6995202
Odysseus: a high-performance ORDBMS tightly-coupled with IR features
We propose the notion of tight-coupling [K. Whang et al., (1999)] to add new data types into the DBMS engine. In this paper, we introduce the Odysseus ORDBMS and present its tightly-coupled IR features (US patented). We demonstrate a Web search engine capable of managing 20 million Web pages in a non-parallel configuration using Odysseus.
3426940
n-Gram/2L: A Space and Time Efficient Two-Level n-Gram Inverted Index Structure
The n-gram inverted index has two major advantages: language-neutral and error-tolerant. Due to these advantages, it has been widely used in information retrieval or in similar sequence matching for DNA and protein databases. Nevertheless, the n-gram inverted index also has drawbacks: the size tends to be very large, and the performance of queries tends to be bad. In this paper, we propose the two-level n-gram inverted index (simply, the n-gram/2L index) that significantly reduces the size and improves the query performance while preserving the advantages of the n-gram inverted index. The proposed index eliminates the redundancy of the position information that exists in the n-gram inverted index. The proposed index is constructed in two steps: 1) extracting subsequences of length m from documents and 2) extracting n-grams from those subsequences. We formally prove that this two-step construction is identical to the relational normalization process that removes the redundancy caused by a non-trivial multivalued dependency. The n-gram/2L index has excellent properties: 1) it significantly reduces the size and improves the performance compared with the n-gram inverted index with these improvements becoming more marked as the database size gets larger; 2) the query processing time increases only very slightly as the query length gets longer. Experimental results using databases of 1 GBytes show that the size of the n-gram/2L index is reduced by up to 1.9 ~ 2.7 times and, at the same time, the query performance is improved by up to 13.1 times compared with those of the n-gram inverted index.
9830894
Odysseus: a High-Performance ORDBMS Tightly-Coupled with Spatial Database Features
We have earlier proposed the tight-coupling architecture for adding new data types into the DBMS engine. In this paper, we introduce the Odysseus ORDBMS and present its tightly-coupled spatial database features. We demonstrate a geographical information system (GIS) implemented using Odysseus.
18004950
Trajectory clustering: a partition-and-group framework
Existing trajectory clustering algorithms group similar trajectories as a whole, thus discovering common trajectories. Our key observation is that clustering trajectories as a whole could miss common sub-trajectories. Discovering common sub-trajectories is very useful in many applications, especially if we have regions of special interest for analysis. In this paper, we propose a new partition-and-group framework for clustering trajectories, which partitions a trajectory into a set of line segments, and then, groups similar line segments together into a cluster. The primary advantage of this framework is to discover common sub-trajectories from a trajectory database. Based on this partition-and-group framework, we develop a trajectory clustering algorithm TRACLUS. Our algorithm consists of two phases: partitioning and grouping. For the first phase, we present a formal trajectory partitioning algorithm using the minimum description length(MDL) principle. For the second phase, we present a density-based line-segment clustering algorithm. Experimental results demonstrate that TRACLUS correctly discovers common sub-trajectories from real trajectory data.
14238943
Secure query processing against encrypted XML data using Query-Aware Decryption
Dissemination of XML data on the internet could breach the privacy of data providers unless access to the disseminated XML data is carefully controlled. Recently, the methods using encryption have been proposed for such access control. However, in these methods, the performance of processing queries has not been addressed. A query processor cannot identify the contents of encrypted XML data unless the data are decrypted. This limitation incurs overhead of decrypting the parts of the XML data that would not contribute to the query result. In this paper, we propose the notion of Query-Aware Decryption for efficient processing of queries against encrypted XML data. Query-Aware Decryption allows us to decrypt only those parts that would contribute to the query result. For this purpose, we disseminate an encrypted XML index along with the encrypted XML data. This index, when decrypted, informs us where the query results are located in the encrypted XML data, thus preventing unnecessary decryption for other parts of the data. Since the size of this index is much smaller than that of the encrypted XML data, the cost of decrypting this index is negligible compared with that for unnecessary decryption of the data itself. The experimental results show that our method improves the performance of query processing by up to six times compared with those of existing methods. Finally, we formally prove that dissemination of the encrypted XML index does not compromise security.
