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Merging image databases as an example for information integration. (English) Zbl 1339.68075
Summary: By integrating information we mean pulling information pieces from various sources together with as little loss of information and as little redundancy as possible. Operation Research techniques applied in many situations, like heuristic algorithms, meta-heuristics, similarity measures, use of constraints, combinatorial algorithms and collaborative efforts provide valuable tools for this process, if augmented by other techniques known from knowledge management and information retrieval. Given the huge amount of information we are confronted with, information integration is one of the biggest challenges of this century. This paper describes methods and techniques for the information integration process. It is interesting to note that in areas such as information integration, consolidation and simplification that are not usually at the heart of Operation Research, some of the most important techniques used in this field can be applied successfully. Information integration is an important topic but, in general no really convincing approaches have been discovered, so far. By limiting the domain to the integration of image databases the problem becomes tractable, by using the mentioned techniques and also applying methods ranging from image processing, knowledge management and natural language processing to feature engineering.

MSC:
68P20 Information storage and retrieval of data
68T20 Problem solving in the context of artificial intelligence (heuristics, search strategies, etc.)
68T50 Natural language processing
68U10 Computing methodologies for image processing
90C59 Approximation methods and heuristics in mathematical programming
Software:
SSE; WHIRL; XPath
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References:
[1] Afzal, MT; Balke, WT; Kulathuramaiyer, N; Maurer, H, Rule based autonomous citation mining with TIERL, JDIM, 8, 196-204, (2010)
[2] Austria-Forum (2014) http://Austria-forum.org/. Accessed 20 Aug 2014
[3] Bikel, DM; Schwartz, R; Weischedel, RM, An algorithm that learns what’s in a name, Mach Learn, 34, 211-231, (1999) · Zbl 0917.68172
[4] Blazsik, Z; Imre, C; Kovcs, Z, Heuristic algorithms for a complex parallel machine scheduling problem, CJOR, 16, 379-390, (2008) · Zbl 1162.90445
[5] Carlson A, Betteridge J, Wang RC, Hruschka ER Jr, Mitchell T (2010) Coupled semi-supervised learning for information extraction. In: Proceedings of the third ACM international conference on web search and data mining, pp 101-110. doi:10.1145/1718487.1718501
[6] Cohen, W, Whirl a word-based information representation language, Artical Intell, 118, 163-196, (2000) · Zbl 0938.68841
[7] Debnath S, Mitra P, Giles CL (2005) Automatic extraction of informative blocks from webpages. 20th annual ACM symposium on applied computing. doi:10.1145/1066677.1067065 · Zbl 1339.90216
[8] Denish (2008) Table drag and drop JQuery plugin. http://isocra.com/2008/02/table-drag-and-drop-jquery-plugin/. Accessed 20 Aug 2014
[9] Deutsche National Bibliothek (2014) Common Authority File (GND). http://www.dnb.de/DE/Standardisierung/GND/gnd_node.html. Accessed 20 Aug 2014
[10] Deutsche National Bibliothek (2014). http://d-nb.info/gnd/118601121/about/html. Accessed 20 Aug 2014 · Zbl 0938.68841
[11] Furian, N; Vössner, S, Constrained order packing:comparison of heuristic approaches for a new bin packing problem, CJOR, 21, 237-264, (2013) · Zbl 1339.90280
[12] Genesereth M, keller A, Duschka O (1997) Infomaster: an information integration system. ACM SIGMOD international conference on management of data, Tucson. doi:10.1145/253262.253400 · Zbl 1339.90216
[13] Grossman DA, Frieder O (2004) Information retrieval: algorithms and heuristics, 2nd edn. Springer, Berlin · Zbl 1066.68041
[14] Imagno (2014). http://www.imagno.at. Accessed 20 Aug 2014
[15] Kaklauskas, L; Sakalauskas, L, Study of on-line measurement of traffic self-similarity, CJOR, 21, 63-84, (2013) · Zbl 1339.90216
[16] Kappe, F; Maurer, H; Zaka, B, Plagiarism—A survey, J Univers Comput Sci, 12, 1050-1084, (2006)
[17] Kirk T, Levy AY, Sagiv Y, Srivastava D (1995) The information manifold. In: Proceedings of the AAAI on information gathering from heterogeneous, distributed environments. doi:10.1.1.32.1651
[18] Korica P, Maurer H (2012) Semi-automatic information retrieval and consolidation with a sample application. In: Proceedings of international conference on emerging technologies (ICET). doi:10.1109/ICET.2012.6375491
[19] Latif A, Afzal MT, Saeed AU, Hoefler P, Tochtermann K (2009) CAF-SIAL: concept aggregation framework for structuring informational aspects of linked open data. In: Proceedings of NDT. doi:10.1109/NDT.2009.5272079 · Zbl 1339.90280
[20] Liu, Y; Wang, Q, A heuristic approach for topical information extraction from news pages, Lect Notes Comput Sci, 4255, 357-362, (2006)
[21] Manning CD, Raghavan P (2009) Introduction to information retrieval. Cambridge University Press, New York · Zbl 1339.90342
[22] Maurer H, Scherbakov N (1998) Mulitmeida authroing for presentation and education. Addison-Wesely, Boston
[23] Maurer, H; Tochtermann, K, On a new powerful model for knowledge-management and its applications, JUCS, 8, 85-96, (2002)
[24] McCann R, Kramnik A, Warren S, Varadarajan V, Sobulo O, Doan A (2005) Integrating data from disparate sources: a mass collaboration approach. In: ICDE proceedings. doi:10.1109/ICDE.2005.81
[25] Mes, M; Heijden, M; Schur, P, Interaction between intelligent agent strategies for real-time transportation planning, CJOR, 21, 337-358, (2013) · Zbl 1397.91267
[26] Nakapan, W; Halin, G; Bignon, J-C; Wagner, M; Humbert, P, Extraction of building product image from the web, Int J Intell Syst, 19, 65-78, (2003)
[27] Nigam K (2006) Text Information extraction, autumn school machine learning over text and images. http://videolectures.net/mlas06_nigam_tie/. Accessed 20 Aug 2014
[28] Saracevic T (1986) Processes and problems in information consolidation. Information processing and management, vol 22, 1st edn. Pergamon Press, Tarrytown, NY, pp 45-60
[29] Swiercz, A; Burke, EK; Cichenski, M; Pawlak, G; Petrovic, S; Zurkowski, T; Blazewicz, J, Unified encoding for hyper heuristics with application to bioinformatics, CJOR, 22, 567-589, (2014) · Zbl 1339.90342
[30] Wurzinger, G, Information consolidation in large bodies of information, J Univers Comput Sci, 16, 3314-3323, (2010) · Zbl 1213.68660
[31] Zelenko, D; Aone, C; Richardella, A; Hofmann, T; Poggio, T; Shawe-Taylor, J, Kernel methods for relation extraction, J Mach Learn Res, 3, 1083-1106, (2003) · Zbl 1061.68565
[32] Zijing T (2008) Answering xpath queries in virtual xml data integration system. In: Proceedings of the international conference on computer science and software engineering. doi:10.1109/CSSE.2008.579
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