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.
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.
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.
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.
17427180
Analyses of multiple evidence combination
It hsa been known that different representations of a query ret rieve different sets of documents. Recent work suggests that significant improvements in retrieval performance can be achieved by combining multiple representations of an information need. However, little effort has been made to understand the reason why combining multiple sources of evidence improves retrieval effectiveness. In this paper we analyze why improvements can be achieved with evidence combination, and investigate how evidence should be combined. We describe a rationale for multiple evidence combination, and propose a combining method whose properties coincide wit h the rationale. We also investigate e the effect of using rank instead of similarity on retrieval effectiveness.
17910425
TMO-structured distributed location information system prototype
To realize location-based services, it is essential to handle the extreme situation that must cope with a very large volume, at least millions, of moving items. In this paper, we describe a location information system prototype of GALIS, which is a cluster-based scalable distributed computing system architecture which consists of multiple data processors, each dedicated to keeping records relevant to a different geographical zone and a different time zone. The proposed system contains all of the major computing nodes of GALIS architecture and is developed as a middleware on top of commercial main-memory database engines and spatial database engines, for short-term data and long-term data processing, respectively. To show the usefulness of our system, some experimental results showing clear advantages of distributed computing are also explained.
11377777
Delayed locking technique for improving real-time performance of embedded Linux by prediction of timer interrupt
In this paper, we propose a new technique, called a delayed locking technique, to improve the real-time performance of embedded Linux. The proposed technique employs the rule that entering a critical section is allowed only if the operation does not disturb the future execution of the real-time application. To execute this rule, we introduce the concepts of timer interrupt prediction and lock hold time acquisition. In addition, we designed and implemented a new high-resolution timer that is simple, yet efficient. We implemented the prototype on Linux 2.4.18. Experimental results show that the worst-case OS latency of real-time process is reduced to 23% of the original one, at the expense of slowdown of the nonreal-time process by 20%. Though we focus only on embedded Linux, our technique is useful for all kinds of real-time operating systems in which the critical section is significantly long.
1336097
Distributed synchronous control units for dataflow graphs under allocation of telescopic arithmetic units
In order to enjoy the performance improvement effects of variable computation time arithmetic units at a system level, we propose a new synchronous control unit design methodology for dataflow graphs under allocation of a telescopic arithmetic unit, which is one of the well-known synchronous variable computation time arithmetic units. The proposed method generates an independent synchronous controller for each component arithmetic unit, and builds a distributed synchronous control unit through integrating the derived controllers. The distributed structure of the final synchronous control unit maximizes the performance improvement effect of telescopic arithmetic units through a complete preservation of original concurrency among operations.
3175252
Predicate-based caching in mobile clients for con tinuous partial match queries
This paper proposes a cache management scheme for continuous partial match queries in mobile computing systems. Conventional cache management methods for mobile clients are record ID-based ones. However, since the partial match query is a content-based retrieval, the conventional record ID-based approach cannot properly manage the cache consistency. We show the pr edicate- based approach is an effective cache management in mobile environments.