18360879
Scalable Hybrid Search on Distributed Databases
We have previously described a hybrid keyword search that combines metadata search with a traditional keyword search over unstructured context data. This hybrid search paradigm provides the inquirer additional options to narrow the search with some semantic aspect from the XML metadata query. But in earlier work, we experienced the scalability limitations of a single-machine implementation. In this paper, we describe a scalable hybrid search on distributed databases. This scalable hybrid search provides a total query result from the collection of individual inquiries against independent data fragments distributed in a computer cluster. We demonstrate our architecture extends the scalability of a native XML query limited in a single machine and improves the performance for some queries.
3831285
Data Integration Hub for a Hybrid Paper Search
In this paper we describe the design of a hybrid search that combines simple metadata search with a traditional keyword search over unstructured context data. This paradigm provides the inquirer additional options to narrow the search with some semantic aspects through the XML metadata query. We demonstrate a paper search for a case study of the hybrid search, and describe a data integration hub to integrate those data dispersed on the Net.
5155977
A Hybrid Keyword Search across Peer-to-Peer Federated Databases
The need for Keyword search in databases is suggested both by Web integration with legacy database management system and by dynamic Web publication. However, it sacrifices the inherent meaning of database schema. Web search engines provide clues for resource location on the Web, but have similar semantic problems. The Semantic Web suggests an ideal solution for the semantic problem on the Web. But due to the need for sophisticated domain definition and lack of unified definitions, many Web pages are not part of the Semantic Web. We define a hybrid search to be a search combining semantic metadata and keywords. A hybrid search on P2P based federated databases provides meaningful and scalable search on an overlay network across the Internet. This paper describes the design of the combined search for unstructured data with associated metadata, information retrieval from the repository, peer-to-peer based communication layer, and data integration hub.
14012710
Interference-Minimizing Colorings of Regular Graphs
Communications problems that involve frequency interference, such as the channel assignment problem in the design of cellular telephone networks, can be cast as graph coloring problems in which the frequencies (colors) assigned to an edge's vertices interfere if they are too similar. The paper considers situations modeled by vertex-coloring d-regular graphs with n vertices using a color set 1, 2,..., n, where colors i and j are said to interfere if their circular distance $\min \{ | i-j | , n- | i-j | \}$ does not exceed a given threshold value $\alpha$. Given a d-regular graph G and threshold $\alpha$, an interference-minimizing coloring is a coloring of vertices that minimizes the number of edges that interfere. Let $I_\alpha (G)$ denote the minimum number of interfering edges in such a coloring of $G$. For most triples $(n, \alpha ,d),$ we determine the minimum value of $I_\alpha (G)$ over all d-regular graphs and find graphs that attain it. In determining when this minimum value is 0, we prove that for $r \geq 3$ there exists a d-regular graph G on n vertices that is r-colorable whenever $d \leq (1- \frac{1}{r}) n-1$ and nd is even. We also study the maximum value of $I_\alpha (G)$ over all d-regular graphs and find graphs that attain this maximum in many cases.
5817098
Neural Network Normalization for Genetic Search
An arbitrary neural network has a number of functionally equivalent other networks. This causes redundancy in genetic representation of neural networks, which considerably undermines the merit of crossover in GAs [1]. This problem has received considerable attention in the past and has also been called the “competing conventions” problem [2].
27330844
Efficient processing of regular path joins using PID
Abstract XML is data that has no fixed structure. So it is hard to design a schema for storing and querying an XML data. Instead of a fixed schema, graph-based data models are widely adopted for querying XML. Queries on XML are based on paths in a data graph. A meaningful query usually has several paths in it, but much of recent research is more concerned with optimizing a single path in a query. In this paper, we present an efficient technique for processing multiple path expressions in a query. We implemented our technique and present preliminary performance results.
30180926
Group Key Agreement Protocol Among Mobile Devices in Different Cells
Mobile communication has become more pervasive and it is considered as one of main concerns of IP telephony, video conferencing, multi-user games and etc. in mobile environments. These applications require secure group communication between a multitude of mobile devices owned by group members. Most of the published group key agreement protocols are based on a model which consists of a stationary base station and a cluster of mobile devices. In this paper, we assume a more realistic scenario in which secret group key is established between several base stations and mobile devices in different cells. We present new group key protocol among mobile devices in different cells and analyze its security.
6065142
On effective data clustering in bitemporal databases
Temporal databases provide built-in supports for efficient recording and querying of time-evolving data. In this paper, data clustering issues in temporal database environment are addressed. Data clustering is one of the most effective techniques that can improve performance of a database system. However, data clustering methods for conventional databases do not perform well in temporal databases because there exist crucial differences between their query patterns. We propose a data clustering measure, called Temporal Affinity, that can be used for the clustering of temporal data. The temporal affinity, which is based on the analysis of query patterns in temporal databases, reflects the closeness of temporal data objects in viewpoints of temporal query processing. We perform experiments to evaluate the proposed measure. The experimental results show that a data clustering method with the temporal affinity works better than other methods.