30150892
Efficient yet accurate clustering
The authors show that most hierarchical agglomerative clustering (HAC) algorithms follow a 90-10 rule where roughly 90% iterations from the beginning merge cluster pairs with dissimilarity less than 10% of the maximum dissimilarity. We propose two algorithms: 2-phase and nested, based on partially overlapping partitioning (POP). To handle high-dimensional data efficiently, we propose a tree structure particularly suitable for POP. Extensive experiments show that the proposed algorithms reduce the time and memory requirement of existing HAC algorithms significantly without compromising accuracy.
8367210
Sensor Sequence Modeling for Driving
Intelligent systems in automobiles need to be aware of the driving and driver context. Available sensor data stream has to be modeled and monitored in order to do so. Currently there exist no building blocks for hierarchical modeling of driving. By semi-supervised segmentation such building blocks can be discovered. We call them drivemes in analogy to phonemes. More parsimonious modeling of driving becomes now possible.
5365583
NeuroRule: A Connectionist Approach to Data Mining
Classification, which involves finding rules that partition a given da.ta set into disjoint groups, is one class of data mining problems. Approaches proposed so far for mining classification rules for large databases are mainly decision tree based symbolic learning methods. The connectionist approach based on neura.l networks has been thought not well suited for data mining. One of the major reasons cited is that knowledge generated by neural networks is not explicitly represented in the form of rules suitable for verification or interpretation by humans. This paper examines this issue. With our newly developed algorithms, rules which are similar to, or more concise than those generated by the symbolic methods can be extracted from the neural networks. The data mining process using neural networks with the emphasis on rule extraction is described. ExperimenM results and comparison with previously published works are presented.
16386059
A Monotonic Measure for Optimal Feature Selection
Feature selection is a problem of choosing a subset of relevant features. In general, only exhaustive search can bring about the optimal subset. With a monotonic measure, exhaustive search can be avoided without sacrificing optimality. Unfortunately, most error- or distancebased measures are not monotonic. A new measure is employed in this work that is monotonic and fast to compute. The search for relevant features according to this measure is guaranteed to be complete but not exhaustive. Experiments are conducted for verification.
46794790
Analysis of Hidden Representations by Greedy Clustering
The hidden layer of backpropagation neural networks (NNs) holds the key to the networks' success in solving pattern classification problems. The units in the hidden layer encapsulate the network's internal representations of the outside world described by the input data. this paper, the hidden representations of trained networks are investigated by means simple greedy clustering algorithm. This clustering algorithm is applied to networks have been trained to solve well-known problems: the monks problems, the 5-bit problem and the contiguity problem. The results from applying the algorithm to problems with known concepts provide us with a better understanding of NN learning. These also explain why NNs achieve higher predictive accuracy than that of decision-tree methods. The results of this study can be readily applied to rule extraction from Production rules are extracted for the parity and the monks problems, as well as benchmark data set: Pima Indian diabetes diagnosis. The extracted rules from the Indi...
14543078
Resource description framework: metadata and its applications
Universality, the property of the Web that makes it the largest data and information source in the world, is also the property behind the lack of a uniform organization scheme that would allow easy access to data and information. A semantic web, wherein different applications and Web sites can exchange information and hence exploit Web data and information to their full potential, requires the information about Web resources to be represented in a detailed and structured manner. Resource Description Framework (RDF), an effort in this direction supported by the World Wide Web Consortium, provides a means for the description of metadata which is a necessity for the next generation of interoperable Web applications. The success of RDF and the semantic web will depend on (1) the development of applications that prove the applicability of the concept, (2) the availability of application interfaces which enable the development of such applications, and (3) databases and inference systems that exploit RDF to identify and locate most relevant Web resources. In addition, many practical issues, such as security, ease of use, and compatibility, will be crucial in the success of RDF. This survey aims at providing a glimpse at the past, present, and future of this upcoming technology and highlights why we believe that the next generation of the Web will be more organized, informative, searchable, accessible, and, most importantly, useful. It is expected that knowledge discovery and data mining can benefit from RDF and the Semantic Web.
