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References [1] Aguilar-Melchor, C., Barrier, J., Fousse, L., Killijian, M.O.: XPIR: Private Information Retrieval for Everyone. Proceedings on Privacy Enhancing Technologies 2016(2), 155-174 (2016) [2] Aguilar Melchor, C., Gaborit, P.: A Lattice-Based Computationally-Efficient Private Information Retrieval Protocol. In: Western European Workshop on Research in Cryptology (2007) [3] Andres, M.E., Bordenabe, N.E., Chatzikokolakis, K., Palamidessi, C.: Geo-indistinguishability: differential privacy for location-based systems. In: Proceedings of the 2013 ACM SIGSAC

Anwendung und Entwicklung komplexer Verfahren in Information-Retrieval-Systemen und ihre Evaluierung

it 4/2011 Distinguished Dissertations An Approach to XML Information Retrieval in Distributed Systems Ein Ansatz für Verteiltes XML Information Retrieval Judith Winter, University of Applied Sciences, Frankfurt, Germany Summary Modern search engines are quite successful in finding relevant documents by using Information Retrieval tech- niques. However, the centralized architecture of systems such as Google raises concerns in regard of the possibility to cen- sure and to manipulate information. Promising alternatives are peer-to-peer search engines that organize

1 Introduction Industrial clusters refer to the collection of enterprises and related corporate bodies with geographical proximity, interrelated, and linked by virtue of mutual commonality and complementarity in a specific field [ 1 ]. The main components of industrial clusters include enterprises, governments, university research institutes, financial institutions, industry associations and intermediary institutions. At present, the relevant platforms provide a variety of information retrieval services for the spatial database of industrial clusters, including

INFORMATION RETRIEVAL 1. Shera, J. H., A. Kent, and J. W. Perry: Information Systems in Documentation, Interscience, 1957, 659 pp. ** 2. ------: Bibliography on Filing, Classification and Indexing Systems for Engineering Offices and Libraries, Engin- eering Societies Library, 1960. ** 3. Fisher, E. L.: A Checklist for the Organization, Operation and Evaluation of a Company Library, Special Libraries Assoc., 1960, 60 pp. 4. Kent, A. (editor): Information Retrieval and Machine Trans- lation, Interscience, 1960. 5. Bar-Hillel, Y. : Some Theoretical Aspects

References [1] R. Sion and B. Carbunar, “On the Computational Practicality of Private Information Retrieval,” in 14th ISOC Network and Distributed Systems Security Symposium (NDSS’07), San Diego, CA, USA, 2007. [2] B. Chor, O. Goldreich, E. Kushilevitz, and M. Sudan, “Private Information Retrieval,” in 46th IEEE Symposium on Foundations of Computer Science (FOCS’95), Pittsburgh, PA, USA, pp. 41-50, IEEE Computer Society Press, 1995. [3] W. Gasarch, “A Survey on Private Information Retrieval,” Bulletin of the European Association for Theoretical Computer Science

References 1. Ahmad, I. S. Text-Based Image Indexing and Retrieval using Formal Concept Analysis. - KSII Transactions on Internet and Information Systems, Vol. 2, 2008, No 3, 150-170. 2. Kumar, A. C., S. Srinivas. Latent Semantic Indexing Using Eigen Value Analysis for Efficient Information Retrieval. - International Journal of Applied Mathematics and Computer Science, Vol. 16, 2006, No 4, 551-558. 3. Kumar, A. C., S. Srinivas. Concept Lattice Reduction Using Fuzzy k Means Clustering. - Expert Systems with Applications, Vol. 37, 2010, No 3, 2696-2704. 4. Kumar, A

References 1. Berry, M., M. Browne. Understanding Search Engines: Mathematical Modeling and Text Retrieval. Society for Industrial and Applied Mathematics, 2005. 2. Brusilovsky, P., C. Tasso. Preface to Special Issue on User Modeling for Web Information Retrieval. – User Modeling and User-Adapted Interaction, Vol. 14 , 2004, No 2-3, pp. 147-157. 3. Cummins, R., C. O’Riordan. Evolving Local and Global Weighting Schemes in Information Retrieval. – Information Retrieval, Vol. 9 , 2006, No 3, pp. 311-330. 4. Dobrov, B., I. Kuralenok, N. Loukachevitch, I