31779905
COMMIX: towards effective web information extraction, integration and query answering
As WWW becomes more and more popular and powerful, how to search information on the web in database way becomes an important research topic. COMMIX, which is developed in the DB group in Peking University (China), is a system towards building very large database using data from the Web for information extraction, integration and query answering. COMMIX has some innovative features, such as ontology-based wrapper generation, XML-based information integration, view-based query answering, and QBE-style XML query interface.
15215532
Estimating Answer Sizes for XML Queries
Estimating the sizes of query results, and intermediate results, is crucial to many aspects of query processing. In particular, it is necessary for effective query optimization. Even at the user level, predictions of the total result size can be valuable in "next-step" decisions, such as query refinement. This paper proposes a technique to obtain query result size estimates effectively in an XML database.Queries in XML frequently specify structural patterns, requiring specific relationships between selected elements. Whereas traditional techniques can estimate the number of nodes (XML elements) that will satisfy a node-specific predicate in the query pattern, such estimates cannot easily be combined to provide estimates for the entire query pattern, since element occurrences are expected to have high correlation.We propose a solution based on a novel histogram encoding of element occurrence position. With such position histograms, we are able to obtain estimates of sizes for complex pattern queries, as well as for simpler intermediate patterns that may be evaluated in alternative query plans, by means of a position histogram join (pH-join) algorithm that we introduce. We extend our technique to exploit schema information regarding allowable structure (the no-overlap property) through the use of a coverage histogram.We present an extensive experimental evaluation using several XML data sets, both real and synthetic, with a variety of queries. Our results demonstrate that accurate and robust estimates can be achieved, with limited space, and at a miniscule computational cost. These techniques have been implemented in the context of the TIMBER native XML database [22] at the University of Michigan.
7798629
Structural joins: a primitive for efficient XML query pattern matching
XML queries typically specify patterns of selection predicates on multiple elements that have some specified tree structured relationships. The primitive tree structured relationships are parent-child and ancestor-descendant, and finding all occurrences of these relationships in an XML database is a core operation for XML query processing. We develop two families of structural join algorithms for this task: tree-merge and stack-tree. The tree-merge algorithms are a natural extension of traditional merge joins and the multi-predicate merge joins, while the stack-tree algorithms have no counterpart in traditional relational join processing. We present experimental results on a range of data and queries using the TIMBER native XML query engine built on top of SHORE. We show that while, in some cases, tree-merge algorithms can have performance comparable to stack-tree algorithms, in many cases they are considerably worse. This behavior is explained by analytical results that demonstrate that, on sorted inputs, the stack-tree algorithms have worst-case I/O and CPU complexities linear in the sum of the sizes of inputs and output, while the tree-merge algorithms do not have the same guarantee.
1362728
Structural join order selection for XML query optimization
Structural join operations are central to evaluating queries against XML data, and are typically responsible for consuming a lion's share of the query processing time. Thus, structural join order selection is at the heart of query optimization in an XML database, just as (value-based) join order selection is central to relational query optimization. We introduce five algorithms for structural join order optimization for XML tree pattern matching and present an extensive experimental evaluation. Our experiments demonstrate that many relational rules of thumb are no longer appropriate: for instance, using dynamic programming style optimization is not efficient; limiting consideration to left-deep plans usually misses the best solution. Our experiments also show that a dynamic programming optimization with pruning (DPP) algorithm can find the optimal solution, with low cost relative to the traditional dynamic programming (DP) algorithm; and an optimization technique that only considers fully pipelined (FP) plans can very quickly choose a plan that in most cases is close to optimal. Our recommendation is that DPP should be used in XML query optimizers where query execution time is expected to be significant, and that FP should be used where it is important to find a good (but not necessarily the best) plan quickly.
15058650
Query estimation by adaptive sampling
The ability to provide accurate and efficient result estimations of user queries is very important for the query optimizer in database systems. In this paper, we show that the traditional estimation techniques with data reduction points of view do not produce satisfiable estimation results if the query patterns are dynamically changing. We further show that to reduce query estimation error, instead of accurately capturing the data distribution, it is more effective to capture the user query patterns. In this paper, we propose query estimation techniques that can adapt to user query patterns for more accurate estimates of the size of selection or range queries over databases.
6184263
An Efficient Approach to Extracting Approximate Repeating Patterns in Music Databases
Pattern extraction from music strings is an important problem. The patterns extracted from music strings can be used as features for music retrieval or analysis. Previous works on music pattern extraction only focus on exact repeating patterns. However, music segments with minor differences may sound similar. The concept of the prototypical melody has therefore been proposed to represent these similar music segments. In musicology, the number of music segments that are similar to a prototypical melody implies the importance degree of the prototypical melody to the music work. In this paper, a novel approach is developed to extract all the prototypical melodies in a music work. Our approach considers each music segment as a candidate for the prototypical melody and uses the edit distance to determine the set of music segments that are similar to this candidate. A lower bounding mechanism, which estimates the number of similar music segments for each candidate and prunes the impossible candidates is designed to speed up the process. Experiments are performed on a real data set and the results show a significant improvement of our approach over the existing approaches in the average response time.
11776269
Geometric invariants and applications under catadioptric camera model
This paper presents geometric invariants of points and their applications under central catadioptric camera model. Although the image has severe distortions under the model, we establish some accurate projective geometric invariants of scene points and their image points. These invariants, being functions of principal point, are useful, from which a method for calibrating the camera principal point and a method for recovering planar scene structures are proposed. The main advantage of using these in variants for plane reconstruction is that neither camera motion nor the intrinsic parameters, except for the principal point, is needed. The theoretical correctness of the established invariants and robustness of the proposed methods are demonstrated by experiments. In addition, our results are found to be applicable to some more general camera models other than the catadioptric one
16588936
Identifying important concepts from medical documents
Automated medical concept recognition is important for medical informatics such as medical document retrieval and text mining research. In this paper, we present a software tool called keyphrase identification program (KIP) for identifying topical concepts from medical documents. KIP combines two functions: noun phrase extraction and keyphrase identification. The former automatically extracts noun phrases from medical literature as keyphrase candidates. The latter assigns weights to extracted noun phrases for a medical document based on how important they are to that document and how domain specific they are in the medical domain. The experimental results show that our noun phrase extractor is effective in identifying noun phrases from medical documents, so is the keyphrase extractor in identifying important medical conceptual terms. They both performed better than the systems they were compared to.
13420664
Music Classification Using Significant Repeating Patterns
With the popularity of multimedia applications, a large amount of music data has been accumulated on the Internet. Automatic classification of music data becomes a critical technique for providing an efficient and effective retrieval of music data. In this paper, we propose a new approach for classifying music data based on their contents. In this approach, we focus on monophonic music features represented as rhythmic and melodic sequences. Moreover, we use repeating patterns of music data to do music classification. For each pattern discovered from a group of music data, we employ a series of measurements to estimate its usefulness for classifying this group of music data. According to the patterns contained in a music piece, we determine which class it should be assigned to. We perform a series of experiments and the results show that our approach performs on average better than the approach based on the probability distribution of contextual information in music.