2004, pp. 293 300 (2004). [15] Li, M., Zhu, M., Zhang, Y. and Zhou, M.: Exploring Distributional Similarity Based Models for Query Spelling Correction, Proc. ACL 2006, pp. 1025 1032 (2006). [16] Cui, H., Wen, J.-R., Nie, J.-Y. and Ma, W.-Y.: Probabilistic query expansion using query logs, Proc. WWW 2002, pp. 325 332 (2002). [17] Rui, Y., Huang, T. S., Ortega, M. and Mehrotra, S.: Relevance feedback: a power tool for interactive contentbased image retrieval, IEEE Trans. on Circuits and Systems for Video Technology, Vol. 8, pp. 644 655 (1998). [18] Songrium: WISS2012 (2012). [19] Hamasaki, M., Goto, M. and Nakano, T.: Songrium: A Music Browsing Assistance Service with Interactive Visualization and Exploration of a Web of Music, Proc. WWW 2014, pp. 523 528 (2014). [20] Goto, M., Yoshii, K., Fujihara, H., Mauch, M. and Nakano, T.: Songle: A Web Service for Active Music Listening Improved by User Contributions, Proc. ISMIR 2011, pp. 311 316 (2011). [21] Mauch, M. Songle: Vol. 54, No. 4, pp. 1363 1372 (2013). [22] Anick, P.: Using terminological feedback for web search refinement: a log-based study, Proc. SIGIR 2003, pp. 88 95 (2003). [23] Voorhees, E. M.: Query expansion using lexical-semantic relations, Proc. SIGIR 94, pp. 61 69 (1994). [24] Mahdabi, P., Gerani, S., Huang, J. X. and Crestani, F.: Leveraging conceptual lexicon: query disambiguation using proximity information for patent retrieval, Proc. IS- MIR 2013, pp. 113 122 (2013). [25] Parikh, N. and Sundaresan, N.: Inferring semantic query relations from collective user behavior, Proc. CIKM 2008, pp. 349 358 (2008). [26] Le-Phuoc, D., Polleres, A., Hauswirth, M., Tummarello, G. and Morbidoni, C.: Rapid prototyping of semantic mash-ups through semantic web pipes, Proc. WWW 2009), pp. 581 590 (2009). [27] Jarrar, M. and Dikaiakos, M. D.: A Query Formulation Language for the Data Web, IEEE Trans. on Knowledge and Data Engineering, Vol. 24, No. 5, pp. 783 798 (2012). [28] Weinberger, D.: (2008). [29] Pariser, E.: (2012). [30] Vol. 2013-MUS-99, No. 33, pp. 1 9 (2013). c 2014 Information Processing Society of Japan 8