8697700
Probabilistic Retrieval Incorporating the Relationships of Descriptors Incrementally
The previous probabilistic retrieval models assume that the relevance probability of a document is independent of the descriptors that are not specified in a query. This is not true in practice because there can be many descriptors that represent the same concept. The probabilistic retrieval model developed in this paper overcomes this unsuitable assumption and incorporates the relationships of descriptors. A learning method is also proposed to figure out the relationships incrementally. Each time retrieval results are available, the method identifies in the relevant documents the descriptors that designate the concepts specified by the query descriptors. Although it employs user feedbacks like relevance feedback, it attempts to capture certain stable relationships of descriptors from many past user queries rather than to distinguish relevant documents from non-relevant ones for a particular query. We show through experiments that the proposed information retrieval method improves retrieval effectiveness over time.
14456420
A replica control method for improving availability for read-only transactions
Data replication is often considered in distributed database systems to enhance availability and performance. The benefit of data replication, however can only be realized at the cost of maintaining the consistency of data. In particular, network partition failures make it more difficult to achieve high data availability while ensuring strong correctness criteria such as l-copy serializability. We propose a replica control method to improve the availability of data in the presence of network partition failures. Our method extends the traditional primary copy method by using the relaxed correctness criterion called insular consistency for large-scale distributed systems, where partition failures frequently occur. We focus on increasing the availability of data for read-only transactions. We introduce a version vector as a tool for guaranteeing insular consistency and present a mechanism that allows read-only transactions to be executed at any partition as long as the insular consistency is satisfied. An asynchronous update propagation mechanism is also employed to improve the performance of update operations. We also show that the proposed method is correct and give some performance considerations.
38239153
Qualitative Behavior Modeling of Information Processing Components
This paper presents qualitative behavior modeling of Information Processing Components(IPCs), which are domain-specific software components for modeling reusable functions in database management systems(DBMSs). After introducing a detailed formal syntax of IPCs, we propose their modular, qualitative behavior generation mechanism. The proposed mechanism is based on qualitative modeling and simulation, thus produces a sequence of temporal state transitions of modeled IPCs. The proposed modeling mechanism aims to facilitate the scientific measurement of
13362734
FINDIT: a fast and intelligent subspace clustering algorithm using dimension voting
Abstract The aim of this paper is to present a novel subspace clustering method named FINDIT. Clustering is the process of finding interesting patterns residing in the dataset by grouping similar data objects from dissimilar ones based on their dimensional values. Subspace clustering is a new area of clustering which achieves the clustering goal in high dimension by allowing clusters to be formed with their own correlated dimensions. In subspace clustering, selecting correct dimensions is very important because the distance between points is easily changed according to the selected dimensions. However, to select dimensions correctly is difficult, because data grouping and dimension selecting should be performed simultaneously. FINDIT determines the correlated dimensions for each cluster based on two key ideas: dimension-oriented distance measure which fully utilizes dimensional difference information, and dimension voting policy which determines important dimensions in a probabilistic way based on V nearest neighbors' information. Through various experiments on synthetic data, FINDIT is shown to be very successful in the high dimensional clustering problem. FINDIT satisfies most requirements for good clustering methods such as accuracy of results, robustness to the noise and the cluster density, and scalability to the dataset size and the dimensionality. Moreover, it is gracefully scalable to full dimension without any modification to algorithm.
591216
The HS File: A New Dynamic Signature File Method for Efficient Information Retrieval
Many works on the signature file methods have been made in the past, but they are mainly for static environments. However, many recent applications in practice require a dynamic information storage structure that effectively supports insertions, deletions and updates. Though there are a few signature file techiniques for dynamic environments, they suffer from serious performance degradation when query signature weights are light. In this paper, we propose a new dynamic signature file organization, called the hierarchical signature(HS) file, that solves the problem of light query signature weights. We perform simulation experiments by using wide range of parameter values. We show through performance comparison based on experiments that the HS file improves performance significantly in both the retrieval time and the storage over-head over the other dynamic signature file methods proposed earlier.
