2888926
AllInOneNews: development and evaluation of a large-scale news metasearch engine
AllInOneNews is the largest news metasearch engine in the world, connecting to over 1,000 news sites over 150 countries. Implementing a large-scale metasearch engine like AllInOneNews needs to overcome unique challenges not faced by building small metasearch engines such as developing highly scalable search engine selection techniques. In this paper, we discuss these unique challenges and our solutions to these challenges. We also discuss some novel features of AllInOneNews such as highly automated solution and semantic query match. This paper also reports the results of a comparative evaluation of three commercial news search systems, one search engine - Google News and two metasearch engines - Mamma News and AllInOneNews. Several measures such as effectiveness, diversity and time-sensitivity are used to perform the comparison. Another contribution of this paper is that we introduce a novel scheme to compare multiple news search systems in a combined measure that takes both relevance and time-sensitivity of retrieved information into consideration.
9484087
Towards automatic incorporation of search engines into a large-scale metasearch engine
A metasearch engine supports unified access to multiple component search engines. To build a very large-scale metasearch engine that can access up to hundreds of thousands of component search engines, one major challenge is to incorporate large numbers of autonomous search engines in a highly effective manner. To solve this problem, we propose automatic search engine discovery, automatic search engine connection, and automatic search engine result extraction techniques. Experiments indicate that these techniques are highly effective and efficient.
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.
3399913
WISE-Integrator: A System for Extracting and Integrating Complex Web Search Interfaces of the Deep Web
We demonstrate WISE-Integrator - an automatic search interface extraction and integration tool. The basic research issues behind this tool will also be explained.
9755561
A Treemap-Based Result Interface for Search Engine Users
Search engines and metasearch engines on the World Wide Web typically display representative information such as the result document titles and snippets in a one-dimensional ranked list. Alternatively, a few others such as Clusty and Kartoo cluster their results so that users can, to a certain extent, interact with documents, keywords and/or clusters. The number of documents that can be effectively presented in one screen is usually limited to between 10 and 20. In this paper, we propose a method based on treemap visualization that substantially improve the information compactness. In addition, it provides a few unique post-search interaction methods that enable a user to manage a large number of results. An online prototype system is built. Various experiments are designed and done to evaluate the efficiency, effectiveness and usability.
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.
26994753
Efficient Scheduling for Reducing Load in the IMS Presence Service
1209241
Spectral Energy Minimization for Semi-supervised Learning
Data mining problems often involve a large amount of unlabeled data and there is often very limited known information on the dataset. In such scenario, semi-supervised learning can often improve classification performance by utilizing unlabeled data for learning. In this paper, we proposed a novel approach to semi-supervised learning as as an optimization of both the classification energy and cluster compactness energy in the unlabeled dataset. The resulting integer programming problem is relaxed by a semi-definite relaxation where efficient solution can be obtained. Furthermore, the spectral graph methods provide improved energy minimization via the incorporation of additional criteria. Results on UCI datasets show promising results.
12670883
On Hadamard-Type Output Coding in Multiclass Learning
The error-correcting output coding (ECOC) method reduces the multiclass learning problem into a series of binary classifiers. In this paper, we consider the dense ECOC methods, combining an economical number of base learners. Under the criteria of row separation and column diversity, we suggest the use of Hadamard matrices to design output codes and show them better than other codes of the same size. Comparative experiments based on the support vector machines are made for some real datasets from the UCI machine learning repository.
207751
PIDD: database for Protein Inter-atomic Distance Distributions
Protein Inter-atomic Distance Distributions (PIDD) is a dedicated database and structural bio-informatics system for distance based protein modeling. The database is developed to host and analyze the statistical data for protein inter-atomic distances based on their distributions in databases of known protein structures such as in the Protein Data Bank (PDB). PIDD is capable of generating, caching, and displaying the statistical distributions of the distances of various types and ranges. The collected information can be used to extract geometric restraints or mean-force potentials for protein structure determination including nuclear magnetic resonance structure determination and comparative model refinement. PIDD is supported with a friendly designed web interface so that users can easily specify the distance types and ranges, and retrieve, visualize or download the distributions of the distances as they desire. PIDD is freely accessible at
345054
An Evolutionary Algorithm for Parameters Identification in Parabolic Systems
In this paper we construct a novel evolutionary algorithm. It yields good performance on a collection of parabolic parameter identification problems. The algorithm has a good tolerability for the noise in the observed data. Even when the noise level is up to 10% we can also get such a good result.