we locate a number of reasons for this problem and propose several methods for node splitting and partial-tree restructuring, which lead to improved query-response times. We have implemented all methods and we present experimental results, which indicate that the proposed methods are superior in all cases to the standard one and up to 5-10 times better for medium and higher weights in inclusive (partial match) queries. Additionally, we have developed new functions for the performance estimation of signature trees which, in contrast to a previous estimation function, are able to take into account the outcome of different split methods and to provide more accurate estimation

Abstract—We present a new access method, called the path dictionary index (PDI) method, for supporting nested queries on object-oriented databases. PDI supports object traversal and associative search, respectively, with a path dictionary and a set of attribute indexes built on top of the path dictionary. We discuss issues on indexing and query processing in object-oriented databases; describe the operations of the new mechanism; develop cost models for its storage overhead and query and update costs; and compare the new mechanism to the path index method. The result shows that the path dictionary index method is significantly better than the path index method over a wide range of parameters in terms of retrieval and update costs and that the storage overhead grows slowly with the number of indexed attributes. Index Terms—Object-oriented database, aggregation hierarchy, index method, file structure, nested query.

Aiming at the efficient retrieval of objects with set-valued attributes, we introduce three variations of a new method in order to satisfy subset and superset queries. Our approach is to combine the advantages of two access methods, that of linear Hashing and of tree-shaped methods, on which other similar methods have been previously reported as well. Performance estimation analytical functions for each particular method are presented, followed by a thorough experimental comparison of all investigated structures, where analytical and experimental results deviate 10% on the average. Finally, the results of this performance evaluation are presented and discussed, clearly showing the superiority of the new methods reaching an improvement of up to 85%.

We present a new access method, called the path dictionary index (PDI) method, for supporting nested queries on object-oriented databases. PDI supports object traversal and associative search, respectively, with a path dictionary and a set of attribute indexes built on top of the path dictionary. We discuss issues on indexing and query processing in object-oriented databases, describe the operations of the new mechanism, develop cost models for its storage overhead and query and update costs, and compare the new mechanism to the path index method. The result shows that the path dictionary index method is significantly better than the path index method over a wide range of parameters in terms of retrieval and update costs and that the storage overhead grows slowly with the number of indexed attributes.

The S-tree is a dynamic height-balanced tree similar in structure to B+trees. S-trees store fixed length bit-strings, which are called signatures. Signatures are used for indexing textbases, relational, object oriented and extensible databases as well as in data mining. In this article, methods of designing multi-disk B-trees are adapted to S-trees and new methods of parallelizing S-trees are developed. The resulting structures aim at achieving performance gain by accessing two or more disks simultaneously. In addition, two different searching techniques that exploit parallel disk accessing are devised. Performance results of experiments based on the new structures and searching techniques are also presented and commented.

Predicate evaluation and object traversal are two critical issues for nested object query processing. Aiming at these two issues, we introduce a new method, the signature path dictionary, which combines signature techniques with the path dictionary organization designed for fast object traversals. We derive cost formulae for its storage overhead as well as the retrieval and update costs. Comparing to a previously proposed indexing organization, path signature, the signature path dictionary is superior in all aspects.

... well as hypertext and multimedia systems, need to handle complex data structures with set-valued attributes, which can be represented as bit strings, called signatures. A set of signatures can be stored in a file, called a signature file. In this paper, we propose a new method to organize a signature file into a tree structure, called a signature tree, to speed up the signature file scanning and query evaluation. In addition, the average time complexity of searching a signature tree is analyzed and how to maintain a signature tree on disk is discussed. We also conducted experiments, which show that the approach of signature trees provides a promising index structure.

this paper, we first present schemes to use signature files to process four types of set retrieval based on the "has-subset," "is-subset," "has-intersection," and "is-equal" conditions, and derive generic formulas estimating the false drops. Then, we derive three sets of concrete formulas to compute the false drop probabilities. We evaluate the validity of each set of the formulas with computer simulations, and discuss their advantages and disadvantages with respect to their reliability and computation cost. Among the three sets of formulas, two are refinements of our previous work presented in [13]. The remaining one is based on the theoretical research by Murphree and Aktug on the signature generation by superimposed coding [15]. The paper is organized as follows: In Sect. 2, we give an overview of the set retrieval in our context and the set query processing with signature files. In Sect. 3, we derive a set of generic formulas and three sets of concrete formulas estimating the false drops in the set query processing. In Sect. 4, we evaluate validity of the formulas with computer simulations and discuss advantages and disadvantages of each set of the formulas. Sect. 5 is the summary and conclusion.

Although object-oriented database systems offer more powerful modeling capability than relational database systems, their performance suffers from the increased complexity in the data model. Recently, a lot of research has focused on mitigating this problem by building indexes over single classes, class hierarchies, or nested object hierarchies. In this paper, we propose a new indexing method. It is based on the technique that employs signature files, but differs from the existing methods in two aspects: (1) all the signature files are organized into a hierarchy to filter irrelevant data as early as possible; (2) a signature file itself is stored as a tree structure (called a signature tree) to speed up signature scanning. Together with the concept of query signature hierarchies, this technique reduces the search space dramatically and, therefore, improves significantly the time complexity of query evaluation.

We follow signature-based approach to object-oriented query handling in this paper. The use of signature files as an index for full text search has been widely known and used. Signature file based access methods initially applied on text have now been used to handle set-oriented queries in Object-Oriented Data Bases (OODB). All the proposed methods use either efficient search method or tree based intermediate data structure to filter data objects matching the query. Use of search techniques retrieves the objects by sequentially comparing the positions of 1s in it. Such methods take longer retrieval time. On the other hand tree based structures traverse multiple paths making comparison process tedious. In this paper we describe a new indexing technique for representing signature file using the dynamic balancing of B+ tree called Signature Declustering tree (SD-tree). The structure has the positions of 1s in the signatures distributed over a set of leaf nodes. Using this for a given query signature all the matching signatures can be retrieved cumulatively from a single node. Also for signature insertion an optimal search path is calculated by keeping a threshold value and by using forward pointers in leaf nodes. To promote optimal search between subsequent queries the backward leaf node pointers are used. Experiments have been conducted to analyze the time and space overhead of the SD-tree by varying the signature length and the distribution of signature weight for varying query signature patterns. Also, to validate the proposed structure a hypothetical object schema is considered and sample queries evaluated. Povzetek: SD drevesa so uporabljena za objektno obravnavo vprašanj. 1