893749
A Distributed and Efficient Flooding Scheme Using 1-Hop Information in Mobile Ad Hoc Networks
Flooding is one of the most fundamental operations in mobile ad hoc networks. Traditional implementation of flooding suffers from the problems of excessive redundancy of messages, resource contention, and signal collision. This causes high protocol overhead and interference with the existing traffic in the networks. Some efficient flooding algorithms were proposed to avoid these problems. However, these algorithms either perform poorly in reducing redundant transmissions or require each node to maintain 2-hop (or more) neighbors information. In the paper, we study the sufficient and necessary condition of 100 percent deliverability for flooding schemes that are based on only 1-hop neighbors information. We further propose an efficient flooding algorithm that achieves the local optimality in two senses: 1) the number of forwarding nodes in each step is minimal and 2) the time complexity for computing forwarding nodes is the lowest, which is O(nlogn), where n is the number of neighbors of a node. Extensive simulations have been conducted and simulation results have shown the excellent performance of our algorithm
9642703
Discovering typical structures of documents: a road map approach
The structure of a document refers to the role and hierarchy of subdocument references. Many online documents are similarly structured, though not identically structured. We study the problem of discovering “typical” structures of a collection of such documents, where the user specifies the minimum frequency of a typical structure. We will consider structural features of subdocument references such as labeling, nesting, ordering, cyclicity, and wild-card references, like those found on the Web and digital libraries. Typical structures can be used to serve the following purposes. (a) The “table-ofcontent” for gaining the general information of a source. (b) A road map for browsing and querying a source. (c) A basis for clustering documents. (d) Partial schemas for building structured layers to provide standard database access methods. (e) User/customer’s interests and browsing patterns. We present a solution to the discovery problem.
7448673
Simple rules underlying gene expression profiles of more than six subtypes of acute lymphoblastic leukemia (ALL) patients
MOTIVATIONS AND RESULTS
For classifying gene expression profiles or other types of medical data, simple rules are preferable to non-linear distance or kernel functions. This is because rules may help us understand more about the application in addition to performing an accurate classification. In this paper, we discover novel rules that describe the gene expression profiles of more than six subtypes of acute lymphoblastic leukemia (ALL) patients. We also introduce a new classifier, named PCL, to make effective use of the rules. PCL is accurate and can handle multiple parallel classifications. We evaluate this method by classifying 327 heterogeneous ALL samples. Our test error rate is competitive to that of support vector machines, and it is 71% better than C4.5, 50% better than Naive Bayes, and 43% better than k-nearest neighbour. Experimental results on another independent data sets are also presented to show the strength of our method.


AVAILABILITY
Under http://sdmc.lit.org.sg/GEDatasets/, click on Supplementary Information.
62639812
Traffic grooming in WDM/SONET BLSR rings with multiple line speeds
WDM/SONET provides a natural migration path to support traffic growth. In WDM/SONET, each wavelength is a separate SONET ring and each ring can be set to one of several line speeds. The line speed should be high if there is enough traffic to realize the economy of scale, otherwise, it should be low to reduce the cost. Despite of the advantages, there are no general tools and methodologies available to help network designers enjoy the benefits of multiple line speeds. For the first time, we propose a comprehensive approach to solve the traffic grooming problem, which includes both novel, complete ILP formulations that can be used to solve small size problems exactly and an efficient heuristic algorithm that can be used to solve large problems quickly. Using the tools we developed, we study the trade-offs of shortest path routing, study the cost benefits of traffic switching, compare UPSR and BLSR, and show that multiple line speeds can significantly reduce cost
6771108
Fault-Tolerant Relay Node Placement in Wireless Sensor Networks
The paper addresses the relay node placement problem in two-tiered wireless sensor networks. Given a set of sensor nodes in an Euclidean plane, our objective is to place minimum number of relay nodes to forward data packets from sensor nodes to the sink, such that: 1 the network is connected, 2 the network is 2-connected. For case one, we propose a 6+e-approximation algorithm for any e>0 with polynomial running time when e is fixed. For case two, we propose two approximation algorithms with 24+e and 6/T+12+e, respectively, where T is the ratio of the number of relay nodes placed in case one to the number of sensors.