Extraction and Implication of Path Constraints

1998

Query languages for data with irregular structure use regular path expressions for navigation. This feature is useful for querying data where parts of the structure is either unknown, unavailable to the user, or changes frequently. Naive execution of regular path expressions is inefficient however, because it ignores any structure in the data. We describe two optimization techniques for queries with regular path expressions. Both rely on graph schemas for specifying partial knowledge about the data's structure. Query pruning uses this structure to restrict navigation to only a fragment of the data; we give an efficient algorithm for rewriting any regular path expression query into a pruned one. Query rewriting using state extents can eliminate or reduce navigation altogether; it is reminiscent of optimizing relational queries using indices. There may be several ways to optimize a query using state extents; we give a polynomial space algorithm that finds all such optimizations. For restricted forms of regular path expressions, the algorithm is provably efficient. We also give an efficient approximation algorithm that works on all regular path expressions

On The Move to …, 2003

2010

For many problems arising in the setting of graph querying (such as finding semantic associations in RDF graphs, exact and approximate pattern matching, sequence alignment, etc.), the power of standard languages such as the widely studied conjunctive regular path queries (CRPQs) is insufficient in at least two ways. First, they cannot output paths and second, more crucially, they cannot express relations among paths.

PRINCIPLES OF …, 2000

Reasoning on queries is a basic problem both in knowledge representation and databases. A fundamental form of reasoning on queries is checking containment, i.e., verifying whether one query yields necessarily a subset of the result of another query. Query containment is crucial in several contexts, such as query optimization, knowledge base verification, information integration, database integrity checking, and cooperative answering.

Lecture Notes in Computer Science, 2006

In this paper, we introduce preferential regular path queries. These are regular path queries whose symbols are annotated with preference weights for "scaling" up or down the intrinsic importance of matching a symbol against a (semistructured) database edge label. Annotated regular path queries are expressed syntactically as annotated regular expressions. We interpret these expressions in a uniform semiring framework, which allows different semantics specializations for the same syntactic annotations. For our preference queries, we study three important aspects: (1) (progressive) query answering (2) (certain) query answering in LAV data-integration systems, and (3) query containment and equivalence. In all of these, we obtain important positive results, which encourage the use of our preference framework for enhanced querying of semistructured databases.

Proceedings of the 1998 ACM SIGMOD international conference on Management of data - SIGMOD '98, 1998

Semistructured data is characterized by the lack of any fixed and rigid schema, although typically the data has some implicit structure.

2019

Path querying on Semantic Networks is gaining increased focus because of its broad applicability. Some graph databases offer support for variants of path queries e.g. shortest path. However, many applications have the need for the set version of various path problem i.e. finding paths between multiple source and multiple destination nodes (subject to different kinds of constraints). Further, the sets of source and destination nodes may be described declaratively as patterns, rather than given explicitly. Such queries lead to the requirement of integrating graph pattern matching with path problem solving. There are currently existing limitations in support of such queries (either inability to express some classes, incomplete results, inability to complete query evaluation unless graph patterns are extremely selective, etc).

1998

Abstract The problem of modeling semi-structured data is important in many application areas such as multimedia data management, biological databases, digital libraries, and data integration. In this paper, we base our work on bdfs, which is a formal and elegant model for semistructured data Buneman et al., 1997] where schemas are graphs whose edges are labeled with formulae of a theory T. We extend bdfs with the possibility of expressing constraints and dealing with incomplete information.

1999

ABSTRACT. We extend the model for semi-structured data proposed in [BUN 97], where both databases and schemas are represented as graphs, with the possibility of expressing different types of constraints on the nodes of the graphs. We discuss how the expressive power of the constraint language may influence the complexity of checking subsumption between schemas, and devise a polynomial algorithm for an interesting class of constraints.

2000

Abstract. Recently, there have been several proposals of formalisms for modeling semistructured data, which is data that is neither raw, nor strictly typed as in conventional database systems. Semistructured data models are graph-based models, where graphs are used to represent both databases and schemas.

2001

We are interested in the theoretical foundations of the optimization of conjunctive regular path queries (CRPQs). The basic problem here is deciding query containment both in the absence and presence of constraints. Containment without constraints for CRPQs is EXPSPACE-complete, as opposed to only NP-complete for relational conjunctive queries. Our past experience with implementing similar algorithms suggests that staying in PSPACE might still be useful. Therefore we investigate the complexity of containment for a hierarchy of fragments of the CRPQ language. The classifying principle of the fragments is the expressivity of the regular path expressions allowed in the query atoms. For most of these fragments, we give matching lower and upper bounds for containment in the absence of constraints. We also introduce for every fragment a naturally corresponding class of constraints in whose presence we show both decidability and undecidability results for containment in various fragments. Finally, we apply our results to give a complete algorithm for rewriting with views in the presence of constraints for a fragment that contains Kleene-star and disjunction.

1999

We extend the model for semi-structured data proposed in [4], where both databases and schemas are represented as graphs, with the possibility of expressing different types of constraints on the nodes of the graphs, and defining queries which are used to select graphs from a database. We show that reasoning tasks at the basis of query optimization, such as schema subsumption, query-schema comparison, query containment, and query satisfiability, are decidable.

Proceedings of the International Conference on …, 1993

We have developed a constraint-based parser capable of processing a word graph containing multiple sentence hypotheses. When syntactic constraints are applied to a word graph, our parser is able to prune the graph of many ungrammatical sentence hypotheses and limit the possible parses of the remaining sentences. However, in many cases syntactic information alone is insu cient for selecting a single sentence hypothesis from a word graph. Hence, we have added semantic constraints to our parser to further limit ambiguity. In this paper, we review the constraint parsing algorithm and then provide a simple example illustrating how syntactic and semantic features can be used to prune word candidates from a word graph and eliminate incorrect parses for the remaining sentences. We also report on the e ectiveness of syntactic and semantic constraints for reducing the ambiguity of word networks.

Lecture Notes in Computer Science

2000

The emerging eld of semistructured data leads to new ways of rep resenting data as schemaless or self describing However in many applications data has often some regularity and ignoring the possibly partial structure hinders the abilities to interpret the data and to access them e ciently In this paper we investigate a knowledge based approach for discovering partial implicit structures from semistructured data We show that semistructured data represented in the form of labeled directed graphs can be typed using description logics