206566936
Approximate Tree Matching in the Presence of Variable Length Don't Cares
Ordered labeled trees are trees in which the sibling order matters. This paper presents algorithms for three problems having to do with approximate matching for such trees with variable length don′t cares (VLDCs). In strings, a VLDC symbol in the pattern may substitute for zero or more symbols in the data string. For example, if "com∗er" is the pattern, then the "∗" would substitute for the substring "put" when matching the data string "computer." Approximate VLDC matching in strings means that after the best possible substitution, the pattern still need not be the same as the data string for a match to be allowed. For example, "com∗er" matches "counter" within distance one (representing the cost of removing the "m" from "com∗er" and having the "∗" substitute for "unt"). We generalize approximate VLDC string matching to three algorithms for approximate VLDC matching on trees. The time complexity of our algorithms is O(|P| × |D| × min(depth(P), leaves(P)) × min(depth(D), leaves(D))) (where |P| and |D| are the number of nodes respectively of the pattern P and the data tree D), the same as for the best approximate tree matching algorithm without VLDCs previously reported.
12680145
Finding Patterns in Three-Dimensional Graphs: Algorithms and Applications to Scientific Data Mining
Presents a method for finding patterns in 3D graphs. Each node in a graph is an undecomposable or atomic unit and has a label. Edges are links between the atomic units. Patterns are rigid substructures that may occur in a graph after allowing for an arbitrary number of whole-structure rotations and translations as well as a small number (specified by the user) of edit operations in the patterns or in the graph. (When a pattern appears in a graph only after the graph has been modified, we call that appearance "approximate occurrence.") The edit operations include relabeling a node, deleting a node and inserting a node. The proposed method is based on the geometric hashing technique, which hashes node-triplets of the graphs into a 3D table and compresses the label-triplets in the table. To demonstrate the utility of our algorithms, we discuss two applications of them in scientific data mining. First, we apply the method to locating frequently occurring motifs in two families of proteins pertaining to RNA-directed DNA polymerase and thymidylate synthase and use the motifs to classify the proteins. Then, we apply the method to clustering chemical compounds pertaining to aromatic compounds, bicyclicalkanes and photosynthesis. Experimental results indicate the good performance of our algorithms and high recall and precision rates for both classification and clustering.
236203
New Techniques for DNA Sequence Classification
DNA sequence classification is the activity of determining whether or not an unlabeled sequence S belongs to an existing class C. This paper proposes two new techniques for DNA sequence classification. The first technique works by comparing the unlabeled sequence S with a group of active motifs discovered from the elements of C and by distinction with elements outside of C. The second technique generates and matches gapped fingerprints of S with elements of C. Experimental results obtained by running these algorithms on long and well conserved Alu sequences demonstrate the good performance of the presented methods compared with FASTA. When applied to less conserved and relatively short functional sites such as splice-junctions, a variation of the second technique combining fingerprinting with consensus sequence analysis gives better results than the current classifiers employing text compression and machine learning algorithms.
14900181
Unordered tree mining with applications to phylogeny
Frequent structure mining (FSM) aims to discover and extract patterns frequently occurring in structural data, such as trees and graphs. FSM finds many applications in bioinformatics, XML processing, Web log analysis, and so on. We present a new FSM technique for finding patterns in rooted unordered labeled trees. The patterns of interest are cousin pairs in these trees. A cousin pair is a pair of nodes sharing the same parent, the same grandparent, or the same great-grandparent, etc. Given a tree T, our algorithm finds all interesting cousin pairs of T in O(|T|/sup 2/) time where |T| is the number of nodes in T. Experimental results on synthetic data and phylogenies show the scalability and effectiveness of the proposed technique. To demonstrate the usefulness of our approach, we discuss its applications to locating co-occurring patterns in multiple evolutionary trees, evaluating the consensus of equally parsimonious trees, and finding kernel trees of groups of phylogenies. We also describe extensions of our algorithms for undirected acyclic graphs (or free trees).
11616193
Automatic Hierarchical Classification of Structured Deep Web Databases
We present a method that automatically classifies structured deep Web databases according to a pre-defined topic hierarchy. We assume that there are some manually classified databases, i.e., training databases, in every node of the topic hierarchy. Each training database is probed using queries constructed from the node titles of the topic hierarchy and the query result counts reported by the database are used to represent the content of the database. Hence, when adding a new database it can be probed by the same set of queries and classified to a node whose training databases are most similar to the new one. Specifically, a support vector machine classifier is trained on each internal node of the topic hierarchy with these training databases and the new database can be classified into the hierarchy top-down level by level. A feature extension method is proposed to create discriminant features. Experiments run on real structured Web databases collected from the Internet show that this classification method is quite accurate.
