27854712
Retrieval of Multimedia Web Documents and Removal of Redundant Information
This paper describes a search engine for multimedia web documents and a methodology for removing (partially or totally) redundant information from multiple documents in an effort to synthesize new documents. In this paper, a typical multimedia document contains free text and images and additionally has associating well-structured data. An SQL-like query language, WebSSQL, is proposed to retrieve this type of documents. The main differences between WebSSQL and other proposed SQL extensions for retrieving web documents are that WebSSQL is similarity-based and supports conditions on images. This paper also deals with the detection and removal of redundant information (text paragraphs and images) from multiple retrieved documents. Documents reporting the same or related events and stories may contain substantial redundant information. The removal of the redundant information and the synthesis of these documents into a single document can not only save a user's time to acquire the information but also storage space to archive the data. The methodology reported here consists of techniques for analyzing text paragraphs and images as well as a set of similarity criteria used to detect redundant paragraphs and images. Examples are provided to illustrate these techniques.
18318137
Automatically Detecting Boolean Operations Supported by Search Engines, Towards Search Engine Query Language Discovery
Each Web search engine provides query language through which it can communicate with its users and retrieve corresponding results to user queries. Supporting Boolean operations is a major characteristic of the query language. In this paper, we propose a novel, fully automatic, query probing based approach to identify what Boolean operations that are supported by a search engines and their corresponding syntaxes. Experiments show high effectiveness and efficiency. Along with this, we also provide a Web application called SE-BOSS (Search Engine Boolean Operation Scanning System) for interested users.
957553
A highly scalable and effective method for metasearch
A metasearch engine is a system that supports unified access to multiple local search engines. Database selection is one of the main challenges in building a large-scale metasearch engine. The problem is to efficiently and accurately determine a small number of potentially useful local search engines to invoke for each user query. In order to enable accurate selection, metadata that reflect the contents of each search engine need to be collected and used. This article proposes a highly scalable and accurate database selection method. This method has several novel features. First, the metadata for representing the contents of all search engines are organized into a single integrated representative. Such a representative yields both computational efficiency and storage efficiency. Second, the new selection method is based on a theory for ranking search engines optimally. Experimental results indicate that this new method is very effective. An operational prototype system has been built based on the proposed approach.
15933707
Automatic extraction of web search interfaces for interface schema integration
This paper provides an overview of a technique for extracting information from the Web search interfaces of e-commerce search engines that is useful for supporting automatic search interface integration. In particular, we discuss how to group elements and labels on a search interface into attributes and how to derive certain meta-information for each attribute.
16923777
Identifying redundant search engines in a very large scale metasearch engine context
For a given set of search engines, a search engine is redundant if its searchable contents can be found from other search engines in this set. In this paper, we propose a method to identify redundant search engines in a very large-scale metasearch engine context. The general problem is equivalent to an NP hard problem -- the set-covering problem. Due to the large number of search engines that need to be considered and the large sizes of these search engines, approximate solutions must be developed. In this paper, we propose a general methodology to tackle this problem and within the context of this methodology, we propose several new heuristic algorithms for solving the set-covering problem.
12822673
Configuring Java-Based Web Application Development Environment for an Academic Setting
In this paper, we analyze the characteristics and constraints of a typical academic environment for web application development. A set of Java-based web technologies and tools are introduced and reviewed for such an environment. The motivation behind this work is to provide comprehensive resource for university faculty members and students about emerging technologies and available tools to facilitate rapid development of web applications.
