Multiparty interactive network applications such as teleconferencing, network gaming, and online trading are gaining popularity. In addition to end-to-end latency bounds, these applications require that the delay difference among multiple clients of the service is minimized for a good interactive experience. We propose a Latency EQualization (LEQ) service, which equalizes the perceived latency for all […]
Efficient Error Estimating Coding: Feasibility and Applications
Motivated by recent emerging systems that can leverage partially correct packets in wireless networks, this paper proposes the novel concept of error estimating coding (EEC). Without correcting the errors in the packet, EEC enables the receiver of the packet to estimate the packet’s bit error rate, which is perhaps the most important meta-information of a […]
Adaptive Opportunistic Routing for Wireless Ad Hoc Networks
A distributed adaptive opportunistic routing scheme for multihop wireless ad hoc networks is proposed. The proposed scheme utilizes a reinforcement learning framework to opportunistically route the packets even in the absence of reliable knowledge about channel statistics and network model. This scheme is shown to be optimal with respect to an expected average per-packet reward […]
Subspace Similarity Search under {rm L}_p-Norm
Similarity search has been widely used in many applications such as information retrieval, image data analysis, and time-series matching. Previous work on similarity search usually consider the search problem in the full space. In this paper, however, we tackle a problem, subspace similarity search, which finds all data objects that match with a query object […]
CoCITe—Coordinating Changes in Text
Text streams are ubiquitous and contain a wealth of information, but are typically orders of magnitude too large in scale for comprehensive human inspection. There is a need for tools that can detect and group changes occurring within text streams and substreams, in order to find, structure, and summarize these changes for presentation to human […]
ROAD: A New Spatial Object Search Framework for Road Networks
In this paper, we present a new system framework called ROAD for spatial object search on road networks. ROAD is extensible to diverse object types and efficient for processing various location-dependent spatial queries (LDSQs), as it maintains objects separately from a given network and adopts an effective search space pruning technique. Based on our analysis […]
Practical Efficient String Mining
In recent years, several algorithms for mining frequent and emerging substring patterns from databases of string data (such as proteins and natural language texts) have been discovered, all of which traverse an enhanced suffix array data structure. All of these algorithms lie at either extreme of the efficiency spectrum; they are either fast and use […]
Mutual Information-Based Supervised Attribute Clustering for Microarray Sample Classification
Microarray technology is one of the important biotechnological means that allows to record the expression levels of thousands of genes simultaneously within a number of different samples. An important application of microarray gene expression data in functional genomics is to classify samples according to their gene expression profiles. Among the large amount of genes presented […]
Learning a Propagable Graph for Semisupervised Learning: Classification and Regression
we present a novel framework, called learning by propagability, for two essential data mining tasks, i.e., classification and regression. The whole learning process is driven by the philosophy that the data labels and the optimal feature representation jointly constitute a harmonic system, where the data labels are invariant with respect to the propagation on the […]
Incremental Information Extraction Using Relational Databases
Information extraction systems are traditionally implemented as a pipeline of special-purpose processing modules targeting the extraction of a particular kind of information. A major drawback of such an approach is that whenever a new extraction goal emerges or a module is improved, extraction has to be reapplied from scratch to the entire text corpus even […]