CHORUS Deliverable 2.1: State of the Art on Multimedia Search Engines

Based on the information provided by European projects and national initiatives related to multimedia search as well as domains experts that participated in the CHORUS Think-thanks and workshops, this document reports on the state of the art related to multimedia content search from, a technical, and socio-economic perspective. The technical perspective includes an up to date view on content based indexing and retrieval technologies, multimedia search in the context of mobile devices and peer-to-peer networks, and an overview of current evaluation and benchmark inititiatives to measure the performance of multimedia search engines. From a socio-economic perspective we inventorize the impact and legal consequences of these technical advances and point out future directions of research

The Signal Data Explorer: A high performance Grid based signal search tool for use in distributed diagnostic applications

We describe a high performance Grid based signal search tool for distributed diagnostic applications developed in conjunction with Rolls-Royce plc for civil aero engine condition monitoring applications. With the introduction of advanced monitoring technology into engineering systems, healthcare, etc., the associated diagnostic processes are increasingly required to handle and consider vast amounts of data. An exemplar of such a diagnosis process was developed during the DAME project, which built a proof of concept demonstrator to assist in the enhanced diagnosis and prognosis of aero-engine conditions. In particular it has shown the utility of an interactive viewing and high performance distributed search tool (the Signal Data Explorer) in the aero-engine diagnostic process. The viewing and search techniques are equally applicable to other domains. The Signal Data Explorer and search services have been demonstrated on the Worldwide Universities Network to search distributed databases of electrocardiograph data

Global-Scale Resource Survey and Performance Monitoring of Public OGC Web Map Services

One of the most widely-implemented service standards provided by the Open Geospatial Consortium (OGC) to the user community is the Web Map Service (WMS). WMS is widely employed globally, but there is limited knowledge of the global distribution, adoption status or the service quality of these online WMS resources. To fill this void, we investigated global WMSs resources and performed distributed performance monitoring of these services. This paper explicates a distributed monitoring framework that was used to monitor 46,296 WMSs continuously for over one year and a crawling method to discover these WMSs. We analyzed server locations, provider types, themes, the spatiotemporal coverage of map layers and the service versions for 41,703 valid WMSs. Furthermore, we appraised the stability and performance of basic operations for 1210 selected WMSs (i.e., GetCapabilities and GetMap). We discuss the major reasons for request errors and performance issues, as well as the relationship between service response times and the spatiotemporal distribution of client monitoring sites. This paper will help service providers, end users and developers of standards to grasp the status of global WMS resources, as well as to understand the adoption status of OGC standards. The conclusions drawn in this paper can benefit geospatial resource discovery, service performance evaluation and guide service performance improvements.Comment: 24 pages; 15 figure

A Density-Based Approach to the Retrieval of Top-K Spatial Textual Clusters

Keyword-based web queries with local intent retrieve web content that is relevant to supplied keywords and that represent points of interest that are near the query location. Two broad categories of such queries exist. The first encompasses queries that retrieve single spatial web objects that each satisfy the query arguments. Most proposals belong to this category. The second category, to which this paper's proposal belongs, encompasses queries that support exploratory user behavior and retrieve sets of objects that represent regions of space that may be of interest to the user. Specifically, the paper proposes a new type of query, namely the top-k spatial textual clusters (k-STC) query that returns the top-k clusters that (i) are located the closest to a given query location, (ii) contain the most relevant objects with regard to given query keywords, and (iii) have an object density that exceeds a given threshold. To compute this query, we propose a basic algorithm that relies on on-line density-based clustering and exploits an early stop condition. To improve the response time, we design an advanced approach that includes three techniques: (i) an object skipping rule, (ii) spatially gridded posting lists, and (iii) a fast range query algorithm. An empirical study on real data demonstrates that the paper's proposals offer scalability and are capable of excellent performance