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2.2 Structural Queries

Beeri and Kornatzky have suggested a logical query language that would allow structural queries over a hypertext network. First-order logic is too general since it ignores the particular characteristics of hypertext. Hence, there is a need for a structural query language to incorporate the notions of recursive and quantification constructs. The logic for the proposed query language is a mixture of propositional calculus (which has no predicates or variables) and quantifiers such as many, most, at least two, exactly five etc. [Beeri & Kornatzky, 1990]. The basic formulae of the logic are the propositions and assertions on attributes’ values. Queries use specifiers to directly retrieve edges, paths, and cycles. The set of elements retrieved is collapsed into a hypertext network. The output of a query being a hypertext network, users can incrementally compose queries. Thus, the combination of specifiers, quantifiers, and the collapsing of query answers into a new hypertext network makes it possible to express structural queries proposed by Halasz. Facilities also exist in this query language to view portions of the retrieved network based on the specification of filters. Research is also underway to develop a visual hypertext query language.

GraphLog is a visual query language implemented on top of the Neptune hypertext system front-end to the Hypertext Abstract Machine (HAM) [Consens & Mendelzon, 1989] . It addresses the following issues raised by Halasz: Search and query mechanisms, augmentation of the basic node and link model, virtual structures, computation over the hypertext network, and versioning. Using GraphLog, queries are formulated by drawing graph patterns. These patterns are then searched for in the hypertext network to yield subgraphs.

GraphLog is highly expressive and it uses the notions of deductive database theory and descriptive complexity. The language is powerful enough to allow the specification and manipulation of arbitrary subsets of the network and supports the computation of aggregate functions on the subgraphs of the hypertext document. It can support dynamically defined structures as well as inference capabilities. GraphLog is an extension of the graph-based query language called G+. G+ was extended by adding the notions of negation, aggregation, and improved semantics to make it simple, yet powerful. It can express structural queries which cannot be expressed in conventional database languages such as relational algebra. For example, it can perform an arbitrarily long sequence of join operations for which there is no equivalent single relational algebra query. It was designed to avoid explicit use of logic formulae and recursion.

The concept of incremental construction of queries can also be found in HyperBase (Schutt & Streitz, 1990]. It provides two sets of retrieval operations, one set with operations that affect the whole hypertext database, another set of functions that operate only with respect to a sub-network. Streitz et al., are also working on the design of a Hypertext Query Language (HTQL).