5985654
Design and Implementation of a Geographic Search Engine
In this paper, we describe the design and initial implementation of a geographic search engine prototype for Germany, based on a large crawl of the de domain. Geographic search engines provide a flexible interface to the Web that allows users to constrain and order search results in an intuitive manner, by focusing a query on a particular geographic region. Geographic search technology has recently received significant commercial interest, but there has bee n only a limited amount of academic work. Our prototype performs massive extraction of geographic features from crawled data, which are then mapped to coordinates and aggregated across link and site structure. This assigns to each web page a set of relevant locations, called the geographic footprint of the page. The resulting footprint d ata is then integrated into a high-performance query processor on a cluster-based architecture. We discuss the various techniques, both new and existing, that are used for recognizing, matching, mapping, and aggregating geographic features, and describe how to integrate geographic query processing into a standard search architecture and interface.
1548803
I/O-efficient techniques for computing pagerank
Over the last few years, most major search engines have integrated link-based ranking techniques in order to provide more accurate search results. One widely known approach is the Pagerank technique, which forms the basis of the Google ranking scheme, and which assigns a global importance measure to each page based on the importance of other pages pointing to it. The main advantage of the Pagerank measure is that it is independent of the query posed by a user; this means that it can be precomputed and then used to optimize the layout of the inverted index structure accordingly. However, computing the Pagerank measure requires implementing an iterative process on a massive graph corresponding to billions of web pages and hyperlinks.In this paper, we study I/O-efficient techniques to perform this iterative computation. We derive two algorithms for Pagerank based on techniques proposed for out-of-core graph algorithms, and compare them to two existing algorithms proposed by Haveliwala. We also consider the implementation of a recently proposed topic-sensitive version of Pagerank. Our experimental results show that for very large data sets, significant improvements over previous results can be achieved on machines with moderate amounts of memory. On the other hand, at most minor improvements are possible on data sets that are only moderately larger than memory, which is the case in many practical scenarios.
1099710
Local methods for estimating pagerank values
The Google search engine uses a method called PageRank, together with term-based and other ranking techniques, to order search results returned to the user. PageRank uses link analysis to assign a global importance score to each web page. The PageRank scores of all the pages are usually determined off-line in a large-scale computation on the entire hyperlink graph of the web, and several recent studies have focused on improving the efficiency of this computation, which may require multiple hours on a workstation.
 However, in some scenarios, such as online analysis of link evolution and mining of large web archives such as the Internet Archive, it may be desirable to quickly approximate or update the PageRanks of individual nodes without performing a large-scale computation on the entire graph. We address this problem by studying several methods for efficiently estimating the PageRank score of a particular web page using only a small subgraph of the entire web. In our model, we assume that the graph is accessible remotely via a link database (such as the AltaVista Connectivity Server) or is stored in a relational database that performs lookups on disks to retrieve node and connectivity information. We show that a reasonable estimate of the PageRank value of a node is possible in most cases by retrieving only a moderate number of nodes in the local neighborhood of the node.
14712495
One-class SVM for learning in image retrieval
Relevance feedback schemes using linear/quadratic estimators have been applied in content-based image retrieval to improve retrieval performance significantly. One major difficulty in relevance feedback is to estimate the support of target images in high dimensional feature space with a relatively small number of training samples. We develop a novel scheme based on one-class SVM, which fits a tight hyper-sphere in the nonlinearly transformed feature space to include most of the target images based on positive examples. The use of a kernel provides us an elegant way to deal with nonlinearity in the distribution of the target images, while the regularization term in SVM provides good generalization ability. To validate the efficacy of the proposed approach, we test it on both synthesized data and real-world images. Promising results are achieved in both cases.
2306448
The TheaterLoc Virtual Application
Although much has been written about various information integration technologies, little has been said regarding how to combine these technologies together to build an entire “virtual” application. In this paper, we describe the design and implementation of TheaterLoc, an information integration application that allows users to retrieve information about theaters and restaurants for a variety of cities in the United States, including an interactive map depicting their relative locations and video trailers of the movies playing at the selected theaters. The data retrieved by TheaterLoc comes from five distinct heterogeneous and distributed sources. The enabling technology used to achieve the integration includes the Ariadne information mediator and wrappers for each of the web-based data sources. We focus in detail on the mediator technologies, such as data modeling, source axiom compilation, and query planning. We also describe how the wrappers present an interface for querying data on web sites, aiding in information retrieval used during data integration. Finally, we discuss some of the major integration challenges we encountered and our plans to address them.
308087
RTSOA: Real-Time Service-Oriented Architecture
This paper extends the traditional service-oriented architecture (SOA) to a new real-time SOA (RTSOA) and proposes a framework for the new architecture, by providing real-time service modeling, design, code generation, simulation, deployment, execution, orchestration, and management. The concepts, architecture, and enabling technique are studied for real-time SOA. In addition, an efficient algorithm is derived in the paper to find the optimal composition of real-time services subject to the real-time constraint
207108480
Weakest Specifunctions for BSP
This paper introduces a calculus of weakest specification for supporting reuse of established components in deriving a design (in the sense of formal methods). The weakest specifunction generalizes the notions of weakest pre-specification and weakest parallel environment; but instead of calculating the weakest required component of a target specification, it calculates the weakest specification function whose value refines the target when applied to an established component. In particular it overcomes the restriction of those other calculi to taking merely one required component at a time. The theory of specifunctions is applied to a new weakest-design calculus in the context of BSP. The calculus is based on the par-seq specifunction which involves two required components: it places one established component in parallel with one required component and the result in sequence with another required component to meet a given specification. A calculus is provided for the par-seq specifunction and it is applied to the derivation of a distributed BSP algorithm for greatest common divisor.
10510843
A SOA Based Pipeline System to Deal with Astronomy Telescope Data
In order to deal with telescope data more systematically and flexibly, this paper proposes a grid middleware pipeline system PMGrid based on service-oriented architecture (SOA) for efficient telescope data processing. This system allows users to dynamically compose data process application as a pipeline virtual service (PVS) using existing services for their special purposes. Furthermore, the configured PVS has the standard interface as services and can be published in PMGrid system as a single unit of service shared and reused by other users. Grid technologies and Web service technologies are aligned with each other in this system through standard-based interface and protocols. Based on SOA, the PMGrid system can provide not only more telescope data process functions to satisfy users' special purposes, but also more shared public functions. Combing SOA and grid, the PMGrid system is portable and has advantages in reducing cost and increasing the services utilization. This paper presents the design, analysis, and implementation of the PVS subsystem in the telescope data processing system