8831551
A per-object based hybrid concurrency control
Existing concurrency control algorithms do not conform well to various environments in the performance perspective. Each algorithm has some assumption on the conflict characteristic of its execution environment, and its performance degrades when the assumption fails. A per-object hybrid scheme integrating a two phase locking algorithm with a parallel validation technique is presented to solve this problem. Read and write accesses on each database object are controlled by one algorithm at a time. This controlling algorithm can alter while transactions are running, in order to enhance the overall system performance. In the simulation study, the proposed scheme with the proposed algorithm alteration strategy is shown to conform well to various execution environments, better than both the two phase locking algorithm and the parallel validation technique.
7659070
Statistical Properties and Adaptive Tuning of Support Vector Machines
In this paper we consider the statistical aspects of support vector machines (SVMs) in the classification context, and describe an approach to adaptively tuning the smoothing parameter(s) in the SVMs. The relation between the Bayes rule of classification and the SVMs is discussed, shedding light on why the SVMs work well. This relation also reveals that the misclassification rate of the SVMs is closely related to the generalized comparative Kullback-Leibler distance (GCKL) proposed in Wahba (1999, Scholkopf, Burges, & Smola (Eds.), Advances in Kernel Methods—Support Vector Learning. Cambridge, MA: MIT Press). The adaptive tuning is based on the generalized approximate cross validation (GACV), which is an easily computable proxy of the GCKL. The results are generalized to the unbalanced case where the fraction of members of the classes in the training set is different than that in the general population, and the costs of misclassification for the two kinds of errors are different. The main results in this paper have been obtained in several places elsewhere. Here we take the opportunity to organize them in one place and note how they fit together and reinforce one another. Mostly the work of the authors is reviewed.
46434197
Flow Control Strategy for Flexible Machining and Assembly System
Abstract In this paper an effective flow control strategy for a Flexible Machining and Assembly System is proposed using the concepts of operation-oriented and, combined push and pull control method. The proposed flow control mechanism could meet production demands with a minimum makespan while satisfying assigned due-dates and keeping a low volume of work-in-process at the same time. It also considers machine failures and rush jobs.
16022713
Query based event extraction along a timeline
In this paper, we present a framework and a system that extracts events relevant to a query from a collection C of documents, and places such events along a timeline. Each event is represented by a sentence extracted from C, based on the assumption that "important" events are widely cited in many documents for a period of time within which these events are of interest. In our experiments, we used queries that are event types ("earthquake") and person names (e.g. "George Bush"). Evaluation was performed using G8 leader names as queries: comparison made by human evaluators between manually and system generated timelines showed that although manually generated timelines are on average more preferable, system generated timelines are sometimes judged to be better than manually constructed ones.
13167655
Optimal Dynamic Control of Resources in a Distributed System
Abstrad-The various advantages of distributed systems can be reallzed unly when their resources are ‘*optimally” (in some sense) contrdled and utilI7~d. For example, distributed systems must he recnnfigured dynamically to rope with component failures and workload changts. Owing to the inherent dilkulty in formulating and solving re~iurce contrd problems, the resnurce control strategies currently propoacdlused for distributed systems are largely ad hoc. It is our purpose in this paper to I) quantitatively formulate the problem of controlling resources in a distributed system so as tu optimize a reward function, and 2) derive optimal control strategies using Markov decision theory. The control variables treated here are quite generak fnr example, they could be control decisions related to system configuration, repair, diagnostics, files, or data. Two algnrithms for resource contnfl In distributed systems are derived for time-invariant Bnd periodic environments, respectively. A detailed example to demonstrate the power and usefulness of our approach is provided.
10452928
Detecting truncation point in steady-state simulation using chaos theory
In the steady-state simulation, it is important to identify initialization bias for the correct estimates of the simulation model under study. In this paper, the methods from chaos theory are applied to the determination of truncation points in the simulation data for controlling the initial bias. Two methods are proposed and evaluated based on their effectiveness for estimating the average waiting time in M/M/1(/spl infin/) queueing model.