2077132
Continuous query processing in data streams using duality of data and queries
Recent data stream systems such as TelegraphCQ have employed the well-known property of duality between data and queries. In these systems, query processing methods are classified into two dual categories -- data-initiative and query-initiative -- depending on whether query processing is initiated by selecting a data element or a query. Although the duality property has been widely recognized, previous data stream systems do not fully take advantages of this property since they use the two dual methods independently: data-initiative methods only for continuous queries and query-initiative methods only for ad-hoc queries. We contend that continuous query processing can be better optimized by adopting an approach that integrates the two dual methods. Our primary contribution is based on the observation that spatial join is a powerful tool for achieving this objective. In this paper, we first present a new viewpoint of transforming the continuous query processing problem to a multi-dimensional spatial join problem. We then present a continuous query processing algorithm based on spatial join, which we name Spatial Join CQ. This algorithm processes continuous queries by finding the pairs of overlapping regions from a set of data elements and a set of queries, both defined as regions in the multi-dimensional space. The algorithm achieves the advantages of the two dual methods simultaneously. Experimental results show that the proposed algorithm outperforms earlier algorithms by up to 36 times for simple selection continuous queries and by up to 7 times for sliding window join queries.
6394953
Accelerating Database Processing at e-Commerce Sites
Most e-commerce Web sites dynamically generate their contents through a three-tier server architecture composed of a Web server, an application server, and a database server. In such an architecture, the database server easily becomes a bottleneck to the overall performance. In this paper, we propose WDBAccel, a high-performance database server accelerator that significantly improves the throughput of the database processing, and thus that of the overall Web site. WDBAccel eliminates costly, complex query processing needed to obtain query results by reusing previous query results for subsequent queries. This differentiates WDBAccel from other database cache systems, which replicate a database into multiple conventional DBMS’s and distribute queries among them. We evaluate the performance of WDBAccel by using the queries of the TPC-W benchmark. The measurement results show that WDBAccel outperforms DBMS-based cache systems by up to an order of magnitude.
40201784
Case-based modification for optimization agents: AGENT-OPT
For the effective implementation of an inter-organizational supply chain on the Web, many optimization model agents need to be embedded in the distributed software agents. For instance, many suppliers make requests to a delivery scheduler who manages a model warehouse at the e-hub. The scheduler deals with the scheduling of many truckers and each trucker's agent must have its own routing optimization models. Since the formulations in the model warehouse vary depending upon the requirements, it is impossible to formulate all combinations in advance. Therefore, we need a case-based model modification scheme that can generate the required formulation from the semantically specified requirement in the agent communication language.This research deals with the issues of the architecture of an optimization model agent system AGENT-OPT, modeling request language in XML, optimization model representation in semantic-level objects using UNIK-OPT, a method of selecting a base model, an optimization model modification language (OMML), and rule-based modification reasoning. The approach is applied to the delivery scheduling to study the effect of base model selection policies on the modification effort. To determine whether to start with a primitive model, full model, or the most similar model, we experimented with the sensitivity of proximity to the primitive model on 24 cases and discovered the threshold for choosing the most efficient base model.
7110658
Automatic Rule Generation by the Transformation of Expert's Diagram: LIFT
Abstract To enhance the efficiency of revealing and refining an expert's knowledge, the Expert's Diagram approach is proposed. The Expert's Diagram proposed in this paper is specifically designed for rule-based consulting systems. Using the Expert's Diagram approach, the knowledge acquisition system LIFT is developed, which transforms the Expert's Diagram automatically to rules in the syntax of the shell SKI 2 that is developed for tax consulting-purposes. For the transformation, either the conclusion-directed approach or the condition-directed approach can be applied. The role of LIFT can be generalized to some extent to adapt to the changes in the Expert's Diagram and target shells. According to our experience in the acquisition of Korean corporate tax knowledge, experts could reveal their knowledge effectively using the Expert's Diagram after a short period of training. Thus the rules could be generated automatically by LIFT without the aid of knowledge engineers.
46124956
The formal definition of the BASIC language
The translator The translator which transforms the parsed text into the abstract text (that is, a text which conforms to the abstract syntax and takes into account the default conditions) is peculiar to the language in the Lucas system but has not been developed here since it is the author's opinion that a general translator may be developed which is applicable to all languages. The default rules for Basic are:
10177775
Enhanced knowledge management with eXtensible Rule Markup Language
XML has become the standard platform for structured data exchange on the Web. Next concern of semantic Web is the exchange of rules in markup language form. The rules should be represented in such a way as to allow software agents to process and browse them for human comprehension. For this purpose, we propose a language eXtensible Rule Markup Language (XRML). XRML is composed of rule identification, rule structure, and rule triggering markup languages. In XRML, a critical concern is how to extract the structured rules implicitly embedded in the Web pages and keep consistency between the two. By using the XRML, the Web based knowledge management systems (KMS) can be integrated with rule-based expert systems. The advanced architecture with XRML can extend the application of KMS to automated form processing, preventive auditing, rule exchange and integration, and agent-based e-commerce.