7233121
PARMA: a PHY/MAC aware routing metric for ad-hoc wireless networks with multi-rate radios
Ad-hoc wireless networks with multi-rate radios (such as 802.11a, b, g) require a new class of MAC/PHY aware metrics that take into account factors such as physical-layer link speed and MAC-layer channel congestion. Conventional "layer 3" ad-hoc routing algorithms typically make routing decisions based on the minimum hop-count (MH). Use of the MH metric leads to the selection of paths with few hops, but one or more of these hops may turn out to be low-speed radio links due to adaptive rate selection at the physical layer We investigate a new cross-layer routing metric that takes into account both physical layer link speed and estimated channel congestion, thus aiming to minimize end-to-end delay that includes both transmission and access times. The proposed "PARMA" routing metric thus helps to spread the traffic across the "good links and nodes" in the network, increasing network capacity and reducing packet loss and delay. The paper presents the design and implementation of the proposed PARMA metric for proactive ad-hoc routing protocols, such as DSDV. DSDV modifications for incorporating the MAC/PHY aware metric into an ns-2 simulation model are given. Simulation results for typical multi-rate 802.11 ad-hoc network scenarios show that the proposed cross-layer PHY/MAC aware metric achieves significantly higher network throughput and decreases network congestion by selecting paths with high bit-rate links, while also avoiding areas of MAC congestion.
6719824
Performance modeling of multicast groups for multiplayer games in peer-to-peer networks
A computer game is usually considered as a finite state machine. For a distributed multiplayer game, state information has to be exchanged among its players when they move and interact in a virtual space. If the number of players is very large, only a small subset of the game entities, controlled by their players, is interested and forms a multicast group so as to reduce the information dissemination over the network. In this paper, analytical models are proposed for evaluating the performance of multicast groups with multiplayer games in peer-to-peer networks. The system modeling is based on two stochastic processes and their possible solutions in terms of game type, player activity, and entity vision size, mode of user input processing, and grouping strategy. The cost of game operations on consumed resources is introduced to characterize the performance measure. Numerical examples are demonstrated, which provide useful insights of the behaviors of such systems.
17480069
Similarity-based Web service matchmaking
With the increasing growth in popularity of Web services, matchmaking of relevant Web services becomes a significant challenge. Commonly, Web service is described by WSDL and published on UDDI registers. UDDI provides limited search facilities allowing only a keyword-based search of businesses, services, and the so called tModels based on names and identifiers. This category-based keyword-browsing method is clearly insufficient. Semantic Web service uses DAML-S instead of WSDL to represent capabilities of Web services. This improvement enables software agents or search engines to automatically find appropriate Web services via ontologies and reasoning algorithm enriched methods. However, the high cost of formally defining to the heavy and complicated services makes this improvement widespread adoption unlikely. To cope with these limitations, we have developed a suite of methods which assesses the similarity of Web services to achieve matchmaking. In particular, we present a conceptual model which classifies properties of Web services into four categories. For each category, a similarity assessment method has been given. In Web service matchmaking process, these similarity assessment methods can be used together or individually. Experiments highlight complementary contributions that our work makes to facilitate Web service matchmaking.
9838468
A Semi-supervised SVM for Manifold Learning
Many classification tasks benefit from integrating manifold learning with semi-supervised learning. By formulating the learning task in a semi-supervised manner, we propose a novel objective function that combines the manifold consistency of whole dataset with the hinge loss of class label prediction. This formulation results in a SVM-alike task operating on the kernel derived from the graph Laplacian, and is capable of capturing the intrinsic manifold structure of the whole dataset and maximizing the margin separating labelled examples. Results on face and handwritten digit recognition tasks show significant performance gain. The performance gain is particularly impressive when only a small training set is available, which is often the true scenario of many real-world problems
7810391
Refinement of Nmr-determined Protein Structures with Database Derived Distance Constraints
The protein structures determined by NMR (Nuclear Magnetic Resonance Spectroscopy) are not as detailed and accurate as those by X-ray crystallography and are often underdetermined due to the inadequate distance data available from NMR experiments. The uses of NMR-determined structures in such important applications as homology modeling and rational drug design have thus been severely limited. Here we show that with the increasing numbers of high quality protein structures being determined, a computational approach to enhancing the accuracy of the NMR-determined structures becomes possible by deriving additional distance constraints from the distributions of the distances in databases of known protein structures. We show through a survey on 462 NMR structures that, in fact, many inter-atomic distances in these structures deviate considerably from their database distributions and based on the refinement results on 10 selected NMR structures that these structures can actually be improved significantly when a selected set of distances are constrained within their high probability ranges in their database distributions.