=Paper= {{Paper |id=Vol-355/paper-1 |storemode=property |title=Multimedia Information Retrieval |pdfUrl=https://ceur-ws.org/Vol-355/manolo.pdf |volume=Vol-355 |dblpUrl=https://dblp.org/rec/conf/syrcodis/Manolopoulos08 }} ==Multimedia Information Retrieval== https://ceur-ws.org/Vol-355/manolo.pdf 
           Multimedia Information Retrieval (An Introduction)

                            c Apostolos Papadopoulos                Yannis Manolopoulos
                       Department of Informatics, Aristotle University, 54124 Thessaloniki, Greece



1     Abstract                                                1.1   Basic Bibliography
Information Retrieval (IR) is an active research area for       1. R. Baeza-Yates and B. Ribeiro-Neto. ”Modern In-
many years. Initially, the field focused on the efficient          formation Retrieval”, Addison Wesley, 1999.
and effective processing of user information needs ex-
pressed as a set of keywords. In fact, this model is still      2. S. Berchtold, D.A. Keim, and H.-P. Kriegel. ”The
active today (e.g., web search engines). However, large            X-tree: An Index Structure for High Dimensional
volumes of information are available in non-textual form,          Data”, VLDB Conference, 1996.
such as images, audio files and videos. The research field      3. C. Faloutsos: ”Searching Multimedia Databases by
of Multimedia Information Retrieval (MIR) deals with               Content”, Kluwer Academic Publishers, 1996.
the efficient and effective processing of queries involv-
ing multimedia objects. The big challenge here is to pro-       4. B. Furht (Ed): ”Handbook of Multimedia Comput-
vide ”retrieval by content”, which means that we do not            ing”, CRC Press, 1999.
just want to provide results based on metadata or textual
descriptions of the objects, but based on the content of        5. A. Guttman: ”R-tree: A Dynamic Index Struc-
these objects. In this talk, we perform a gentle introduc-         ture for Spatial Searching”, ACM SIGMOD Con-
tion to the field, starting from stabilized methods used           ference, 1984.
in text-based retrieval, and then moving on to the fun-         6. O. Marques and B. Furht: ”Content-Based Image
damentals and challenges of multimedia-based retrieval.            and Video Retrieval”, Kluwer Academic Publishers,
We discuss the representation of multimedia objects as             2002.
vectors in a multi-dimensional space, the organization of
these representations by means of indexing schemes and          7. N. Roussopoulos, S. Kelly, and F. Vincent: ”Nearest
the retrieval of similar objects based on user queries.            Neighbor Queries”, ACM SIGMOD Conference,
   The outline of the talk is as follows:                          1995.

    • text representation                                       8. R.C. Veltkamp, M. Tanase: ”Content-Based Image
                                                                   Retrieval Systems: A Survey”, 2000
    • information retrieval vs data retrieval

    • components of an IR system

    • indexing text databases

    • boolean and vector-based retrieval

    • efficiency and effectiveness

    • similarity queries

    • feature extraction (images, audio, video)

    • indexing multimedia objects (R-trees and X-trees)

    • index-based processing

    • current trends

    • conclusions

    • bibliography

Proceedings of the Spring Young Researcher’s Colloquium
on Database and Information Systems, Saint-Petersburg, Rus-
sia, 2008