2286283
Query result ranking over e-commerce web databases
To deal with the problem of too many results returned from an E-commerce Web database in response to a user query, this paper proposes a novel approach to rank the query results. Based on the user query, we speculate how much the user cares about each attribute and assign a corresponding weight to it. Then, for each tuple in the query result, each attribute value is assigned a score according to its "desirableness" to the user. These attribute value scores are combined according to the attribute weights to get a final ranking score for each tuple. Tuples with the top ranking scores are presented to the user first. Our ranking method is domain independent and requires no user feedback. Experimental results demonstrate that this ranking method can effectively capture a user's preferences.
37966786
Analysis of soft handoff algorithms with dynamic spreading WCDMA system
The undergoing 3G wireless network needs to support integration of voice and multimedia data services with varying QoS requirements. It is critical that the least BER for voice traffic, WWW traffic, and streaming video traffic be guaranteed at all time. With the capability of dynamically changing spreading factor, CDMA system could provide a range of QoS fitting the needs for different traffic type. In this paper, we extend our dynamic spreading admission control scheme to a multi-cell situation, by proposing a dynamic spreading enable soft handoff framework. The static system behavior is analyzed through the studying of the updating probability for both handoff mobile and target cell. Our analysis shows that the updating probability varies according the traffic of interest. A general expression of the joint updating probability is given assuming an equal distribution of traffic type. The processing time of the handoff request is analyzed. We found that the update process caused by handoff is the major component of delay. Further investigation shows that the update associated with handoff might consume too much access channel time, and increase the delay of handoff, especially when handoff traffic is heavy. We therefore adopt a batch mechanism such that multiple handoff requests could be processed simultaneously. The average delay is reduced from 1.12 seconds to 800 ms in heavy handoff rate.
16538539
Optimal jumper insertion for antenna avoidance under ratio upper-bound
Antenna effect may damage gate oxides during plasma-based fabrication process. The antenna ratio of total exposed antenna area to total gate oxide area is directly related to the amount of damage. Jumper insertion is a common technique applied at routing and post-layout stages to avoid and to fix the problems caused by the antenna effect. This paper presents an optimal algorithm for jumper insertion under the ratio upper-bound. It handles Steiner trees with obstacles. The algorithm us based on dynamic programming while works on free trees. The time complexity is O(alpha|V|2 ) and the space complexity is O(|V|2), where |V| is the number of nodes in the routing tree and a is a factor depending on how to find a non-blocked position on a wire for a jumper
891661
Fast prefix matching of bounded strings
Longest Prefix Matching (LPM) is the problem of finding which string from a given set is the longest prefix of another, given string. LPM is a core problem in many applications, including IP routing, network data clustering, and telephone network management. These applications typically require very fast matching of bounded strings, i.e., strings that are short and based on small alphabets. We note a simple correspondence between bounded strings and natural numbers that maps prefixes to nested intervals so that computing the longest prefix matching a string is equivalent to finding the shortest interval containing its corresponding integer value. We then present retries, a fast and compact data structure for LPM on general alphabets. Performance results show that retries often outperform previously published data structures for IP look-up. By extending LPM to general alphabets, retries admit new applications that could not exploit prior LPM solutions designed for IP look-ups.
15784976
A New Algorithm to Solve Synchronous Consensus for Dependent Failures
Fault tolerant algorithms are often designed under the t-out-of-n assumption, which is based on the assumption that all processes or components fail independently with equal probability. However, real systems may exhibit dependent failures. Cores and survivor sets are used to build an abstraction model for dependent process failures. Using this abstraction, we design an algorithm to solve consensus problem crash failures. Our algorithm uses the processes in all cores to broadcast messages. Each core reaches agreement separately and even simultaneously in some round with no failure in the core. In the worst-case, the decision can be made in the round that is equal to the size of the minimal core. Our algorithm guarantees that all processes eventually decide on the same value regardless the initial values. We prove the correctness of our algorithm and give the lower bound of the number of rounds to solve consensus problem.
12016558
Constrained motion control of flexible robot manipulators based on recurrent neural networks
In this paper, a neural network approach is presented for the motion control of constrained flexible manipulators, where both the contact force everted by the flexible manipulator and the position of the end-effector contacting with a surface are controlled. The dynamic equations for vibration of flexible link and constrained force are derived. The developed control, scheme can adaptively estimate the underlying dynamics of the manipulator using recurrent neural networks (RNNs). Based on the error dynamics of a feedback controller, a learning rule for updating the connection weights of the adaptive RNN model is obtained. Local stability properties of the control system are discussed. Simulation results are elaborated on for both position and force trajectory tracking tasks in the presence of varying parameters and unknown dynamics, which show that the designed controller performs remarkably well.