PUMA
Istituto di Scienza e Tecnologie dell'Informazione     
Gennaro C., Mordacchini M., Orlando S., Rabitti F. A scalable distributed data structure for multi-feature similarity search. In: SEBD 2008 - Sixteenth Italian Symposium on Advanced Database Systems (Mondello (PA), 22-25 June 2008). Atti, pp. 302 - 309. Salvatore Gaglio, Ignazio Infantino, Domenico Sacc (eds.). Fotograf, (Palermo), 2008.
 
 
Abstract
(English)
Similarity search for content-based retrieval (where content can be any combination of text, image, audio/video, etc.) has gained importance in recent years, also because of the advantage of ranking the retrieved results according to their proximity to a query. However, to use similarity search in real world applications, we need to tackle the problem of huge volumes of such mixed multimedia data (e.g., coming from Web sites) and the problem of their distribution on multiple cooperating nodes. The proposed approach is being used in two running projects: SAPIR and NeP4B. In this paper we approach this problem by considering a scenario of a network of autonomous peers maintaining a local collection of metric objects (i.e., mixed mode multimedia content). This network forms a distributed Peer--to--Peer (P2P) search engine for similarity search based on the paradigm of Routing Index. Each peer in the network thus maintains both an index of its local resources and a table for every neighbor, summarizing the objects that are reachable from it. The paper presents techniques that aim to make our P2P similarity-based search system viable, trading approximate results for scalable solutions. Results of simulations that use real collections of images are discussed.
Subject Peer-to-Peer
Routing Index
Content based search
Similarity Search
E.1 Data Structures
H.3.3 Information Search and Retrieval


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